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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728501 (2008) https://doi.org/10.1117/12.819778
This PDF file contains the front matter associated with SPIE
Proceedings Volume 7285, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.
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Data Acquisition and Processing: Mechanism of Remote Sensing
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728502 (2008) https://doi.org/10.1117/12.812228
Wavelet transform is an important pretreatment tool to extract texture information, which can decompose
image as different level and provide rich detail information. But the tool is fit to any size spatial resolution image? The
paper gives several tests and extracts texture information from high and medium spatial resolution images, compares the
texture information; what's more, image classification is tested too. The result shows that wavelet transform cannot provide effective texture information for medium spatial resolution image.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728503 (2008) https://doi.org/10.1117/12.815679
This paper compares the normalized difference built-up index (NDBI) and normalized difference vegetation index
(NDVI) as indicators of surface urban heat island (SUHI) effects in MODIS imagery by investigating the relationships
between the land surface temperature (LST), NDBI and the NDVI. MODIS data were used to estimate the LST, NDBI
and NDVI from four different seasons for Changsha-Zhuzhou-Xiangtan metropolitan area. Our analysis indicates than
there is a strong linear relationship between LST and NDBI, whereas the relationship between LST and NDVI is much
less strong and varies by season. This result suggests NDBI is an accurate indicator of SUHI effects and can be used as a
complementary metric to the traditionally applied NDVI for analyzing LST quantitatively over the seasons for SUHI
studies.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728504 (2008) https://doi.org/10.1117/12.815691
In the preprocessing course of spatial data, different departments always have diverse naming methods when describing
the same geographical entity, due to different backgrounds and views of angle. There is also great difference among the
feature sets which are used to describe concepts of geo-ontology, making it difficult to conduct semantic interoperation
based on the theory of concepts reasoning in the information science. Consequently, this paper takes green land system
for example and presents a reasoning method of geo-ontology based on object-oriented remote sensing analysis. We
firstly establish an image hierarchical network system by using the object-oriented multi-scale segmentation technology.
Then, the mapping from domain ontologies to image objects is realized by the maximum area method. Finally, through
analyzing the features of image objects, the reasoning principles are built up, realizing the semantic interoperation
between concepts of ontologies and image objects.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728505 (2008) https://doi.org/10.1117/12.815701
The integration of the earth observation data and GIS data is a focal point in the research of remote sensing data analysis.
In this paper, after the conflation of the high resolution images and the land-use maps the segment and their features are
obtained. Then we do some researches about the uniformity between the features and land-use class. After the analyzing
using the traditional method, the result shows that the features of the segment are not in accord with land-use class of it.
Then we analyze this phenomenon and find three reasons. Moreover, the third reason, we think, may be the main factor.
So we propose a approach establishing the mapping between the features and the land-use class. The result of the
experiment is much better than the traditional method. It demonstrates the validity to deal with the non-uniformity in
earth observation data and GIS data.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728506 (2008) https://doi.org/10.1117/12.815791
For information lost phenomenon on RS image, we present a robust completion algorithm based on a single image
instead of adopting image placement measure. In order to avoid the occurrence of visually inconsistent results caused by
greedy patch-by-patch manner, we creatively introduce GIS accessorial data to guide structure completion and pose this
task in the form of a discrete global optimization problem. In the process of implementing this optimization scheme, our
method integrates exemplar-based texture synthesis techniques and Dynamic programming algorithm. By this way,
Information Compensation is separated into two independent processes to deal with. Comparative Experiments is
conducted and prove the efficiency of our method successfully.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728507 (2008) https://doi.org/10.1117/12.815820
The aim of this study is to examine the feasibility of Support vector regression (SVR) in retrieval of suspended sediment
concentration by comparing it with band ratio regression models. First, the remote sensing reflectance and the suspended
sediment concentrations were measured in field and in laboratory. The in situ dataset and laboratory dataset were used in
t developing retrieval models based on support vector regression and band ratio regression. Second, we select band ratio
regression model with high R-square value and low Root Mean Squared Error as the best band ratio regression model.
Finally, the best band ratio regression model was compared with SVR model in different datasets by leave-one-out cross
validation. The experimental results demonstrate that the prediction accuracy of support vector regression outperforms
the band ratio regression models based on the mean absolute error in general. SVR using all bands yielded slightly
superior results than using TM1 and TM4 bands in terms of accuracy. The findings suggest that the SVR model is
available using all bands data. The support vector regression can be applied in retrieval of suspended sediment
concentration without selecting bands and constructing band ratio expression. SVR is a promising alternative to
suspended sediment retrieval models.
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Teng Fei, Valentijn Venus, Bert Toxopeus, Andrew K. Skidmore, Martin Schlerf, Yaolin Liu, Sjef van Overdijk, Meng Bian
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728508 (2008) https://doi.org/10.1117/12.815981
Lizards are an "excellent group of organisms" to examine the habitat and microhabitat use mainly
because their ecology and physiology is well studied. Due to their behavioral body temperature
regulation, the thermal environment is especially linked with their habitat use. In this study, for
mapping and understanding lizard's distribution at microhabitat scale, an individual of Timon Lepidus
was kept and monitored in a terrarium (245×120×115cm) in which sand, rocks, burrows, hatching
chambers, UV-lamps, fog generators and heating devices were placed to simulate its natural habitat.
Optical cameras, thermal cameras and other data loggers were fixed and recording the lizard's body
temperature, ground surface temperature, air temperature, radiation and other important environmental
parameters. By analysis the data collected, we propose a Cellular Automata (CA) model by which the
movement of lizards is simulated and translated into their distribution. This paper explores the
capabilities of applying GIS techniques to thermoregulatory activity studies in a microhabitat-scale. We
conclude that microhabitat use of lizards can be explained in some degree by the rule based CA model.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728509 (2008) https://doi.org/10.1117/12.815983
In this study, we monitored the quality of fresh tea leaves as raw materials of tea products by
hyperspectral technology, as a way to explore the potential of hyperspectral remote sensing to detect
the taste-related chemical components with low concentration in living plants. At leaf scale, empirical
models have been established to find the relationships between quality-related chemicals in fresh tea
leaves and foliar spectral data. Tea polyphenols (TP) and amino acid (AA) and water-soluble protein
(SP) are three target chemicals in this paper. Near infrared spectroscopy (NIRS) was also been applied
to estimate these chemicals for dried and ground leaves in laboratory. They are compared in terms of
retrieval precision. Two main methodologies have been employed for modelling: (a) two bands
normalized ratio index (NRI), (b) partial least squares (PLS) regression. The PLS method was
performed using the original and transformed spectra: mean centred spectra, standard first derivative
and standard normal variate (SNV) transformed spectra. The results demonstrated that the biochemical
parameters related to the quality of tea can be estimated with satisfactory accuracy both at dried
powder and fresh leaf scales.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850A (2008) https://doi.org/10.1117/12.815986
As the important component of soil, soil organic matter not only provides every nutrient element for crop, but also has
determinant effect for forming of soil structure and melioration the soil physical character. Mapping and dating soil
organic matter is of great importance in soil use and evaluation. In this study we examine the feasibility of soil organic
matter content by using Hyperspectrally reflective remote sensing methodology. This technique was tested in Xiaochang
County located in Hubei province. The soil reflectance properties of samples were measured in the laboratory by ASD
field spectrometer. The correlation analysis related with organic matter content was processed from three factors: the
spectral reflectance parameter ((lgρ)', ρ/
ρ450-750 and (1/lgρ623)'/ (1/lgρ564)'). The results show that the correlation
coefficients of r values were: organic matter identification index (ρ/
ρ450-750) > logarithmic first derivative of reflectivity
((lgρ)') > organic matter mix identification index ((1/lgρ623)'/(1/lgρ564)'). Knowing these correlations we were able to
use the best prominence correlation of organic matter identification index of 1850nm wavelength as the variable
regression to build up statistical regression analysis. We used five model types (Linear Function, Logarithmic Function,
Quadratic Function, Power Function and Exponential Function) to forecast the soil organic matter content Hyperion
model. The accuracy assessment (R2= 0.8484) by relating forecasted organic matter values with Quadratic Function
regression showed that the model is reliable and significantly correlative with known stabilization processes throughout
the study area. The quantitative methodology developed in this study for refutations soil organic matter content can be
adapted to other regions throughout the world.
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Quanjun Jiao, Bing Zhang, Wenjuan Zhang, Di Wu, Yuangfeng Wu
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850B (2008) https://doi.org/10.1117/12.816010
Leaf Area Index (LAI) is an important parameter in terrestrial ecosystem. Wide width of HJ-1A CCD image causes
varied view angels. It is rather important to analyze HJ-1A CCD camera's geometrical features to improve the accuracy
of LAI production. This paper focuses on the imaging geometry characteristics of HJ-1A multi-spectral CCD camera,
and then brings a self-adaptive approach of retrieving vegetation parameter through analyzing the influence of sensor's
imaging geometry factor to vegetation parameter retrieval. This self-adopt approach couples remote sensing imaging
process model with vegetation information extraction model and studies systemically on the vegetation information
extraction general modeling, data simulation with the remote sensing image features, analyzing the influence of imaging
factor to vegetation information extraction and optimizing vegetation information extraction model. The validation result
shows that the method in this paper is much better than the simple semi-empirical model no consider of imaging
geometrical factor of HJ-1A CCD camera.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850C (2008) https://doi.org/10.1117/12.814992
SVM (Support Vector Machine) is a new kind of machine learning method , it can solve classification and regression
problems very successfully and accomplish classification with small sample incident perfectly. In this paper, the NPA is
proposed to compute the optimization problem to achieve the classification for hyperspectral remote sensing (RS) image
by "1 VS m" strategy and radial basis kernel function. Besides, a new method, the dual-binary tree + SVM algorithm is
proposed, to solve the mutil-class, high-dimensional(HD) problems of hyperspectral RS image. In the end, the test is
carried on the OMIS image. The comparative results of this algorithm with other methods are given, which shows that
our algorithm is very competitive, particularly for the small samples and non-equilibrium surface features. Both the
accuracy and speed of classification are improved greatly.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850D (2008) https://doi.org/10.1117/12.815331
Basic clustering algorithms including K-means, fusion c-means and C4.5 decision tree have been applied in cloud
detection with FY-2C data. With the limitation that no reliable template is available, supervised classification algorithm
is utilized to test the credibility of non-supervised classification algorithms, which contribute to generate a cloud
classification model with high credibility. It is proved that cloud classification product distributed by National Satellite
Meteorological Center enjoys a high credibility and stability. It is also demonstrated that FY-2C data is eligible to
classify cloud into 4 types as cumulonimbus, cirrostratus, dense-cirrus and low and middle cloud.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850E (2008) https://doi.org/10.1117/12.815783
Lagragian support vector machine (LSVM) is a linearly convergent Lagrangian, which is obtained by reformulating the
quadratic program of a standard linear support vector machine. To investigate the performance of the classifier working
on multispectral images with LSVM as optimizer, we devise a new test based on LSVMs for classifying multispectral
data in this work. First of all, data are preprocessed. To acquire the optimum bands for image classification,
multispectral image is mapped into a two-dimensional feature space to inspect the bands with redundant spectral
information. These extracted data acquired through the feature selection is named data group B relative to the original
data group A for a purpose of comparison. Then, to classify multiclass problem, binary classification is extended to
multiclass classification by pairwise method. Secondly, two groups of data are trained to find models. In this phase,
optimal C values are chosen carefully through trials with different values. Then, classifiers based on LSVMs with
optimal C values are used to yield optimal separating hyperplane (OSH). Lastly, in prediction phase, the two groups of
data are inputted respectively into each classifier for testing. These classifiers include ones with linear kernel and ones
with polynomial kernel of degree 2. The results of the experiment reveal that classifiers with LSVMs as an optimizer
have excellent performances with both linear kernel and polynomial kernel of degree 2. Bias caused by the differentia of
the two groups of data is not obvious.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850F (2008) https://doi.org/10.1117/12.815857
High spatial resolution remote sensing images are playing an increasing important role in various applications in the
world. As the fundamental work, classification of remote sensing is significant in the applications. This paper proposed
a new feature extraction approach based on the shape adaptive neighborhood (SAN) for the classification of high spatial
resolution remote sensing images. The heterogeneity based on the color characteristics was employed to determine the
SAN of each pixel. Then all the color features, texture features and shape features were extracted from each SAN, and
were fused by the feature level data fusion methods to the final feature space of the RS image. Then the features were
used to do the classification work. As the experiment results shown, the total precision of the classification was 0.9187,
and the kappa coefficient was 0.7950. By analyzing different maximum size of the SAN and different threshold of the
heterogeneity, the best maximum size of the SAN was 11*11 for the study area and the most suitable threshold was 0.5.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850G (2008) https://doi.org/10.1117/12.815883
In the traditional BNC model, the relationship between the attributes are the same for all the instances of the class
variable C. BMN classifier is a generalized form of BNC, in the sense that it allows different relationships among
attributes for every values of the class variable, and provides a unique net structure for every object class. This paper
proposes Bayesian Multi-nets (BMN) Models based on the analysis of conditional mutual information(CMI) between
image features of different objects classes, and constructs BMN classifier for remote sensing images on the basis of
experiment. Classification accuracy of single objects in BMN classifier outperforms that of traditional BN, proves the
latent value of the proposed models in the classification of remote sensing images.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850H (2008) https://doi.org/10.1117/12.815912
In this paper, we propose a new classification algorithm for high spatial resolution remote sensing data, which makes
use of both the spatial information and spectral information of the remote sensing data, and is also suitable for the
specific data format that high special resolution remote sensing data has. Because the classification is based on the
remote sensing raw data, image fusion process of the raw data can be avoided, which will lower the computational cost.
Moreover, the classification algorithm framework we propose can be extended for other segmentation algorithms.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850I (2008) https://doi.org/10.1117/12.815962
The radial basis function (RBF) neural network is a powerful method for remote sensing image classification. It has a
simple architecture and the learning algorithm corresponds to the solution of a linear regression problem, resulting in a
fast training process. The main drawback of this strategy is the requirement of an efficient algorithm to determine the
number, position, and dispersion of the RBF. Traditional methods to determine the centers are: randomly choose input
vectors from the training data set; vectors obtained from unsupervised clustering algorithms, such as k-means, applied to
the input data. These conduce that traditional RBF neural network is sensitive to the center initialization. In this paper,
the artificial immune network (aiNet) model, a new computational intelligence based on artificial immune networks
(AIN), is applied to obtain appropriate centers for remote sensing image classification. In the aiNet-RBF algorihtm, each
input pattern corresonds to an antigenic stimulus, while each RBF candidate center is considered to be an element, or cell,
of the immune network model. The steps are as follows: A set of candidate centers is initialized at random, where the
initial number of candidates and their positions is not crucial to the performance. Then, the clonal selection principle will
control which candidates will be selected and how they will be upadated. Note that the clonal selection principle will be
responsible for how the centers will represent the training data set. Finally, the immune network will identify and
eliminate or suppress self-recognizing individuals to control the number of candidate centers. After the above learning
phase, the aiNet network centers represent internal images of the inuput patterns presented to it. The algorithm output is
taken to be the matrix of memory cells' coordinates that represent the final centers to be adopted by the RBF network.
The stopping criterion of the proposed algorithm is given by a pre-defined number of iterations. The classification results
are evaluated by comparing with that of the k-means center selection procedures and other results from the literature
using remote sensing imagery. It is shown that aiNet-RBF NN algorithm outperform other algorithms and provides an
effective option for remote sensing image classification.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850J (2008) https://doi.org/10.1117/12.815965
Land use and land cover (LULC) data is essential to environmental and ecological research. However, semantic
heterogeneous of land use and land cover classification are often resulted from different data resources, different cultural
contexts, and different utilities. Therefore, there is need to develop a method to measure, compare and integrate between
land cover categories. To understand the meaning and the use of terminology from different domains, the common
ontology approach is used to acquire information regarding the meaning of terms, and to compare two terms to
determine how they might be related. Ontology is a formal specification of a shared conceptualization of a domain of
interest. LULC classification system is a ontology. The semantic similarity method is used to compare to entities of three
LULC classification systems: CORINE (European Environmental Agency), Oregon State (USA), and Taiwan. The
semantic properties and relations firstly have been extracted from their definitions of LULC classification systems. Then
semantic properties and relations of categories in three LULC classification systems are mutually compared. The
visualization of semantic proximity is finally presented to explore the similarity or dissimilarity of data. This study
shows the semantic similarity method efficiently detect semantic distance in three LULC classification systems and find
out the semantic similar objects.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850K (2008) https://doi.org/10.1117/12.816101
Texture features are recognized to be a special hint in images, which represent the
spatial relations of the gray pixels. Nowadays, the applications of the texture analysis in image
classification spread abroad. Combined with wavelet multi-resolution analysis or support vector
machine statistical learning theory, texture analysis could improve the quality of classification
increasingly. In this paper, we focus on the land cover for the Three Gorges reservoir using remote
sensing data SPOT-5, a new classification method, wavelet-SVM classifier based on texture
features, is employed for this study. Compare to the traditional maximum likelihood classifier and
SVM classifier only use spectrum feature, this method produces more accurate classification
results. According to the real environment of the Three Gorges reservoir land cover, a best texture
group is selected from several texture features. Decompose the image at different levels, which is
one of the main advantage of wavelet, and then compute the texture features in every sub-image,
and the next step is eliminating the redundant, every texture features are centralized on the first
principal components using principal component analysis. Finally, with the first principal
components inputted, we can get the classification result using SVM in every decomposition scale,
but what the problem we couldn't overlook is how to select the best SVM parameters. So an
iterative rule based on the classification accuracy is induced, the more accuracy, the proper
parameters.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850L (2008) https://doi.org/10.1117/12.816115
In many remote sensing image classification applications, interest focuses on a specific land-cover class. In these cases,
one-class classification (OCC) approach is appropriate, because one classifier can be trained with samples of target class
and just few or no samples of classes that are not of interest are required. However, it is always hard to build a training
sample set effectively to represent the target class completely. In this paper, an active learning is introduced for OCC
based on support vector data description (SVDD). In active SVDD learning, a SVDD classifier is started with a small
size of training samples and an expert is asked to label supplementary training data by asking only for the labels of the
most informative, unlabeled examples. Thus, it is possible to build a training sample set effectively to represent the target
class completely. The effectiveness of active SVDD is proved by preliminary experiments.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850M (2008) https://doi.org/10.1117/12.812103
In so far as geometric shape is concerned a curvilinear band is very similar to a road segment. Roads may be regarded as
a particular type of curvilinear bands. Many methods have been developed for extracting such targets, some of which
are based on edge information. It is very difficult to extract roads and curvilinear bands with no clear and continuous
boundaries using existing algorithms. To mitigate this problem a new strategy is presented in this paper. Edge lines are
detected by means of an improved Burns' method and Dynamic Programming. Target segments are then formed by
matching these edge lines. Connecting the obtained segments produces the final results. Experiments prove the
efficiency of the proposed method while being applied to extract complicated roads and curvilinear bands in different
kinds of images.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850N (2008) https://doi.org/10.1117/12.812467
Imaging spectroscopic technique has been used for the mineral and rock geological mapping and
alteration information extraction successfully with many reasonable results, but it is mainly used in arid
and semi-arid land with low vegetation covering. In the case of the high vegetation covering, the
outcrop of the altered rocks is small and distributes sparsely, the altered rocks is difficult to be
identified directly. The target detection technique using imaging spectroscopic data should be
introduced to the extraction of small geological targets under high vegetation covering area. In the
paper, we take Ding-Ma gold deposit as the study area which located in Zhenan country, Shanxi
province, the spectral features of the targets and the backgrounds are studied and analyzed using the
field reflectance spectra, in addition to the study of the principle of the algorithms, some target
detection algorithms which is appropriate to the small geological target detection are introduced. At last,
the small altered rock targets under the covering of vegetation in forest are detected and discriminated
in imaging spectroscopy data with the methods of spectral angle mapper (SAM), Constrained Energy
Minimization (CEM) and Adaptive Cosine Estimator (ACE). The detection results are reasonable and
indicate the ability of target detection algorithms in geological target detection in the forest area.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850O (2008) https://doi.org/10.1117/12.812495
This paper presents a BP neural network method to retrieve vegetation cover of the Drainage basin of Miyun
Reservoir based on the new remote sensing data - Beijing-1 microsatellite data. And the retrieval result was
compared with the one retrieved by the traditional methods. The compared results showed that for vegetation cover
retrieval in mountainous areas, neural network has the advantage of precise simulation of non-linear transmission
over traditional methods, especially for mountainous vegetation cover retrieval which traditional methods usually
fail.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850P (2008) https://doi.org/10.1117/12.813453
Hyperspectral and high spatial resolution remote sensing technology take important role in uranium geological
application, data mining and knowledge discovery methods are key to character spectral and spatial information of
uranium mineralization factors. Based on curvelet transform algorithm, this paper developed the image fusion
technology of hyperspectral (Hyperion) and high spatial data (SPOT5), and results demonstrated that fusion image had
advantage in denoising, enhancing and information identification. Used discrete wavelet transform, the spectral
parameters of uranium mineralization factors were acquired, the spectral identification pedigrees of typical quadrivalence
and hexavalence uranium minerals were established. Furthermore, utilizing hyperspectral remote sensing observation
technology, this paper developed hyperspectral logging of drill cores and trench, it can quickly processed lots of
geological and spectral information, and the relationship between radioactive intensity and abnormal spectral
characteristics of Fe3+ was established. All those provided remote sensing technical bases to uranium geology, and the
better results have been achieved in Taoshan uranium deposits in south China.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850Q (2008) https://doi.org/10.1117/12.814904
This paper aims at the extraction of roads and road network from high-resolution dual-polarization synthetic aperture
radar data over urban areas. According to the different features and applications for road network, the errors will be
brought in the detection algorithm if it was not selected correctly. We proposed a modified extraction method making full
use of available information to reduce such errors. In particular, we want to show how to implement road extraction
algorithms based on the D-S evidence theory to establish the frame of discernment. The responses of two line detectors
at the local analysis process were combined, which was done at the feature level by balancing the weight of two
propositions constructed by responses of two line detectors. Then the road network optimization is accomplished using a
Markov random field model of road, where both some contextual knowledge and global constraints were taken into
account. The experimental results indicate that the proposed method is promising for main roads detection of urban
areas.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850R (2008) https://doi.org/10.1117/12.814958
In this paper we focus on feature extraction method of complex objects from range data captured by vehicle-borne
laser scanning system. In our study, we classified the objects obtained by laser scanner into three types: road surface,
building facade and free sharps which consisted by scattered points. We have developed the corresponding methods for
the extraction of those objects. The DSCD (Density Statistics with Conformal Division) for road surface extraction and
DSEI (Density Statistics with Equal Interval) for building facade extraction. Especially, our experiment has shown that
the MST (Minimum Spanning Tree) is a good way for scattered points classification, and the free sharps are extracted
with high automation and efficiency.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850S (2008) https://doi.org/10.1117/12.815348
Tree height is an important biophysical parameter. It is a need for forest and biomass map for the estimation of carbon
budget. Polarimetric SAR interferometry (PolInSAR) has been applied successfully to retrieve biophysical parameters
from forest areas. In the real process, the retrieval result is not truthfulness because of non-volumetric scattering
decorrelation scatterer. The scatterer is generated by coherence noise. The scatterer will be misjudged and mistook for a
tree. Before Retrieving of Tree Height, non-volumetric scattering decorrelation scatterer needed to be removed. This
paper will propose to combine the linear and optimization polarization interferometric coherence to remove the nonvolumetric
scattering decorrelation scatterer. The retrieval results have been proved reasonable.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850T (2008) https://doi.org/10.1117/12.815899
In this paper, a multi-level image representation model is developed and used for multi-spectral remote sensing image
retrieval in order to narrow the gap between the low-level feature and high-level semantic. This model consists of an
image segmentation part, a feature extraction part and semantic extraction part. The first two parts aim at the extraction
of primitive region feature of an image. In these two steps, an improved JSEG algorithm is used to segment the image
stored in the database, then spectral feature and texture feature are extracted for each region. In semantic extraction part,
the semantic information hidden in different regions of different images is extracted by Bayesian method and expectation
maximization (EM) method. At last, positive example and negative example concept is used in image retrieval instead of
relevant feedback. Experiment shows that this method not only improves the accuracy of the result but also decreases the
complexity of retrieval.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850U (2008) https://doi.org/10.1117/12.815930
The automatic extraction of roads from high spatial resolution remote sensing images is the hotspot and difficulty in
remote sensing research, and has attracted extensive attention. Road extraction from remote sensing images is a leading
direction of remote sensing image processing and widely demanded in transportation, mapping, urban planning and other
fields. In this paper, the actuality of road extraction is investigated. The road extraction process is divided into five
phases, which are pre-processing, low-level processing, mid-level processing, high-level processing and the application
of extraction results. The methods used in each phase are analyzed. Low-level processing is considered to be the key and
foundation of road extraction. Based on the representative method in low-level processing, mathematical morphology,
this paper presents an approach for automatic road extraction and tests the method on remote sensing image. The
experimental result shows the efficiency of the presented approach.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850V (2008) https://doi.org/10.1117/12.815998
The abundance of high resolution image information and the intensity of urban spatial system can be combined
organically in the process of image understanding, information extraction and quota measurement. The evaluation
indices of urban land use intensity extracted from Quickbird image include building density, floor ratio area, green ratio,
vacancy ratio, and etc. Firstly, land use condition in the research area is acquired through the overlay of Quickbird image
and Wuhan land use map. Secondly, the study adopts spectral threshold segmentation method to extract building
shadow, object-oriented classification method to obtain building base area, shadow-based height reversion approach to
estimate building height in typical urban residential block and object-oriented segmentation and classification approach
to estimate concerned indices in city village. In the end, the comparison and discussion of urban land intensity are made
according to BD and FAR in urban residential block and city village respectively. It is concluded that FAR (floor ratio
area) in urban residential block can be planned higher and BD (building density) in city village should be lower
according to the present planning regulations in Wuhan.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850W (2008) https://doi.org/10.1117/12.810206
ADS40 from Leica Geosystems is new-type airborne digital camera, which has aggregated worldwide focus
in application fields of aerial photogrammetry and remote sensing nowadays, with its noticeable superiority in
interpreting and mapping the comprehensive conditions of ground surface. At the same time, its special characteristics
make the data processing some complicated. Based on the long-team research and the experiment on usage of ADS40,
the paper presented the workflow in details including data capture, processing and application of ADS40, described some
problem and exercise in practice.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850X (2008) https://doi.org/10.1117/12.812373
Accurate atmospheric correction is an important and essential process in ocean color remote sensing because the
influence of atmosphere account for the main part of signals received by sensors. Traditional methods usually depend on
in-situ measured parameters of atmosphere and could not be applied in operational system. In this paper, MODIS
products synchronize with Beijing-1 micro-satellite image were used to extract the parameters of atmosphere. we chose
a marine space of clean water far away from the coast in MODIS image and used the products include MOD02, MOD03
and MOD07 to calculate the aerosol radiance of near-infrared bands of MODIS which were used to extrapolate the
aerosol radiances of each band of Beijing-1 micro-satellite. Brought the results into radioactive transfer equation and
fulfilled atmosphere correction. We found this method can enhanced the detail information of water body, especially to
case 2 water. We compared the correction results with original image and the results from 6S model; its effect was
consistent well with real conditions and better than 6S model. All these indicated that this method is feasible to
atmospheric correction of turbid coastal waters and expands the application of multi-spectral sensors in ocean color
remote sensing.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850Y (2008) https://doi.org/10.1117/12.813381
The hyperspectral reflectance for rape fresh leaves and data of chlorophyll and total nitrogen content were acquired in
primary growth stages under different nitrogen levels in order to monitor rape status and diagnose nitrogen using remote
sensing method. A new method was developed for estimating the nitrogen nutrition of rape using continuum-removed
method, which generally used in spectral analysis on rock and mineral. Based on the continuum-removed treatment and
the correlation between absorption feature parameters and total nitrogen content of fresh leaves, results show that
reflectance at the visible region decreased with increasing in the nitrogen fertilization, and continuum-removed
operation can magnify the subtle difference in spectral absorption characteristics arose from the nitrogen stress on rape.
During the seeding stage, bud-emerging stage and flowering stage of rape, total area of absorption peak, area left of the
absorption peak and area right of the absorption peak in 550-750 nm region increased with increasing in the nitrogen
fertilization, but it was opposite for the area-normalized maximal absorption depth. The correlation analysis indicated
that it is at seeding stage that the relation between absorption characteristics parameters and leaf total nitrogen was best
close. The research demonstrated that continuum-removed method is a feasible method for quantificational evaluation
of rape nitrogen nutrition, and the seeding stage of rape is the best stage for assessment of rape nitrogen nutrition based
on absorption characteristics of fresh leaves.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72850Z (2008) https://doi.org/10.1117/12.814071
This paper extended the best tradeoff fast intensity-hue-saturation (BTFIHS) fusion to a more general model. Firstly,
based-on the methods proposed by previous researches, we integrated injecting strategy of spatial detail information into
the fusion model and also adopted the idea of BTFIHS to keep the intensity unchanged with the corresponding pixel in
panchromatic (PAN) image, while the hue and saturation of every pixel using BTFIHS were equal to them using tradeoff
fast intensity-hue-saturation (TFIHS). Then we got a general formula of the improved best tradeoff for high-resolution
image fusion based-on getting injecting parameter by spectral reflection function (SRF). At last, several experiments
were carried on to analysis and discuss the quality of the new methods compared with their originals. Results show that
the new method could yield a "true" high-resolution multispectral (MS) image, with vast improvement in blue band and
nearly 3.3% improvement in Q4 for all bands.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728510 (2008) https://doi.org/10.1117/12.814901
The ADS40 system is a multi-line-array digital photogrammetry system. It takes the photo of terrain by pushbroom
scanning. Highly integrated with POS, it can obtain the orientation elements for every scan line through the post-process
of POS. For the existence of system errors of GPS and IMU, the Orientation elements may not satisfy the highly precise
application. It can be expressed with the function of time. In order to improve the accuracy of the orientation elements of
each scan line, Aerial triangulation must be used. We set out from the principle of photogrammetry, analyze the imaging
principle of ADS40, and put forward the imaging equations of ADS40 and the error equations of POS. We discuss on the
relationship between the orientation elements of each scan line and time, and form the function of the orientation
elements of each scan line and time. By introducing the conception of orientation fix we derive the adjustment math
model which include the orientation elements obtained through the post-process of POS. Therefore we may illuminate
the system errors or occasional errors of each observed value by adjustment, and achieve the aim to raise the accuracy of
orientation elements.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728511 (2008) https://doi.org/10.1117/12.814925
Synthetic aperture radar (SAR) is an active remote sensing sensor. It is a coherent imaging system, the speckle is its
inherent default, which affects badly the interpretation and recognition of the SAR targets. Conventional methods of
removing the speckle is studied usually in real SAR image, which reduce the edges of the images at the same time as
depressing the speckle. Morever, Conventional methods lost the information about images phase. Removing the speckle
and enhancing the target and edge simultaneously are still a puzzle. To suppress the spckle and enhance the targets and
the edges simultaneously, a half-quadratic variational regularization method in complex SAR image is presented, which
is based on the prior knowledge of the targets and the edge. Due to the non-quadratic and non- convex quality and the
complexity of the cost function, a half-quadratic variational regularization variation is used to construct a new cost
function,which is solved by alternate optimization. In the proposed scheme, the construction of the model, the solution
of the model and the selection of the model peremeters are studied carefully. In the end, we validate the method using the
real SAR data.Theoretic analysis and the experimental results illustrate the the feasibility of the proposed method.
Further more, the proposed method can preserve the information about images phase.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728512 (2008) https://doi.org/10.1117/12.816357
The orthometric height system plays a key role in geodesy, and it has broad applications
in various fields and activities. On an arbitrary equigeopotential surface, there does not exist the
frequency shift of an electromagnetic wave signal. However, between arbitrary two different
equigeopotential surfaces, there exists the frequency shift of the signal. Just due to this principle
of nature, one can determine the geopotential difference as well as the orthometric height
difference between two separated points P and Q using electromagnetic wave signals,
especially the GPS signals. GPS signals with a definite frequency f are emitted and two
receivers at P and Q on ground receive the signals coming from the emitter simultaneously.
The frequencies of the signals are recorded by receivers at P and Q, and consequently the
frequency difference (shift) between the received frequencies of the signals at P and Q is
determined. Then, the geopotential difference between these two points is determined based on
the geopotential frequency shift equation, and the corresponding orthometric height difference is
further determined based on the Bruns' formula. Further, using this approach a unified world
height datum could be realized, because P and Q could be chosen quite arbitrarily, e.g., they
are located on two separated continents or islands.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728513 (2008) https://doi.org/10.1117/12.815334
This paper introduce a new method for rapid extracting the planar features by integrating their point cloud and digital
images, the method is more efficient than any planar feature extracting methods based on one of the both type data and
can get the accurate 3D object boundaries. The main idea and the basic data processing flow about the presented method
are discussed in detail, and a test with the data of a building side face is employed to analyzing the efficiency and the
accuracy of the presented method. Some conclusions and future work are given in the last section.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728514 (2008) https://doi.org/10.1117/12.815335
C factor, known as cover and management factor in USLE, is one of the most important factors since it represents the
combined effects of plant, soil cover and management on erosion, whereas it also most easily changed variables by men
for it itself is time-variant and the uncertainty nature. So it's vital to compute C factor properly in order to model erosion
effectively. In this paper we attempt to present a new method for calculating C value using Vegetation Index (VI)
derived from multi-temporal MODIS imagery, which can estimate C factor in a more scientific way. Based on the theory
that C factor is strongly correlated with VI, the average annual C value is estimated by adding the VI value of three
growth phases within a year with different weights. Modified Fournier Index (MFI) is employed to determine the weight
of each growth phase for the vegetation growth and agricultural activities are significantly influenced by precipitation.
The C values generated by the proposed method were compared with that of other method, and the results showed that
the results of our method is highly correlated with the others. This study is helpful to extract C value from satellite data
in a scientific and efficient way, which in turn could be used to facilitate the prediction of erosion.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728515 (2008) https://doi.org/10.1117/12.815423
This paper discusses a new method for the automatic matching of ground control points (GCPs) between satellite remote
sensing Image and digital raster graphic (DRG) in urban areas. The key of this method is to automatically extract tie
point pairs according to geographic characters from such heterogeneous images. Since there are big differences between
such heterogeneous images respect to texture and corner features, more detail analyzations are performed to find
similarities and differences between high resolution remote sensing Image and (DRG). Furthermore a new algorithms
based on the fuzzy-c means (FCM) method is proposed to extract linear feature in remote sensing Image. Based on linear
feature, crossings and corners extracted from these features are chosen as GCPs. On the other hand, similar method was
used to find same features from DRGs. Finally, Hausdorff Distance was adopted to pick matching GCPs from above two
GCP groups. Experiences shown the method can extract GCPs from such images with a reasonable RMS error.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728516 (2008) https://doi.org/10.1117/12.815453
New technologies and automated systems (such as multi-sensor systems) allow us to collect and store a large amount of
spatial data in a quite efficient and inexpensive way. Especially, the advent of remote sensing and GIS has great
enhanced our capabilities to capture spatial data. However raw data are seldom useful without some kind of processing,
it needs more powerful technologies to deal with the databases. Therefore, spatial data fusion and data mining have been
used in this domain. They can improve the efficiency and accuracy of spatial information utilization. In this paper, we
focused on how to fusion spatial data for decision making by learning Bayesian networks. A review is presented on
spatial data fusion. We propose a method of spatial data fusion based on Bayesian networks, which is optimized by using
the theory of Particle Swarm Optimization (PSO). And then we showed a case study for spatial data fusion based on the
approach. The experimental results are given to illustrate the practical feasibility of the proposed technique. Eventually,
we conclude with a summary and a statement of future work.
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Feilong Ling, Zengyuan Li, Erxue Chen, Qinmin Wang
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728517 (2008) https://doi.org/10.1117/12.815613
The objective of this study is to exploit the new features of ALOS PALSAR dual polarization mode data and to develop
novel classification method for forest mapping in heterogeneous areas. A test site was selected in Fujian province in
southeast of China. Traditionally, forest is detected by its low coherence, low temporal variability of the backscattering
intensity and mediate backscattering intensity. However, the analyses in this paper indicate that it is not possible to
discriminate forest from nonforest by any single PALSAR feature in this test site. After examination the dependences of
the multitemporal backscatter intensity, the polarimetric parameters and the interferometric coherence on different land
cover types, a hierarchical classification method is proposed for coastal forest and hilly forest mapping. The forest maps
are validated by forest inventory data and SPOPT-5 images. The results show that multitemporal PALSAR dual
polarization data can accurate maps for coastal forest in flat areas using the proposed method. The capability to map
forest in hilly regions is still limited.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728518 (2008) https://doi.org/10.1117/12.815737
In order to raise the intelligent level and improve cooperative ability of grid. This paper proposes an agent oriented
middleware, which is applied to the traditional OGSA architecture to compose a new architecture named CIG
(Cooperative Intelligent Grid) and expounds the types of cooperative processing of remote sensing, the architecture of
CIG and how to implement the cooperation in the CIG environment.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728519 (2008) https://doi.org/10.1117/12.815808
An improved method of wavelet threshold denoising is introduced and
applied to hyperspectral imagery denoising in spectral domain. This method estimates
a threshold value for each spectrum. Thresholds are set to a scalar specifying the
percentage of cumulative power to retain in the filtered wavelet transform. Find the
actual percent corresponding to these coefficients. During the processing, four
families of mother wavelets (Symlets, Daubechies, Haar and Coiflet) are tested in a
series of experiments to estimate the functioning of those wavelets and thresholding
parameters. Experimental results show that the proposed algorithm with Coiflet
provides an improvement in SNR for hyperspectral data specially.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851A (2008) https://doi.org/10.1117/12.815884
Laser scanning is an effective way to acquire geometry data of the cultural heritage with complex architecture. After
generating the 3D model of the object, it's difficult to do the exactly texture mapping for the real object. we take effort to
create seamless texture maps for a virtual heritage of arbitrary topology. Texture detail is acquired directly from the real
object in a light condition as uniform as we can make. After preprocessing, images are then registered on the 3D mesh
by a semi-automatic way. Then we divide the mesh into mesh patches overlapped with each other according to the valid
texture area of each image. An optimal correspondence between mesh patches and sections of the acquired images is
built. Then, a smoothing approach is proposed to erase the seam between different images that map on adjacent mesh
patches, based on texture blending. The obtained result with a Buddha of Dunhuang Mogao Grottoes is presented and
discussed.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851B (2008) https://doi.org/10.1117/12.815896
The development of remote geological interpretation technology is booming during recent years.
However, there is a significant obstacle for extracting geology information from remote sensing
imagery--the presence of clouds and their shadows. Diverse techniques have been proposed including
different algorithms such as filtering algorithm and multi-temporal cloud removing algorithm to solve
the problem. This paper presents a modified solution to denoise the haze, based on ETM+ imagery.
First of all, wavelet transform is applied to Band1, Band2 and Band3 imagery to determine the clear
region and different levels of cloud regions. Then all pixels of the ETM+ imagery are classified to
specific cover types after the cluster analysis of band4, Band5 and Band7. At last, the mean reflectance
matching is performed in the first three bands separately according to different cover types in both clear
region and cloud region. Above all, the method is implemented by IDL. The results show that this
modified method not only can quantitatively determine the cloud area but also can remove cloud from
imagery efficiently. Moreover, compared with the homomorphic filtering method, the experiment
results of the proposed method is much more satisfying in Geology Interpretation.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851C (2008) https://doi.org/10.1117/12.815928
Among all enhancement techniques being developed over the past two decades, anisotropic diffusion has received a lot
of attention and has experienced significant developments, with promising results and applications in several specific
domains. The elegant property of the technique is that it can enhance images by reducing undesirable intensity variability
within the objects in image, while improving signal-to-noise ratio (SNR) and enhancing the contrast of the edges in
scalar and, more recently, in vector-valued images, such as color, multispectral and hyperspectral imagery. In this paper,
we firstly analyze two complementary schemes-variational methods and nonlinear diffusion partial differential
equations (PDEs), in terms of edge enhancement. Based on these analyses, a general flexible class of hyperspectral
forward-and-backward (FAB) diffusion process will be proposed, which can achieve the main requirements for edgepreserving
regularization with image enhancement. In addition, we use additive operator splitting (AOS) scheme to
speedup the numerical evolution of the nonlinear diffusion equation with respect to traditional explicit schemes. The
performance of the vector-valued FAB diffusion PDE is studied using some hyperspectral remote sensing images.
Experimental results on these images are shown the validity and effectiveness of the proposed method.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851D (2008) https://doi.org/10.1117/12.815932
The study on epipolarity model of satellite stereo-imagery has been the research focus in application field of remote
sensing for a long time. So far, there are basically two technical routines for exploring the epipolarity model of satellite
images: one totally disregards any geometric sensor model when establishing the epipolar relations but figures out the
epipolar curves in image-space by image correspondence and mathematical modeling, e.g. the Polynomial Fitting Model
(PFM); on the contrary, the other attempts to exploit the epipolar relations based on specific sensor models, such as the
Projection Trajectory based Epipolarity Model (PTEM), the Parallel Projection Transformation based Epipolarity Model
(PPEM), etc. Although such models have been studied and used to generate epipolar images of satellite stereo pairs,
some technical limitations still exist when taking the universality, applicability and implemental simplicity into account.
Accordingly, this paper proposes a novel epipolarity model for satellite stereo-imagery based on the Virtual Horizontal
Plane (VHP) of object-space. Firstly, the principle of the VHP-based epipolarity model is described; and then, the
workflow of VHP-based epipolar resampling is outlined in detail; finally, to verify the feasibility and correctness of new
theory and method, the approximate epipolar images of SPOT5-HRG stereo-imagery are generated. It is demonstrated
that the vertical parallaxes of conjugate image points have all reached the sub-pixel level after epipolar resampling;
besides, by rearranging the approximate epipolar lines on the VHP defined in our method, the stereoscopic model that is
horizontal to the object-space and with consistent resolution can be available.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851E (2008) https://doi.org/10.1117/12.815988
This paper introduces three methods of eliminating shadow on airborne SAR images, which are increasing overlap ratio,
imaging on both sides and imaging on across orientation. Reason and factors of causing shadow is analyzed in this paper.
The effect of eliminating shadow using the three methods mentioned is analyzed quantitatively. Given the side-looking
angle is from 20 degree to 70 degree. When the slope of reversing side-looking orientation is smaller than 70 degree, if
SAR images' overlap ratio is 75%, shadow incidence can be reduced to the slope from 57.5 degree to 70 degree. At the
same time, if imaging on both sides is used, shadow can be eliminated absolutely when the slope of one side is between
57.5 degree to 70 degree, and shadow can be eliminated in the condition of vale bottom's width is more than the
threshold value mentioned in this paper when the slopes of both sides are between 57.5 degree to 70 degree. When the
slope of reversing side-looking orientation is bigger than 70 degree and vale bottom's width is less than the threshold
value mentioned in this paper, air line which flight track is across vale can be adopted in order to avoiding shadow effect.
The reasons caused shadow by terrain and eliminating methods used are analyzed in Hengduan Mountain area, air lines
are designed in this area for obtaining airborne SAR images based on above.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851F (2008) https://doi.org/10.1117/12.816025
An algorithm for satellite tracking and orbit prediction is presented in detail. Firstly, the satellite's position and velocity
are calculated by the Simplified General Perturbations Version 4 and Simplified Deep-space Perturbation Version 4
(SGP4/SDP4) orbit propagation algorithms. And we put forward "Two-Point-Pair" which means two points that the
CCD of satellite's IFOV rays intersecting with the earth. We make use of the "Two-Point-Pair" to calculate the accuracy
bounding box of satellite at the instantaneous time through the satellite's position and velocity above. Besides, we build a
system called GeoGlobe to simulate the algorithm. The system can be used to simulate all kinds of satellites that the
Two-Line Element (TLE) Sets files can provide.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851G (2008) https://doi.org/10.1117/12.816609
This paper presents a universal maximum a posteriori (MAP) based reconstruction method which can be used for
destriping, inpainting (the removal of dead pixels) and super resolution reconstruction (the recovery of a high resolution
image from several low resolution images). In the MAP framework, the likelihood probability density function (PDF) is
constructed based on a linear image observation model, and a robust Huber-Markov model is used as the prior PDF. A
gradient descent optimization method is employed to produce the desired image. The proposed algorithm has been tested
using MODIS images for destriping and super resolution reconstruction, and CBERS (China-Brazil Earth Resource
Satellite) and QuickBird images for simulated inpainting. The experiment results and quantitative analyses verify the
efficacy of this algorithm.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851H (2008) https://doi.org/10.1117/12.816692
Image registration is a fundamental process in many remote sensing applications, such as image fusion, temporal
change detection. Generally, Algorithms for image registration can be classifeed into two categories: featurebased
and area-based methods. feature-based methods are relatively fast, robust and reliable, and area-based
methods can get high accuracy with high computational cost. Because the result produced by traditional feature
detector may vary with image contrast, it is dificult to set appropriate thresholds automatically for the reference
image and sensed image. To solved these problem, an automatic approach for image registration is presented in
this paper. It use a feature-based approach to get a coarse registration at first. Then, area-based method used
to improve the accuracy of the result. In feature detection stage, it employs a feature detector implemented in
frequency domain to obtain features with normalized measure. Constant thresholds can be applied for different
images. Due to feature matching is time-consuming and computation expensive, line features detected from the
images with approximate direction are mapped into Hough space to estimate the transformation parameters
with Modified Iterative Hough Transform method. Furthermore, it use a hierarchical framework to speed up the
registration process. The experiments show that the approach mentioned above is feasible and efficient.
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Data Acquisition and Processing: Image Restoration and Segmentation
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851I (2008) https://doi.org/10.1117/12.815420
Segmentation of Point cloud data is a key but difficult problem for architecture 3D reconstruction. Because compared to
reverse engineering, there are more noise in ancient architecture point cloud data of edge because of mirror reflection and
the traditional methods are hard that is not fuzzy in the preceding part of this paper, these methods can't embody the case
of the points of borderline belonging two regions and it is difficult to satisfy demands of segmentation of ancient
architecture point cloud data. Ancient architecture is mostly composed of columniation, plinth, arch, girder and tile on
specifically order. Each of the component's surfaces is regular and smooth and belongingness of borderline points is very
blurry. According to the character the author proposed a modified Fuzzy C-means clustering (MFCM) algorithm, which
is used to add geometrical information during clustering. In addition this method improves belongingness constraints to
avoid influence of noise on the result of segmentation. The algorithm is used in the project "Digital surveying of ancient
architecture--- Forbidden City". Experiments show that the method is a good anti-noise, accuracy and adaptability and
greater degree of human intervention is reduced. After segmentation internal point and point edge can be districted
according membership of every point, so as to facilitate the follow-up to the surface feature extraction and model
identification, and effective support for the three-dimensional model of the reconstruction of ancient buildings is
provided.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851J (2008) https://doi.org/10.1117/12.815625
Image segmentation is essential for information extraction from remote sensing image, but it remains the lacks of a
general mathematical theory, object merging for poor object boundary localization, dealing with object fragmentation
and sensitivity of current procedures to noise. This paper focuses on hyper-spectral image segmentation using
probabilistic neural networks (PNN). The methodology, implementation and optimization of a PNN are studied, and a
constructed PNN is applied to segment hyper-spectral image. The experience demonstrates main advantage of a PNN
that it has quick training and learning, gives a measurement of confidence associated with an output, and has the ability
to process large data set. It is concluded that the PNN is superior in image segmentation and the obtained results are
satisfied.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851K (2008) https://doi.org/10.1117/12.815864
In this paper, a new texture segmentation approach based on Markov random field (MRF) and global optimal method of
particle swarm optimization (PSO) is proposed. According to this approach, firstly the MRF texture model is established,
and potential function of Gibbs distribution and the calculating method of Gibbs parameters are represented. Then the
fitness function is designed and the PSO is adopted here to solve the maximum a posterior (MAP) estimate. Finally, a
comparison of the new algorithm with the Metropolis algorithm and the Gibbs Sampler is made in texture segmentation
of remote sensing images. Results show that PSO algorithm can reduce the computational complexity and is much more
efficient.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851L (2008) https://doi.org/10.1117/12.815885
We propose an efficient, hybrid Fourier-Contourlet regularized deconvolution (ForCorRD)
algorithm that performs noise regularization via scalar shrinkage in both the Fourier and Contourlet
domains. It is based on and more efficient to the famous Fourier-Wavelet regularized deconvolution
(ForWaRD) algorithm. The Fourier shrinkage exploits the Fourier transform's economical representation
of the colored noise inherent in deconvolution, whereas the contourlet shrinkage exploits the contourlet
domain's economical representation of piecewise smooth signals and images. Like the ForWaRD algorithm,
ForCoRD is also applicable to all ill-conditioned deconvolution problems. In the same experiment condition
for nature images' debluring, we prove that ForCoRD outperforms ForWaRD's in terms of both visual
quality and PSNR performance.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851M (2008) https://doi.org/10.1117/12.815892
The performance of high-resolution imaging with large optical instruments is severely limited by atmospheric
turbulence. Image deconvolution such as iterative blind deconvolution (IBD) and Richardson-Lucy (RL) deconvolution
are required. The IBD method involves the imposition of constraints such as conservation of energy, positivity, and finite
support, with known size, alternately on the image and the PSF in the spatial and Fourier domains, until convergence.
The iterative RL solution converges to the maximum likelihood solution for Poisson statistics in the data. Properties of
the RL algorithm which make it well-suited for IBD are energy conservation and the sustenance of nonnegativity. So, RL
was incorporated into the IBD framework. In this paper, an enhanced Richardson-Lucy-based iterative blind
deconvolution (ERL-IBD) algorithm is proposed to restore the blurred images due to atmospheric turbulence. The ERLIBD
incorporates dynamic PSF support estimation, bandwidth constraint of optical system, and the asymmetry factor
update. The experimental results demonstrate that the ERL-IBD algorithm works better than IBD algorithm in
deconvolution of the blurred-turbulence image.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851N (2008) https://doi.org/10.1117/12.815996
We always suffer the speckle noise when SAR image is used. In order to facilitate image interpretation, finding a speckle
reduction method is important and has practical significance. We propose a method which uses fractal net evolution
segmentation approach to find homogenous region to replace the traditional rectangular window. The experiment proves
our method is more effective than the other traditional methods.
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Data Acquisition and Processing: Orbit and Attitude Determination
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851O (2008) https://doi.org/10.1117/12.814899
Along with the rapid development of modern space science, it is becoming a hot topic to use network spacecrafts for
deep space detection or earth observation. And that autonomous relative navigation is one of key technologies for
network spacecraft system. In this paper, we now propose a new autonomous relative navigation algorithm for network
spacecraft system with quaternion. In this abstract, we just add some pertinent remarks to listing the main work of this
paper: (1) a 3-D line and its transformation can be described by using dual quaternion finely. Moreover, the algorithm
with dual quaternion is used to calculate both relative position and attitude organically. So in the first topic section, how
to depict a 3-D line and its transformation with dual quaternion will be introduced; (2) in second topic section, the
thought of how to select the state valuable will be expatiated here firstly, and then we built the state equation state
equation according to Clohessy-Wiltshire (C-W) equation and quaternion differential equation; (3) in this paper, the state
valuable and the observation valuable are inconsistent for the observation unit is feature line. So how to build the
relationship between the state valuable and the observation valuable is very important. Here through the observation
transition matrix, we build the observation equation according to con-line equation of vision navigation; (4) finally, we
give an example about network spacecraft system. The simulation results show that proposed algorithm is valid for
network spacecraft system.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851P (2008) https://doi.org/10.1117/12.815352
A very important factor for recovering the high accuracy Earth's gravity field is the knowledge of the GOCE satellite
orbit. In this paper, a 30-day arc of the GOCE satellite orbit (called the reference orbit) was simulated using dynamic
orbit integration method, and the perturbation accelerations due to the lunisolar perturbations, the Earth tides, the ocean
tides, the atmospheric tides, the pole tides, the relativity effects, the atmospheric drag and the solar radiation pressure
were computed along the simulated orbit according to the dynamic models. Then the maximum perturbation
accelerations and their percentage contribution in the sum of all accelerations due to the aforementioned forces were
given and analyzed. In addition, the various variants of the satellite orbit (called the modified reference orbits) were
obtained by subtracting the selected conservative forces to the satellite motion model for the reference orbit. Finally, the
motion of GOCE satellite that influenced by the conservative forces were analyzed through comparing the satellite
positions between the reference orbit and the modified reference orbits. The analysis results can be as a reference for the
precise orbit determination and gravity field recovery of GOCE mission.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851Q (2008) https://doi.org/10.1117/12.816216
Space Very Long Baseline Interferometry (SVLBI) is the unique space technique that can
directly interconnect the main three reference systems for geodesy and geodynamics. However, the
estimable sequence of geodetic parameters including nutation parameters within SVLBI mathematical
model has not been determined yet. In this paper, using the mathematical model of space-ground SVLBI
observations including the nutation parameters derived by WEI Erhu et al.(2008), the estimable
parameter sequence is determined. And the same study is done with space-space SVLBI Observations.
To study the standard deviation of nutation parameters estimated with space-ground SVLBI observations,
the model of variance propagation is derived, with which some numerical tests are done. Finally, the
results are present.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851R (2008) https://doi.org/10.1117/12.816223
The new generation of space datum in China should comply with the latest IERS (International Earth Rotation and
Reference System Service) convention as much as possible. This paper has deeply addressed and researched the main
improvements of the current version IERS Conventions (2003), including the changes of the Terrestrial Reference
System, the Celestial Reference System, and the transformation between them, the tide correction and so on, which
would undoubtedly benefit the realization and maintenance of our space datum. Based on PANDA (Position And
Navigation Data Analyst) software developed by GNSS Center of Wuhan University, we analyzed the effect of
improvements of the IERS Conventions (2003) on precise orbit determination and precise positioning. The results show
that the effect of improvements of models of the coordinate transformation between the celestial and the terrestrial
reference system and tide correction (including solid earth tide, ocean tide and polar tide) on precise orbit determination
are 4mm, 9mm and 5mm in terms of RMS in along, cross and radial direction of the track; and the effect of the
improvement of the tide models on positioning is basically under 0.6mm, and the RMS of the differences are 0.3mm,
0.3mm and 0.2mm in X, Y and Z.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851S (2008) https://doi.org/10.1117/12.816261
Under the financial support of several Chinese national scientific projects, PANDA (Positioning And Navigation Data
Analyst) software developed originally by Wuhan University has achieved the advanced level in the world. PANDA is
currently recognized as a main research tool in several famous institutes in the GNSS community. In this paper, the
recent development of PANDA software is introduced, including the COSMIC orbit determination in low Earth orbits,
the real-time GPS satellite orbit and clock determination and precise point positioning with ambiguity resolution. It is
concluded that PANDA is of great improvement in the past five years, and more advancement will be made in its
pragmatic aspect especially in engineering applications.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851T (2008) https://doi.org/10.1117/12.816263
In this paper, the methods of earth rotation parameter (ERP) estimation based on IGS
SINEX file of GPS solution are discussed in details. To estimate ERP, two different ways are
involved: one is the parameter transformation method, and the other is direct adjustment method
with restrictive conditions. With the IGS daily SINEX files produced by GPS tracking stations can
be used to estimate ERP. The parameter transformation method can simplify the process. The
process result indicates that the systemic error will exist in the estimated ERP by only using GPS
observations. As to the daily GPS SINEX files, why the distinct systemic error is exist in the ERP,
or whether this systemic error will affect other parameters estimation, and what its influenced
magnitude being, it needs further study in the future.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851U (2008) https://doi.org/10.1117/12.816265
Real-time high-precision GPS positioning and navigation requires that cycle-slip in the undifferenced carrier-phase
measurements can be detected instantaneously. A slip of only a few cycles can bias measurements enough to make
centimeter-level positioning or navigation difficult. Over the past decade a number of methods have been developed to
detect and repair cycle slips. The majority of methods invariably are used in the post-processing cycle-slip detection. A
method has been developed from various exiting techniques, that provides real-time cycle-slip detection (i.e., using only
current epoch's GPS carrier-phase measurements). The approach utilizes two linear combinations, the Geometry-free and
the Melbourne-Wübbena combination. The low degree polynomial fitting and running-average filter are used to detect
cycle slips. Simulation tests are conducted to the kinematic data. Results indicate that single-cycle slips can be reliably
detected instantaneously.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851W (2008) https://doi.org/10.1117/12.816275
The high precision relative positioning is one of the key conditions of multiple earth-observation satellites
differential observation. Usually, the earth-observation satellites' relative positions are got by GNSS differential
positioning. The key technology of GNSS high precision differential positioning is carrier phase AR (Ambiguity
Resolution). The distance between two earth-observation satellites is from several kilometers to several hundreds
kilometers. So it's a problem of ambiguities resolution for mid-long distance baseline. There are a lot of difficulties to
solve this kind of ambiguities such as large double difference systematic errors. In order to solve these difficulties, this
paper proposed a fast and kinematic AR method named as CPES (Coordinate Parameters Eliminated and Stepwise)
method which is based on LAMBDA method. At first, the primary theories of this method are introduced. Then, the steps
from wide-lane ambiguities resolution to L1, L2 ambiguities resolution are proposed. Lastly, several examples' results
show that this AR method has the advantages of fast speed and high reliability.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851X (2008) https://doi.org/10.1117/12.816351
In this paper, atmospheric profiles of refractivity, pressure and temperature derived from the Constellation Observing
System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation (RO) mission are compared statistically
with collocated high-vertical-resolution soundings of 38 radiosonde stations distributed over Australia and the Antarctica
during the period from July 15, 2006 to April 30, 2008.
Refractivity comparison results show that through 0~30 km, the mean absolute fractional refractivity differences are less
than 0.5%, but the refractivity standard deviations vary greatly. The smallest refractivity standard deviation of less than
1% is got at about 10km and the largest standard deviations are found below 5km. It is shown in the pressure comparison
results that the mean absolute fractional pressure differences are generally less than 0.5% between 5 km and 25 km.
Below 5 km, the mean absolute fractional pressure differences increase to be about 2%. Temperature comparison results
show that the mean absolute temperature differences are generally less than 1K and the standard deviations generally less
than 2K in the middle to upper atmosphere. In the lower troposphere, the temperature standard deviation increases to be
larger than 2.5K.
It can be concluded that the precision of GPS RO data from COSMIC are equivalent to radiosonde data in the upper
troposphere and lower stratosphere. Being able to complement radiosonde network over the oceans and polar regions,
GPS RO data are of great value for climate monitoring.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851Y (2008) https://doi.org/10.1117/12.816354
Some Orbit Determination (OD) of Low Earth Orbiters (LEOs) based on undifferenced spaceborne GPS data were
discussed firstly in this paper. Then the principle and mathematical models of two different types of reduced-dynamic
were present. After that, dual-frequency spaceborne GPS data of doy 89, 2004 from CHAMP and GRACE satellite were
computed using two types of reduced-dynamic POD and the OD results were analyzed. Our CHAMP orbiting results of
one day using two different reduced dynamic POD methods are within 7 centimeters compared with GFZ Post processed
Science Orbits (PSO) and the GRACE orbiting results are with 3 centimeters compared with JPL OD results.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851Z (2008) https://doi.org/10.1117/12.816366
The paper puts forward a new method of real-time precise GPS satellite clock offset estimation. The method adapts
the Square Root Information Filter (SRIF) that has benefits of the numerical stabilization, also eliminates the ambiguity
parameter through the difference of the epoch which will save the time of the filter consumedly. Based on the above
methods, the real-time precise clock offset estimation module is added to the PANDA software which developed by the
WuHan University for Position and Navigation Data Analysis. In addition, a examples are analyzed for one week
observation from 70 IGS global tracking stations around the world with the software, The results show: The software can
achieve the 1HZ's updating clock offset resolution for a global network of GPS tracking stations. Also, the accuracy of
0.2ns is achieved with the software compared with the IGS final products.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728520 (2008) https://doi.org/10.1117/12.816380
Periodical orbit maneuver makes a serious problem for navigation users to get correct Geostationary
(GEO) orbit information in real-time. As a result, it is very difficult to use GEO satellite for navigation
application purpose. In this presentation, the precision of the orbit determination of GEO satellite
without maneuver operation has been introduced at first. Then, two strategies of orbit determination
during satellite maneuvers are discussed in details. One method is called as maneuver force modeling;
the other is empiric force parameter estimation. The results show the residual is of the order of 40 cm
by using these strategies, and the position difference between dynamic orbit and kinematics orbit is
about 10 m.
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Geospatial Analysis and Service: Geospatial Information Service
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728521 (2008) https://doi.org/10.1117/12.807439
In order to implement some kinds of spatial data center system in the grid GIS environment, we need to introduce the
concept of grid spatial data center (GSDC). This paper presents the basic architecture of GSDC, which is the research
focus of this study. GSDC architecture is based upon and extended from the grid GIS architecture, considers and absorbs
the important characters of traditional distributed spatial data center (DSDC). The key techniques and mechanism of
DSDC, such as multi-hierarchical spatial data exchange and update, and inhomogeneous data seamless integration, are
reconstructed to become the essential services of GSDC in a new form. This paper is also a contribution to achieve an
approach to implement such system, and we discuss the various applications of GSDC in appropriate occasions. First of
all, this paper analyzes the traditional distributed multi-hierarchical spatial data center architecture in detail, and indicates
the senseful ideas and inherent bottleneck problems of it. Then, it gives some advantages come from the developing grid
GIS, which can solve the bottleneck problems of DSDC mentioned previously. After presenting the desirability of
combining these two powerful things together, this paper analyses the essential services to compose GSDC, which come
from the decomposition of the traditional multi-hierarchical DSDC. The original normal modules are transformed into
services, and provide their well defined standard function into grid. This paper also gives out the framework of
establishing multi-hierarchical virtual organization in GSDC, which is the infrastructure to satisfy the geographical
distribution of the using organizations, and the resource sharing and exchange between them. Then, it deals with
implementation aspects, and indicates that smooth upgrade from DSDC to GSDC is very important to the application of
GSDC. In conclusion, this paper concludes that grid services can give the necessary specifications and standardizations
to implement spatial data centers, and can improve the collaboration between them. The disadvantage factors in
development of GSDC are also discussed.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728522 (2008) https://doi.org/10.1117/12.808592
With the rapid increase in the amount of spatial data and the number of geospace information
system users, current network architecture of geospace information system mainly based on a single
server has two primary data transport bottlenecks: the bottleneck of network services throughout
provided by the server and the bottleneck of I/O throughout of the storage system for distributed spatial
data. In order to avoid both bottlenecks, we present a C/S mode geospace information system based on
double-cluster, namely server cluster and storage cluster, and it is called GlobeSIGht.
In GlobeSIGht, we use a Linux Virtual Server (LVS) cluster to avoid the bottleneck of network
services throughout provided by the server, and use an Object-Based Storage (OBS) cluster to avoid
the bottleneck of I/O throughout of the storage system for distributed spatial data. Spatial data is
organized as spatial storage object stored in the object-based storage device, and the metadata server
manages all the object-based storage devices and spatial storage objects to provide a spatial data shared
storage pool as the backend storage of the LVS cluster. Furthermore, by using plug-in technology,
GlobeSIGht has integrated many relevant application systems such as 2D geographic information
system, 3D geographic information system, multimedia application subsystem, massive MODIS
remote sensing images management and dispensing online system.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728523 (2008) https://doi.org/10.1117/12.811087
With the increase of geospatial data and services, how to more efficiently utilize and share the geographic information
becomes a crucial problem. To effectively integrate and enhance abundant geographic information anywhere, this paper
presents a Registry Centre for Geospatial Web Service (RCGWS) based on the Open Geospatial Consortium (OGC)
Catalogue Service for Web and the ebXML Registry Information Model (ebRIM), which provides registration and
discovery portals for geospatial metadata for dataset and services. The design ideology and architecture of RCGWS are
introduced, and the techniques of appending GIS services classification in extended ebRIM and external interfaces of
RCGWS based on OGC CWS are discussed. The implementation of RCGWS platform shows that this Registry Centre
can satisfy the requirement of geospatial dataset and services.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728524 (2008) https://doi.org/10.1117/12.815010
The visualization results of multi-dimensional and dynamically spatio-temporal information are diversified by the
varying user demands. To realize the sharing of spatio-temporal data, information and knowledge, this paper proposes a
technical framework for on-line generation and distribution of the visualization of spatio-temporal information to meet
personality need from difference level user; then, describes the key technologies that are involved; final, introduces the
implementation and application of the system by taking a marine disaster information system as an example.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728525 (2008) https://doi.org/10.1117/12.815339
Recent advances in computer architectures, computational power and memory bandwidth have created new
opportunities for visualizing large terrain data sets. Real 3D terrain simulation results from combining two main data
set- an aerial or satellite image as terrain texture and Digital Elevation Model (DEM) as terrain. Because these data are
huge amount and in different format, it is necessary to do some prior process for terrain simulation. In this paper a data
process chain of RSG DEM and remote sensing image for 3D real terrain simulation is proposed. Then a terrain
simulation system using this process method is introduced.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728526 (2008) https://doi.org/10.1117/12.815404
Geographic information portrayal standard within geographic information standards community in ISO 19117 is
consisted of symbol specification, symbol assignment, portrayal services, cartographic finishing rules and
implementation specification. The portrayal standard specifies a conceptual framework which includes classes,
attributes, associations and operations and is the base of implementation and sharing of the geographic information
portrayal. The portrayal standard associates geographic features with symbols. This paper starts up with the quantitative
methodology for specifying visual variables. Consequently, visual variable values of geographic information portrayal
are taken to be statistically analyzed on shape, size and color. Furthermore, a set of quantitative rules of visual variables
within the geographic information portrayal system are retrieved. Meanwhile, a visual variable model for portrayal is
founded in this paper. At last, the standard definition sharing of the portrayal is implemented with XML, which will
become model base of geographic information portrayal and visual analyses for earth observation data.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728527 (2008) https://doi.org/10.1117/12.815446
Aiming at various (near) real-time on-demand services, this paper puts forward the concept of focused geospatial
information services with three kinds of service patterns to aggregate and cooperate with all kinds of information
services, including the geospatial data services, geospatial processing services, transport network services and sensor
services. The challenge of focused geospatial information service is complex in user demand, rich in data dimension,
diversified in sensor type, complicated in processing and time-varying in network, which makes intricate in semantics. A
hierarchical constraint model is therefore proposed as a uniform semantics description model with four levels including
user semantic constraints, data semantic constraints, processing services functional semantic constraint and process
service quality semantic constraints. The constraints act role of establishing the connection between user semantics and
data services and processing services, and of basic of semantic reasoning in service discovery, selection, and
composition.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728528 (2008) https://doi.org/10.1117/12.815462
As remote sensing technology become ever more powerful with multi-platform and multi-sensor, it has been widely
recognized for contributing to geospatial information efforts. Because the remotely sensed image processing demands
large-scale, collaborative processing and massive storage capabilities to satisfy the increasing demands of various
applications, the effect and efficiency of the remotely sensed image processing is far from the user's expectation. The
emergence of Service Oriented Architecture (SOA) may make this challenge manageable. It encapsulate all processing
function into services and recombine them with service chain. The service composition on demand has become a hot
topic. Aiming at the success rate, quality and efficiency of processing service composition for remote sensing
application, a remote sensed image processing service composition method is proposed in this paper. It composes
services for a user requirement through two steps: 1) dynamically constructs a complete service dependency graph for
user requirement on-line; 2) AO* based heuristic searches for optimal valid path in service dependency graph. These
services within the service dependency graph are considered relevant to the specific request, instead of overall registered
services. The second step, heuristic search is a promising approach for automated planning. Starting with the initial state,
AO* uses a heuristic function to select states until the user requirement is reached. Experimental results show that this
method has a good performance even the repository has a large number of processing services.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728529 (2008) https://doi.org/10.1117/12.815567
Knowledge sharing and semantic interoperability is a significant research theme in Geographical Information Science
(GIScience) because many researchers believe that semantic heterogeneity has been identified as the main obstacle for
GIScience development. Interoperability issues can exist at three levels: syntactic, structural (also called systemic) and
semantic. The former two, however, can be achieved by implementing international or domain standards proposed by
several organizations, for example, Open Geospatial Consortium (OGC), World Wide Web Consortium (W3C) and the
International Organization for Standardization/Technical Committee for Geographic information/Geomatics (ISO/TC
211). In this paper, we are concentrating on semantic interoperability, which is the sort of topic that halt conversations
and cause people's eyes to glaze over, from two aspects: data/information/knowledge and operation/processing. We
presented a service-centered architecture for semantic interoperability of geospatial data and processes. OGC standards
like Web Feature Service (WFS) and Web Map Service (WMS) have been employed as normative interfaces for
analyzing requests, division requests and delivering small requests. Ontology has been introduced to describe distributed
resource including various data and geo-processing operations. The role of interoperability, especially from semantic
perspective, has been distinguished at the first section in this paper. As a fundamental principal, the following section
introduces semantic web, web service and other related works at this orientation. We present our service-based
architecture in detail and its simple application at part three. Conclusion and further orientations have been illustrated at
last section.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852A (2008) https://doi.org/10.1117/12.815595
This paper details a simple knowledge framework, so as to set up a scale-independent spatial database, or so called
multi-scaling GIS, for the efficient organization and management of spatial database as well as for multi-scale
representation and analysis. GIS is not only the tool for map storage and production but more importantly, GIS is the
effective means used for accessing the real word from the map. The framework emphasizes those different thematic
feature classes play different roles in the range of different scales and have different effects in the multi-scale
representation and processing. Propose multi-grade modeling representation rules based on thematic models in a variety
of professional fields, as well as knowledge framework of multiscale representation and processing based on spatial
feature classification structure and parameter table.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852B (2008) https://doi.org/10.1117/12.815604
Now most of distributed virtual geographic environments (DVGE) applications still adopt the centralized pattern, which
brings the network congestion or single point of failure to the side of center server. But the P2P technique takes away the
bottleneck in data transmission exists in traditional C/S model by virtue of its multilink self-adaptive mechanism of the
data transmission, which has a magnitude meaning for researches on the spatial data delivering in distributed virtual
geographic environment. As the spatial data has the characteristic of the massive volumes and client change the
interesting spatial area in virtual scene so frequently that the spatial application efficiency is sharply decreased, the
author brought forward a layered P2P architecture of the spatial data interoperation and flexible group mode in P2P
network. A mechanism of layered query of oriented suit (LQOS) and the self-adapted cache mode were introduced to
adjust the peer loading and the link numbers for the reliable data capture. In this way, we provide DVGE the rapid data
transmission speed among peers, the great data transmission reliability and the better user experience. A DVGE
prototype was developed and it proved the efficiency of this P2P DVGE framework. At last the futures of involved
techniques and methods are concluded.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852C (2008) https://doi.org/10.1117/12.815678
Earth observation mission planning for the near space aircrafts is a vital problem in the application of near space
aircrafts. It plays an important role in satisfying the requirement of earth observation mission most and increasing the
utilization rate of aircraft resources. Considering the mission requirement constrains and payload constrains, the paper
conceives the mixed integer programming model for earth observation missions of the near space aircrafts firstly, then
analyzes the possible conflicts among the earth observation missions, put forwards the conception of possible conflicts
of missions and divides up the whole set of missions into the sets of possible conflicts missions using the conception.
The paper gives the calculation method of mission executing conflict degree subsequently and designs a genetic and
simulated annealing algorithm based on conflicts resolution. At the end the paper proves the validity of the algorithm by
the simulation example.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852D (2008) https://doi.org/10.1117/12.815686
In order to describe accurately and comprehend quickly the perfect GIS requirements, this article will integrate the ideas
of QFD (Quality Function Deployment) and UML (Unified Modeling Language), and analyze the deficiency of
prototype development model, and will propose the idea of the Customer-Experienced Rapid Prototyping (CE-RP)
and describe in detail the process and framework of the CE-RP, from the angle of the characteristics of Modern-GIS.
The CE-RP is mainly composed of Customer Tool-Sets (CTS), Developer Tool-Sets (DTS) and Barrier-Free
Semantic Interpreter (BF-SI) and performed by two roles of customer and developer. The main purpose of the CE-RP
is to produce the unified and authorized requirements data models between customer and software developer.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852E (2008) https://doi.org/10.1117/12.815690
A common Sensor Web data service framework for Geo-Processing Workflow (GPW) is presented
as part of the NASA Sensor Web project. This framework consists of a data service node, a data
processing node, a data presentation node, a Catalogue Service node and BPEL engine. An abstract
model designer is used to design the top level GPW model, model instantiation service is used to
generate the concrete BPEL, and the BPEL execution engine is adopted. The framework is used to
generate several kinds of data: raw data from live sensors, coverage or feature data, geospatial
products, or sensor maps. A scenario for an EO-1 Sensor Web data service for fire classification is
used to test the feasibility of the proposed framework. The execution time and influences of the
service framework are evaluated. The experiments show that this framework can improve the quality
of services for sensor data retrieval and processing.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852F (2008) https://doi.org/10.1117/12.815700
Antarctica plays a key role in many scientific questions, of which those related to global climate change are probably the
most prominent examples. There are many researches on Antarctic are carried out at present, and some special institutes
sponsored by public and private communities are responsible for antarctica data management and maintenance.
Antarctic Spatial Data Infrastructure (AntSDI) [1]sponsored by SCAR's Standing Committee on Antarctic Geographic
Information (SC-AGI) is the one responsible for Antarctica spatial data maintenance and sharing by means of OGC
standard and specification. Antarctica Spatial Data Infrastructure (AntSDI) has already collected huge volumes of
geospatial data and offer an opening geospatial information service. In order to management and use Geospatial data
efficiently, and enable most of the users can access to Geospatical data and service at will, we firstly must registry data
and service into one or more registry center, then we should construct a building system which can supply users a
uniform interface to access data and service in registry center and user also can add their own data and service to system
and become part of system's capability. in this paper we present GeoAnt, a prototype interoperable AntSDI building
system. GeoAnt is a three-tier standard-based open geospatial web service system which fully automates data discovery,
access, and integration steps of the geospatial information discovery process under the interoperable service framework.
The paper discusses the system architecture, the individual components of the system and the use of the system in the
international project- Grove Mountains GIService Portal (GMGP).
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852G (2008) https://doi.org/10.1117/12.815709
This paper proposes the theory framework of spatial information sharing on digital city, and analyzes its technical
characteristics. According to the Service Oriented Architecture (SOA) framework, a geospatial information sharing
platform is put forward. The spatial data sharing model based on SOA is designed. A prototype platform of realizing
multiple-source spatial information sharing based on ArcGIS Server is developed.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852H (2008) https://doi.org/10.1117/12.815721
Presently, the spacial social and natural phenomenon is studied by both the GIS technique and statistics methods.
However, plenty of complex practical applications restrict these research methods. The data models and technologies
exploited are full of special localization. This paper firstly sums up the requirement of spacial statistical analysis. On the
base of the requirement, the universal spatial statistical models are transformed into the function tools in statistical GIS
system. A pyramidal structure of three layers is brought forward. Therefore, it is feasible to combine the techniques of
spacial dada management, searches and visualization in GIS with the methods of processing data in the statistic analysis.
It will form an integrative statistical GIS environment with the management, analysis, application and assistant
decision-making of spacial statistical information.
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Liang Tao, Deqing Chen, Lingkui Meng, Jiyuan Li, Zhanfeng Wang
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852I (2008) https://doi.org/10.1117/12.815732
MODIS (Moderate Resolution Imaging Spectroradiometer, Moderate Resolution Imaging Spectroradiometer) is carrying
on a major satellite remote sensing sensors of EOS series in the United States. MODIS remote sensing data is the new
generation of satellite remote sensing information sources; it has broad application prospects in ecological research,
environmental monitoring, global climate change and agricultural resources survey and other studies. MODIS data has
featured a large volume of data and dealing with complex. In this paper Grid Computing technology brought to the
processing of MODIS L1B Data is in order to improve the efficiency. First of all, this paper gives a brief introduction of
MODIS L1B data and its application status, also talks about gird computing. Then the structure of MODIS L1B Data
Process Based on Grid Computing (MLDPGRID) on logic is given, also explain the function of three tiers. In the
realization section, receiving of MODIS L1B data, Grid Platform, software environment and network architecture,
processing of MODIS L1B data and portal of MLDPGRID are all discussed. Finally, the paper gives the evaluation and
conclusion of the MLDPGRID, meanwhile the optimization strategy and future work are discussed.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852J (2008) https://doi.org/10.1117/12.815751
The Open Geospatial Consortium, Inc (OGC) Web Services (OWS) were initially primarily simple synchronous Web
services based on the HTTP transport protocol, which is perfectly valid in the case of simple geoprocessing of simple
data available from local sources. However, with the development of Web-based geospatial technologies, especially the
development of the Sensor Web, a number of limitations have been identified with using HTTP-GET/POST binding in
OGC OWS, which cannot meet the needs of asynchronous communication and operations between clients and services
or in OGC services chain. Asynchronicity in Web services could be achieved in different ways. Callback pattern is
widely supported in client asynchronous invocation. Message-based middleware often can be used together with the
asynchronous invocation alternatives. Web Notification Service (WNS) is designed to provide asynchronous messagebased
communication in OGC. This paper describes a mechanism for an asynchronous, message-based, event-driven,
dynamic geospatial Web system based on OGC Web services. The addition of asynchronicity in OGC Web services has
two components. One is the augmentation of OGC Web services with asynchronous message-based notification. The
other is asynchronous OGC Web service orchestration based on BPEL.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852K (2008) https://doi.org/10.1117/12.815756
Map decoration is an important component of the topographic map production. To study and tell of the decoration
rules in national basic scale topographic maps and multiple-topographic maps, to enhance efficiency, and reduce the
workload of topographic map production, the paper plans to study and use of object-oriented technology, to complete the
map decoration automatically. The module has been applied to the photographic map and topographic map product
development test in the project of 1:50 000 Topographic Mapping of Blank Area in the Western Region, China. The
module practice has proved that the realization of Automatic Decoration Technique greatly improves the work
efficiency.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852L (2008) https://doi.org/10.1117/12.815762
The Open Geospatial Consortium (OGC) standard-compliant services define a set of standard interfaces for geospatial
Web services to achieve the interoperability in an open distributed computing environment. Grid technology is a
distributed computing infrastructure to allow distributed resources sharing and coordinated problem solving. Based on
the OGC standards for geospatial services and grid technology, we propose the geospatial grid portal to integrate and
interoperate grid-enabled geospatial services. The implementation of the geospatial grid portal is based on a three-tier
architecture which consists of grid-enabled geospatial services tier, grid service portal tier and application tier. The OGC
standard-compliant services are deployed in a grid environment, the so-called grid-enabled geospatial services. Grid
service portals for each type of geospatial services, including WFS, WMS, WCS and CSW, provide a single point of
Web entry to discover and access different types of geospatial information. A resource optimization mechanism is
incorporated into these service portals to optimize the selection of grid nodes. At the top tier, i.e. the application tier, the
client interacts with a semantic middleware for the grid CSW portal, thus allows the semantics-enabled search. The
proposed approach can not only optimize the grid resource selection among multiple grid nodes, but also incorporate the
power of Semantic Web technology into geospatial grid portal to allow the precise discovery of geospatial data.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852M (2008) https://doi.org/10.1117/12.815770
How to use web services quickly and efficiently is quite important in geospatial applications. A possible solution of
sharing and integrating geospatial resources in opening web environment is to chain distributed and diversified geodata
and geoprocessing by using web services. This paper presents an approach for chaining geoprocessing by employing
Web Processing Service (WPS) and Business Process Execution Language for Web Services (BPEL4WS) under the
service-oriented architecture (SOA) and Open Geospatial Consortium (OGC) standard. Workflow control model and
SQL Server based register center are used in a prototype system for chaining geoprocessing web services which have
been performed functionality decomposition and packed by using extended WPS.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852N (2008) https://doi.org/10.1117/12.815774
Spatial service chain composed by multiple spatial services, which distributed on the internet, can realize specific,
complicated spatial information processing task. This chain may be involved in bad stability, low usability and low
efficiency because of service stateless and variability of service operation environment. In this paper, we abstract the
spatial information service to form the Spatial Service Agent (SSA), and attach the spatial information data and
processing service to become operation capability of SSA. After introduce contract and policy which are used to restrict
and instruct the behavior of the SSA, multi-SSA based spatial information services flow expressed by half-ordered
contract set which formed by SSA's negotiation. Through assign specific contract operation rule to each contract and
indicate the prerequisite of cooperation, time consuming, and accomplishment state and so on, we can accurately get the
service execution state of each step for spatial information services flow monitoring and exception handling.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852O (2008) https://doi.org/10.1117/12.815861
Spatial information dissemination is a necessary step to make use of spatial information for which is a bridge between
the acquirement and the application of spatial information. However, conventional methods of spatial information
dissemination cannot cater to users in that not only users' personalized requirements cannot be satisfied, but initiative
dissemination service cannot be provided. In this paper, the idea of intelligent spatial information dissemination (ISD) is
proposed. Combining the ideas of personalized information retrieval, information filtering and recommender systems,
the ISD system employs user profiles and query conditions to provide two implement ways of spatial information
disseminations, namely "pull" and "push". Then, the three layers architecture of intelligent spatial information
dissemination system based on user profile model is given, and the procedure of data in the ISD system is introduced.
Also, the user profile is presented including user profile model and user profile management. Finally, the prototype
system of intelligent spatial information dissemination is presented.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852P (2008) https://doi.org/10.1117/12.815913
Geospatial metadata, data, and services have been widely collected, developed and deployed in recent years. This
flourishing of geospatial resources also added to the problem of geospatial heterogeneity. Interoperability research and
implementation are needed for advancement in potential solutions to integrate and interoperate these widely dispersed
geospatial resources. We design and implement Wuhan Geospatial Information Sharing Platform based on existing
WMS. This platform consists of three components: Web Client, Metadata Catalog, and Data Services. Data Services
provide WMS. All spatial information from different sources has been published as WMS. These WMS have been
described by geospatial metadata compatible with geospatial metadata standard. These geospatial metadata has been
stored in Metadata Catalog. Web Client provides functionalities to access and process WMS described by geospatial
metadata in Metadata Catalog.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852Q (2008) https://doi.org/10.1117/12.815927
With the rapid development and application of Internet technology, Geographic Information System has stepped into a
new age with its main form as Geographic Information Services. Although there are so many Geographic Information
Services available on the Internet now, they are still in very low rate of application. To facilitate the discovery, some
proposals for Geographic Information Services infrastructures focus on centralized service registry (UDDI, Universal
Description, Discovery and Integration ) for cataloguing their geospatial functions and characteristics. Centralized
systems introduce single points of failure, hotspots in the network and expose vulnerability to malicious attacks. In order
to solve the problem above, this paper proposes A Complex Network Peer-to-Peer Approach for Geospatial Web
Services Discovery. Based on complex network theory, a Peer-to-Peer network has been established, and it takes the
charge of each peer's communication and management, and an EBRIM registry centre has been inserted into each peer
for the registry and query of Geographic Information Services.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852R (2008) https://doi.org/10.1117/12.815944
Geo-ontology, a kind of domain ontology, is used to make the knowledge, information and data of concerned
geographical science in the abstract to form a series of single object or entity with common cognition. These single
object or entity can compose a specific system in some certain way and can be disposed on conception and given specific
definition at the same time. Ultimately, these above-mentioned worked results can be expressed in some manners of
formalization. The main aim of constructing geo-ontology is to get the knowledge of the domain of geography, and
provide the commonly approbatory vocabularies in the domain, as well as give the definite definition about these
geographical vocabularies and mutual relations between them in the mode of formalization at different hiberarchy.
Consequently, the modeling tool of conception model of describing geographic Information System at the hiberarchy of
semantic meaning and knowledge can be provided to solve the semantic conception of information exchange in
geographical space and make them possess the comparatively possible characters of accuracy, maturity and universality,
etc. In fact, some experiments have been made to validate geo-ontology. During the course of studying, Geo-ontology
oriented to flood can be described and constructed by making the method based on geo-spatial affairs to serve the
governmental departments at all levels to deal with flood. Thereinto, intelligent retrieve and service based on geoontology
of disaster are main functions known from the traditional manner by using keywords. For instance, the function
of dealing with disaster information based on geo-ontology can be provided when a supposed flood happened in a certain
city. The correlative officers can input some words, such as "city name, flood", which have been realized semantic label,
to get the information they needed when they browse different websites. The information, including basic geographical
information and flood distributing and change about flood with different scales and ranges in the city, can be distilled
intellectively and on its own initiative from the geo-ontology database. Besides, correlative statistical information can
also be provided to the governmental departments at all levels to help them to carry out timely measures of fighting back
disaster and rescue. Compared with the past manners, the efficiency of dealing with flood information has been improved
to some extent than ever because plenty of information irrespective and interferential to flood in different websites can
be sieved in advance based on the retrieve method oriented to Geo-ontology. In a word, it will take the pursuers long
time to study geo-ontology due to actual limited resource. But then, geo-ontology will be sure to further perfect
correspondingly especially in the field of Geographic Information System owing to its more and more factual
applications.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852S (2008) https://doi.org/10.1117/12.815950
Large-size of spatial data and limited bandwidth of network make it restricted to transmit spatial data in WebGIS. This
paper employs IPv6 (Internet Protocol version 6), the successor of IPv4 running now, to transmit spatial data efficiently.
As the core of NGN (Next Generation Network), IPv6 brings us many advantages to resolve performance problems in
current IPv4 network applications. Multicast, which is mandatory in IPv6 routers, can make one server serve many
clients simultaneously efficiently, thus to improve capacity of network applications. The new type of anycast address in
IPv6 will make network client applications possible to find the nearest server. This makes data transmission between
client and server fastest. The paper introduces how to apply IPv6 multicast and anycast in WebGIS to transmit data
efficiently.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852T (2008) https://doi.org/10.1117/12.815951
This article discusses the synchronous update mechanism and implementary policy for real-time network of the land
survey database based on multi-level distributed heterogeneous structure of "state-province-city-county", and to design
and realize the incremental update network system in application to web service model and incremental updating mode
of the land survey data. The main procedure of real-time network synchronous update policy in this article includes: data
standardization transition, web services network asynchronous transmission, data processing and checking, spatial entity
data increment updating. This paper also experiments, tests and validates the model method and updating policy as
Laoren village land block data update for an example.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852U (2008) https://doi.org/10.1117/12.815974
Along with the development of earth observation technology, large amounts of geospatial information are accessible.
There are also a lot of geospatial data and services which are shared on the Internet. However they vary in formats and
are stored at various organizations leading to problems of data discovery, data interoperability and usability. The Open
Geospatial Consortium (OGC) has developed standard service called catalogue in order to overcome this problem. The
goal of a geospatial catalogue is to support a wide range of users in discovering relevant geographic data and services
from heterogeneous and distributed repositories. But in most of geospatial catalogue services, the search functionality is
limited to the direct match of keywords from metadata, the OGC catalogues may not return useful results as the used
keywords often do not match with the meta-information stored in the catalogues. In this paper, we propose a geospatial
semantic catalogue services that aims at overcoming this limitation.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852V (2008) https://doi.org/10.1117/12.816000
With the development of space technology, a growing number of the earth observing satellites have been used to acquire
data of the earth for various purposes, and the capability of data acquirement from spaceborne sensor makes a rapid
enhancement. Under this circumstance, it is very important to measure the capability of data acquirement quantitatively.
This paper concerns on the measurement of EOS data acquirement. This measurement can identify access area of a
specific EOS. Considering the characteristics of payload, the location of instantaneous imaging area could be calculated
based on sensor geometric model. To calculate the location of a given sensor instantaneous imaging area, the
measurement is divided into 3 stages: firstly, a satellite motion prediction is undertaken for the purpose of getting
position and velocity of the satellite; furthermore, considering the performance of skew maneuver, the imaging area of
the satellite's sensor could be calculated based on strict geometric model, finally, the imaging area of sensor is
calculated. Experimental results show that the proposed measurement is accurate.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852W (2008) https://doi.org/10.1117/12.816008
GML can only achieve geospatial interoperation at syntactic level. However, it is necessary to resolve difference of
spatial cognition in the first place in most occasions, so ontology was introduced to describe geospatial information and
services. But it is obviously difficult and improper to let users to find, match and compose services, especially in some
occasions there are complicated business logics. Currently, with the gradual introduction of Semantic Web technology
(e.g., OWL, SWRL), the focus of the interoperation of geospatial information has shifted from syntactic level to
Semantic and even automatic, intelligent level. In this way, Geospatial Semantic Web (GSM) can be put forward as an
augmentation to the Semantic Web that additionally includes geospatial abstractions as well as related reasoning,
representation and query mechanisms. To advance the implementation of GSM, we first attempt to construct the
mechanism of modeling and formal representation of geospatial knowledge, which are also two mostly foundational
phases in knowledge engineering (KE). Our attitude in this paper is quite pragmatical: we argue that geospatial context is
a formal model of the discriminate environment characters of geospatial knowledge, and the derivation, understanding
and using of geospatial knowledge are located in geospatial context. Therefore, first, we put forward a primitive
hierarchy of geospatial knowledge referencing first order logic, formal ontologies, rules and GML. Second, a metamodel
of geospatial context is proposed and we use the modeling methods and representation languages of formal
ontologies to process geospatial context. Thirdly, we extend Web Process Service (WPS) to be compatible with local
DLL for geoprocessing and possess inference capability based on OWL.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852X (2008) https://doi.org/10.1117/12.816078
This paper firstly introduces the spatial data grid and the CDN (Content Delivery Network) technology. And then it
depicts the significance of integrating grid with CDN. On this basis, this paper proposes a method of constructing the
spatial data grid system by using CDN to support the massive spatial data online service. Finally, the simulation results
by OPNET show that the programme do can improve the system performance, and reduce response time in a greater
extent.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852Y (2008) https://doi.org/10.1117/12.816104
This paper presents a P2P approach to the delivery of earth-observation data. Conventional P2P networks can speed up
data delivery but suffers the problem of stability when handling spatial data. We design a hybrid CDN-P2P strategy to
speed up data delivery while maintaining stability. We tested our strategy in a simulation environment in which
performance of data transfer is observed against different bandwidths. The results show that the hybrid approach
performs much better than the conventional only-server and only-peers model. Dynamic allocation of peers and predownload
are also presented as strategies to address the special needs of spatial data delivery.
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Geospatial Analysis and Service: Geospatial Analysis
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72852Z (2008) https://doi.org/10.1117/12.812375
This paper proposes a multi-activities scheduling algorithm based extended space-time prism under time geography
framework. This algorithm aims to schedule multi-activities from different kinds of activity, which can be used as kernel
function of an innovative location based service-multi-activities scheduling service. The extended space-time prism is
derived of space-time prism concepts of time geography. For each available activity opportunity in this extended spacetime
prism, two new shortest path trees are computed to measure the travel time between activities from different kinds
of activity, one new space-time tree arrive at this available activity opportunity, and the another one departs from this
available activity opportunity. A prototype 3D space-time environment is implemented to support the concept of
extended space-time prism, and provide function of this proposed algorithm. An example of multi-activities scheduling
scenario is shown to demonstrate the usefulness of this proposed algorithm for this location based service. Finally,
several future works are also introduced in this paper.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728530 (2008) https://doi.org/10.1117/12.813354
Exploratory data analysis is increasingly more necessary as larger spatial data is managed in electro-magnetic media.
Spatial clustering is one of the very important spatial data mining techniques. So far, a lot of spatial clustering algorithms
have been proposed. In this paper we propose a robust spatial clustering algorithm named SCABDT (Spatial Clustering
Algorithm Based on Delaunay Triangulation). SCABDT demonstrates important advantages over the previous works.
First, it discovers even arbitrary shape of cluster distribution. Second, in order to execute SCABDT, we do not need to
know any priori nature of distribution. Third, like DBSCAN, Experiments show that SCABDT does not require so much
CPU processing time. Finally it handles efficiently outliers.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728531 (2008) https://doi.org/10.1117/12.814959
This paper first synthetically analyzes three classical algorithms of constructing Delaunay Triangulation Irregular Net (DTIN),
then uses improved convex hull algorithm to construct non-constrained D-TIN. The non-constrained D-TIN may
cause some Delaunay triangles which span contour lines, so these Delaunay triangles must be dealt with. Then the local
adjusting algorithm based on diagonals changing of the impacted region is used to embed contour lines into D-TIN as
constrained segments and ultimately construct constrained D-TIN (CD-TIN). After constructing CD-TIN which supports
the spatial data mining, it is easy to compute normal vectors of Delaunay triangles in the CD-TIN, and then get their
gradient values. By means of the relationship of gradient values and terrain features, flats and mountain regions can be
distinguished from topographic map based on contour lines. Even the terrain features such as mountain peak can be also
recognized in the recognized mountain regions primarily by Flat-Triangle whose three vertexes have the same digital
elevation.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728532 (2008) https://doi.org/10.1117/12.814999
We describe a method, based on spatial relations, to generate algorithms for watermarking 2D vector map. The method
consists of: defining and computing the metric meatures of topological relations between map objects; extracting cover
data from metric meatures; deviding the cover data into different subsets; adjusting the spatial relations between map
objects within the precision tolerance of the map to make the cover data distribution of one subset shows one of the two
expected patterns to suggest the embedding of bit 1 or 0. The method is blind and experiments show that it is also
robust.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728533 (2008) https://doi.org/10.1117/12.815943
Oracle9i database is a very big and complicated run system whose run efficiency is of great importance to E-government
system capability. There are large numbers of basic geo-spatial data and attributed data in the E-government system,
such as vector data, grid data, image data, DEM data and statistical data, etc. The large oracle9i database and B/S
structure with three layers are adopted during the course of system application. It is very important to optimize the
database capability due to using oracle9i database to manage the great capacity of data in the system. This paper
proposed some optimizational principles and methods of oracle9i database capability in detail in the aspects of database
structure, SQL Sentence and memory assignation. At last, some examples are given to validate the above-mentioned
principles and methods. In fact, the optimization of oracle9i database is a long and continually dynamic process with the
development of time due to great capacity of different data. It involves a lot of work and need often track diversified
statistical targets and analyze the cause of capability change. Different aspects of factors must be synthetically
considered in order to enhance the run efficiency of the system. During the course of system construction, DBA must
analyze carefully different requirements and configure rationally diversified parameters about database structure, SQL
sentence and memory assignation so that the run system based on oracle9i database can be at its best and improve the
decision-making efficiency of e-government.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728534 (2008) https://doi.org/10.1117/12.815431
In this paper, we specially emphasize on BP Artificial Neural Networks (BP ANNs) in spatial interpolation of DEM, and
simulate one spatial interpolation case in the area where there are several discrete known levelling points using input
vector: (X, Y, XY, X2, Y2) or (X, Y, XY, X2, Y2, XY2, X2Y, X3, Y3)instead of (X,Y), where the X is the horizontal
coordinate and the Y is the vertical coordinate. The results show that the new input vectors are usually applicable and
better than the classic one. In the numerical experiment of this paper, the maximum error is 2.032m when the input
vector, (X, Y, XY, X2, Y2, XY2, X2Y, X3, Y3) is used, while it is 2.807m when (X, Y) is applied. Further this BP ANNs
method is better than the classic polynomial method in which the maximum error of polynomial method is 6.728m.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728535 (2008) https://doi.org/10.1117/12.815569
The development and application of spatial database ultimately create the demand for spatial information security, and
access control is our primary concern. The access control requirements for spatial database contain two special aspects:
1) fine-grained; 2) meeting certain conditions, including spatial and non-spatial. In this paper, we propose a view-based
mechanism to implement access control functionalities. We firstly present the authorization model for spatial data. Then
we thoroughly discuss the definition of various views and their authorization, and explain the advantages and
disadvantages of this model. We also provide a reference framework for the view-based access control system, and the
components and control flow are explained. Finally, we use a case study to demonstrate the feasibility and effectiveness
of view-based authorization model for securing spatial database access.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728536 (2008) https://doi.org/10.1117/12.815596
The path planning method is one of the main research directions in current UAV(unmanned aerial vehicle) technologies.
In this paper we perform analyses on the adversarial environment which may be broken through during the UAV mission
for ground observation, and carry out the grade classification according to the threat level. On the basis of genetic
algorithm, the encoding method of dimension reduction and direct quantization is used to combine the threat value of
each leg with the flight distance, so as to construct the fitness evaluation function based on the threat amount and design
the algorithm. This method is proven to be able to converge effectively and quickly via the simulation experiments,
which meet the threat restriction and applicability of UAV in route planning.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728537 (2008) https://doi.org/10.1117/12.815598
Geospatial data are the backbone of spatial analysis, but only current and accurate data can provide the appropriate
framework for successful use of GIS technology. The revision of geospatial data is still one of the major open challenges
for the successful implementation of Geographic Information Systems (GIS). There is a great need for cost-efficient data
revision and quality control methods in order to fulfill the need of most faithful image of the geographic space reality.
Maintaining one database per scale without directly maintaining interrelationship between multiple scale databases leads
to no update propagation and inter-database consistency is lost. A Multi-resolution/representation-database (MRDB)
approach is proposed in this paper to solve this problem. MRDB is a spatial database technology that designed to store
one real world phenomena at several specially designed levels of precision, accuracy and resolution. Propagating updates
between these different scales datasets in MRDB with the advantage that data consistency and integrity can be
significantly improved and enable an automatic incremental update process for the data sets.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728538 (2008) https://doi.org/10.1117/12.815612
This paper gave a brief of basic principles of neural network, analyzed the BP algorithm applications in
the neural network, and introduced the BP algorithm machinery. Based on BP algorithm, takes Karst
rocky desertification in Du'an country of Guangxi province as example, proposed the neural network
Karst rocky desertification early warning model structure which can realize the rocky desertification
warning analysis, calculate the rocky desertification fatalness indexes, and expresses the rocky
desertification early warning levels in the thematic map. The result verifies the credibility and the
possibility of the early warning analysis model with BP algorithm.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728539 (2008) https://doi.org/10.1117/12.815617
Computation Grids enable the coordinated sharing of large-scale distributed heterogeneous computing resources that can
be used to solve computationally intensive problems in science, engineering, and commerce. Grid spatial applications are
made possible by high-speed networks and a new generation of Grid middleware that resides between networks and
traditional GIS applications. The integration of the multi-sources and heterogeneous spatial information and the
management of the distributed spatial resources and the sharing and cooperative of the spatial data and Grid services are
the key problems to resolve in the development of the Grid GIS. The performance of the spatial index mechanism is the
key technology of the Grid GIS and spatial database affects the holistic performance of the GIS in Grid Environments. In
order to improve the efficiency of parallel processing of a spatial mass data under the distributed parallel computing grid
environment, this paper presents a new grid slot hash parallel spatial index GSHR-Tree structure established in the
parallel spatial indexing mechanism. Based on the hash table and dynamic spatial slot, this paper has improved the
structure of the classical parallel R tree index. The GSHR-Tree index makes full use of the good qualities of R-Tree and
hash data structure. This paper has constructed a new parallel spatial index that can meet the needs of parallel grid
computing about the magnanimous spatial data in the distributed network. This arithmetic splits space in to multi-slots
by multiplying and reverting and maps these slots to sites in distributed and parallel system. Each sites constructs the
spatial objects in its spatial slot into an R tree. On the basis of this tree structure, the index data was distributed among
multiple nodes in the grid networks by using large node R-tree method. The unbalance during process can be quickly
adjusted by means of a dynamical adjusting algorithm. This tree structure has considered the distributed operation,
reduplication operation transfer operation of spatial index in the grid environment. The design of GSHR-Tree has
ensured the performance of the load balance in the parallel computation. This tree structure is fit for the parallel process
of the spatial information in the distributed network environments. Instead of spatial object's recursive comparison
where original R tree has been used, the algorithm builds the spatial index by applying binary code operation in which
computer runs more efficiently, and extended dynamic hash code for bit comparison. In GSHR-Tree, a new server is
assigned to the network whenever a split of a full node is required. We describe a more flexible allocation protocol
which copes with a temporary shortage of storage resources. It uses a distributed balanced binary spatial tree that scales
with insertions to potentially any number of storage servers through splits of the overloaded ones. The application
manipulates the GSHR-Tree structure from a node in the grid environment. The node addresses the tree through its
image that the splits can make outdated. This may generate addressing errors, solved by the forwarding among the
servers. In this paper, a spatial index data distribution algorithm that limits the number of servers has been proposed. We
improve the storage utilization at the cost of additional messages. The structure of GSHR-Tree is believed that the
scheme of this grid spatial index should fit the needs of new applications using endlessly larger sets of spatial data. Our
proposal constitutes a flexible storage allocation method for a distributed spatial index. The insertion policy can be tuned
dynamically to cope with periods of storage shortage. In such cases storage balancing should be favored for better space
utilization, at the price of extra message exchanges between servers. This structure makes a compromise in the updating
of the duplicated index and the transformation of the spatial index data. Meeting the needs of the grid computing, GSHRTree
has a flexible structure in order to satisfy new needs in the future. The GSHR-Tree provides the R-tree capabilities
for large spatial datasets stored over interconnected servers. The analysis, including the experiments, confirmed the
efficiency of our design choices. The scheme should fit the needs of new applications of spatial data, using endlessly
larger datasets. Using the system response time of the parallel processing of spatial scope query algorithm as the
performance evaluation factor, According to the result of the simulated the experiments, GSHR-Tree is performed to
prove the reasonable design and the high performance of the indexing structure that the paper presented.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853A (2008) https://doi.org/10.1117/12.815628
Parallelism of spatial index could significantly improve the performance of spatial queries, special for massive spatial
databases, so the research of parallel spatial index takes a important role in high performance spatial databases. Existing
parallel spatial index methods have two main shortcoming: one is accessing hotspot and bottleneck of index items
located in main server, the other is high costs and complicated operations for maintaining index consistency. Aim at
these, a distributed parallel spatial index structure called DPR-tree is proposed. It splits whole index region into partition
sub-regions by using Hilbert space-filling curve grid and organizes index sub-regions according to locality of spatial
objects, then maps index sub-regions to partition sub-regions and assigns these index sub-regions to different computer
nodes by a appointed map function, Each computer node manages a multi-level distributed sub-Rtree which is built from
a index sub-region. Our experimental results indicate that the proposed parallel spatial index can achieve speedup well
and offer significant potential for reducing query response time.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853B (2008) https://doi.org/10.1117/12.815659
In some fields of space science such as GPS positioning system and remote sensing image processing, the function
model is physically unambiguous and nonstatistical, and many of them are nonlinear. Further more, data collected in
many fields of space science include systematic errors inevitably, parametric models sometimes are in difficulty to deal
with them, and semiparametric model is an approach to solve this kind of problems. This paper focuses on a kind of
semiparametric model with a nonlinear parametric component, in which the nonlinear parametric component is used to
express the physical relationship and the nonparametric component is used to describe systematic errors and other model
errors. The resolving of nonlinear semiparametric model is a new problem now. The most general method is
linearization, but linearization is likely to introduce model error in to the model. In this paper, the direct estimating
formulas of kernel method under the least-squares principle of this kind of model are deduced, including the calculating
formulae of the estimation of parametric and nonparametric components, and gives the direct nonlinear estimating
formulas of kernel estimator considering the second order items. Based on direct estimating formulas and simulated GPS
observation data, this paper proved that: as to some least-squares kernel estimating of nonlinear semiparametric models,
we can use direct estimating methods considering the second order items.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853C (2008) https://doi.org/10.1117/12.815695
In data mining one of the classical algorithms is Apriori which has been developed for association rule mining in large
transaction database. And it cannot been directly used in spatial association rules mining. The main difference between data
mining in relational DB and in spatial DB is that attributes of the neighbors of some object of interest may have an influence on
the object and therefore have to be considered as well. The explicit location and extension of spatial objects define implicit
relations of spatial neighborhood (such as topological, distance and direction relations) which are used by spatial data mining
algorithms. Therefore, new techniques are required for effective and efficient spatial data mining.
Geostatistics are statistical methods used to describe spatial relationships among sample data and to apply this
analysis to the prediction of spatial and temporal phenomena. They are used to explain spatial patterns and to interpolate
values at unsampled locations.
This paper put forward an improved algorithm of Apriori about mining association rules with geostatistics. First the
spatial autocorrelation of the attributes with location were estimated with the geostatistics methods such as kriging and
Spatial Autoregressive Model (SAR). Then a spatial autocorrelation model of the attributes were built. Later an
improved algorithm of apriori combined with the spatial autocorrelation model were offered to mine the spatial
association rules. Last an experiment of the new algorithm were carried out on the hayfever incidence and climate factors
in UK. The result shows that the output rules is matched with the references.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853D (2008) https://doi.org/10.1117/12.815699
Spatial clustering is one of those major methods applying to spatial data mining and knowledge discovery. The purpose
of this paper is to set forth Spatial Clustering Method Based on Multidimensional Cloud Model, which can be widely
applied to the research on classification and hierarchy in realm of spatial data mining and knowledge discovery. This
paper summarizes all kinds of cloud model and analyzes the optimalizing form of spatial data−three-dimensional
cloud model. The limitation which sets the weighing value subjectively in traditional way and propagation of error can
be avoided. The implementation procedure of this method is advanced, and the feasibility of this method is proven
through experiments effectively.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853E (2008) https://doi.org/10.1117/12.815749
In this paper, a guide star selection algorithm based on angular grids is presented, which can be used to minimize the size
of initial star catalogue and guarantee the distribution of the guide stars as uniform as possible . This algorithm is
preformed by dividing the FOV into many equal angular grids and mapping the grids onto the celestial sphere. The guide
stars are selected in the extent of grids and their brightness and position in the celestial sphere are considered as well.
The experiment with real star catalogue data demonstrates the validity of the proposed algorithm.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853F (2008) https://doi.org/10.1117/12.815752
Prediction of farmland change is a basic work of farmland protection, and also provides basic data for land use
planning. According to non-linear characteristic of farmland change, a new method which employs Cellular Automata
and Logistic Regression Model to simulate and predict farmland change is discussed in this paper, and structure of
Logistic-CA Model and parameters calculation are analyzed. And then, taking Xiantao City as a case, Logistic-CA
Model mentioned in this paper was applied to simulate and predict farmland change in this area. Results show:
(1)Logistic-CA Model can get rid of disadvantages of traditional mathematic models and get higher accuracy in farmland
change prediction; (2)Logistic-CA Model can not only predict quantitative change of farmland, but also simulate pattern
evolvement of farmland; (3)Logistic-CA Model can simulate and predict farmland change in various scenarios, and give
evidences for establishing policies to protect farmland.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853G (2008) https://doi.org/10.1117/12.815920
Traditional modeling methods on spatial objects are not eligible to deal well with the fuzzy features that acquired from
image, some research need to be carried out on the fuzzy spatial objects modeling. With the deep investigation on the
spatial objects model of GIS and the representation of natural geographical feature, fuzzy spatial objects have been
proposed by researchers. Referring to the characteristics of the representation of fuzzy spatial objects, a generation
method of fuzzy spatial objects based on fuzzy Neural Networks is going to be demonstrated by the authors in this paper.
By combining the fuzzy technique and neural networks, utilizing the learning ability to enhance the fuzzy membership
function and fuzzy rules, the system will be self-Adaptive. By comparing with the traditional fuzzy objects generation,
the method in this paper improves the accuracy of results according to the experiments in this paper.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853H (2008) https://doi.org/10.1117/12.815990
In order to visualize spatio-temporal data and temporal geographic information in a dynamic way, a spatio-temporal GIS that are
capable of demonstrating how geographic phenomena evolving should be established, for the fundamental theory of spatio-temporal
GIS, it is urgent to analyze the impetus and mechanism that how spatio-temporal process happened. The authors proposed a set of
universal change patterns for modelling of spatio-temporal processes, which builds a fundamental basis for the representation of
dynamic phenomena. Change detection algorithms were also developed and pattern association methods were implemented for the
modelling of changing geographical world.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853I (2008) https://doi.org/10.1117/12.816114
Spatio-Temporal Autoregressive Integrated Moving Average (STAIRMA) model family is a very useful tool in
modeling space-time series data. It assumes that space-time series data is correlated linearly in space and time. However,
in reality most space-time series contains nonlinear space-time autocorrelation structure, which can't be modeled by
STARIMA. Artificial neural networks (ANN) have shown great flexibility in modeling and forecasting nonlinear
dynamic process. In the paper, we developed an architecture approach to model space-time series data using artificial
neural network (ANN). The model is tested with forest fire prediction in Canada. The experimental result demonstrates
that STANN achieves much better prediction accuracy than STARIMA model.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853J (2008) https://doi.org/10.1117/12.814360
With the development of digital city, 3D City Models (3DCM) are created and applied in more and more fields in recent
years. However, the geometric structure of 3DCM is complicated and the volume of texture data is huge, which is beyond the
real time rendering abilities of current work stations. On the other hand, various applications have different requirements on
the accuracy of geometric data and visual effects. Hence, the levels of detail (LoD) of 3DCM is of vital importance for a
3DCM. Because buildings are the main component of a city, research on the LOD of 3DCM focused on the LOD
representation of urban buildings by generalization. Different from 2D map generalization, where maps have standardized
official scale series, which lead to determinate generalization space and specific levels of detail. However, 3D building group
models have no uniform standard to specify the levels of detail, which leads to difficulties in defining specific generalization
space and geometric and semantic layer. Aiming at the automatic generalization of 3D urban building group models, this
paper proposes a hierarchical partition approach of 3D urban building-group models to obtain different levels of
generalization space.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853K (2008) https://doi.org/10.1117/12.814924
Augmented Reality (AR) is a growing research area in virtual reality and generates a composite view for the user. It is
combination of the real scene viewed by the user and a virtual scene generated by the computer that augments the scene
with additional information. About 80 percent information in the real world is related with spatial location. The
combination of Geographical information system (GIS) and AR technologies would promote the development of outdoor
AR systems, and also would explore a new research direction for GIS. The key technologies of outdoor augmented
reality GIS, including basic tracking methods, display devices, typical applications and registration processes, are
discussed. In indoor augmented reality's closed environments the tracking of position and head orientation as well as the
presentation of information is much more unproblematic than the same task in an outdoor environment. The main
application task of outdoor augmented reality GIS is the presentation of information to a user while moving through an
unknown region. The system helps to detect automatically objects in sight of a person who need its information. It
compares the conventional solutions of 3D registration with, while it discusses their algorithm procedure to basic
parameters to give out their advantages and disadvantages at different condition. While affine transformation approach
uses the idea of computer graphics and vision technology for reference. Its accuracy is mainly based on the precision and
speed of scene feature point extracted from natural or artificial feature.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853L (2008) https://doi.org/10.1117/12.815176
This paper presents a method on how to organize 3D remote sensing images and how to publish these images quickly.
We use two levels of grid-based spatial index to organize massive images. First, we divide a huge digital city image into
many map sheets (big images). All of map sheets construct a matrix structure. We use row number and column number
to encode every map sheet. Second, by using resample and bilinear interpolation method, we build pyramid for every
map sheet to form multi-scale hierarchical structure. At the same time building pyramid, we adopt JPEG compression
technology to produce JPEG image format files. The number of output image files equals to the number of pyramid
layers. Third, divide every pyramid layer image into many small image tiles. The size of each tile image is 256*256
pixels. All of small tiles of each pyramid layer image also construct a matrix structure. We also use row number and
column number to encode every small image tile. We create a file directory for each map sheet in order to store all of
small image tiles. we neatly combine the spatial index structure with the file name of each tile, which make server be
able to return tile to browser side very quickly without any query operation. With the proposed method, we can provide
users with a fast and efficiently tool to publish their own spatial information without involving any programming work.
The system performance is very good and the response time is almost identical for different size images.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853M (2008) https://doi.org/10.1117/12.815594
The traditional two-dimensional and three-dimensional GIS can no longer
satisfy people's requirement to understand the real world. So, the new three-dimensional
digital terrestrial GIS based on digital earth has been developed, which can give users more
intuitive information. Further more, in a more realistic manner, the new three-dimensional
digital terrestrial GIS can treatment Multi-source space information of models, It can indicate
the variety, the quantity and the quality of spatial objects, the spatial location of these objects
and the spatial and temporal distribution of the phenomena. This paper is based on GeoGlobe
digital terrestrial platform. It requires some fast scheduling data method. Because the data
organization and management methods in the traditional 3D GIS are no longer suitable
according to the requirement of data scheduling in the digital earth theory, it is necessary to
put forward a more reasonable and conformable data structure to implement clipping data
scheduling. Advances one method, which takes geometric object model systems to deal with
multi-source space model data and takes reasonable data organization, supports quick data
scheduling for digital earth and constructs one 3D model database which is fit for digital
earth's use.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853N (2008) https://doi.org/10.1117/12.815702
Airborne LIDAR has a large number of data, which contains a large amount of
redundant information. The information have little help or no help on the follow-up analysis,
but the redundant data will take up a lot of storage space and computing time, which will take
the inconvenience to the LIDAR data transmission and application. Therefore, in this paper
we provide a kind of block algorithm on the basis of tile pyramid, which could rapidly
process LIDAR data and reduce the data volume in the terrain mapping. Then based on the
block algorithm, we put forward the simplification of LIDAR data, the experiment results
show that the algorithm can control simplification degree of point cloud, delete the maximum
redundant information, adaptive to retain topographical features information. Therefore, we
could construct the Multi-Level of Detail Organization of Airborne LIDAR Data, and it can
be the basis of the visualization and transmission network of LIDAR data.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853O (2008) https://doi.org/10.1117/12.815748
Due to finite space, there is an increasing need to plan and develop strategic underground facilities and
infrastructures for various military and non-military applications in Singapore in recent years. The awareness of the
underground option among planners, developers, and financiers should be increased so that subsurface planning issues
can be better addressed. The lack of adequate and accurate 3D spatial data often makes the design and construction of
such underground works difficult. It is necessary to integrate all of the spatial objects for underground planning.
Over the past two decades, a number of commercial software systems have been developed for 3D geographic and
geological modeling. For example, VGEGIS software allows users to create 3D surface geological maps. 3D
GeoModeller, a 3D geological modeling and geophysical inversion package, allows project geologists to build realistic
3D geology models.
This paper presents an approach to integrate the geographic and geological models for underground planning. A
prototype of 3D Geographic Information System (3DGIS) called "3DRock" has been developed by authors to implement
the data integration with 3D GeoModeler. The results so far showed that 3DRock is able to integrate the above-surface,
surface, and subsurface information available from maps, sections, terrain models, topographic data, drillholes, etc. for
the Banyan Basin in Jurong Island, Singapore, in a case study.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853P (2008) https://doi.org/10.1117/12.815832
The growth of web and wireless of geographical information systems presents a new set of challenges for map
personalization services, because web and wireless mobile users of geographical information systems require
information that is directly relevant to the specific task in which they are engaged. In this paper, we propose to set up
user ontology for map personalization. Based on the user ontology, we put forward and adopt the cartographic
generalization for web map personalization visualization driven by user ontology, which remain or reduce online web
map description data according to user's interests and increase user's understanding of the web map. Based on this, we
set up automatic web cartographic prototype systems to generate web mapping on demand.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853Q (2008) https://doi.org/10.1117/12.815963
Spatial buffer analysis is one of the important and basic spatial operation functions of geographic information system.
Studying 2D spatial buffer generation and analysis was more than the 3D spatial presently, thereby a novel 3D buffer
generation algorithm based on vector was presented in this paper. 3D spatial solid is represented by B-Rep model and it's
buffer is categorized into solid boundary buffer and solid interior, then construct the whole buffer by union operation on
them. The boundary features of 3D spatial solid are classified into point feature, line features and face features. Usually,
the statistical analysis is necessary after solid buffer generation. Thus, we proposed a new method which can quick judge
whether the buffer affecting the surrounding objects based on collision detection theory. Finally, taking the surface and
underground 3D space around University City region of Xianlin as the research area, a 3D buffer with complex
geological environment and man-made buildings is created based on the new presented algorithm, and spatial statistical
analysis is achieved based on the generated 3D buffer. The results show that the improved algorithm is efficient and
practicable, especially the proposed 3D buffer generation algorithm based on vector is applicable for convex body and
concave body comparing with current approaches.
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Geospatial Analysis and Service: Uncertainty and Accuracy
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853R (2008) https://doi.org/10.1117/12.815017
Mixture spectra are common in remote sensing due to the limitations of spatial resolution and the heterogeneity of land
surface. During the past 30 years, a lot of subpixel model have developed to investigate the information within mixture
pixels. Linear spectral mixture model (LSMM) is a simper and more general subpixel model. LSMM also known as
spectral mixture analysis is a widely used procedure to determine the proportion of endmembers (constituent materials)
within a pixel based on the endmembers' spectral characteristics. The unmixing accuracy of LSMM is restricted by
variety of factors, but now the research about LSMM is mostly focused on appraisement of nonlinear effect relating to
itself and techniques used to select endmembers, unfortunately, the environment conditions of study area which could
sway the unmixing-accuracy, such as atmospheric scatting and terrain undulation, are not studied. This paper probes
emphatically into the accuracy uncertainty of LSMM resulting from the terrain undulation. ASTER dataset was chosen
and the C terrain correction algorithm was applied to it. Based on this, fractional abundances for different cover types
were extracted from both pre- and post-C terrain illumination corrected ASTER using LSMM. Simultaneously, the
regression analyses and the IKONOS image were introduced to assess the unmixing accuracy. Results showed that
terrain undulation could dramatically constrain the application of LSMM in mountain area. Specifically, for vegetation
abundances, a improved unmixing accuracy of 17.6% (regression against to NDVI) and 18.6% (regression against to MVI) for R2 was achieved respectively by removing terrain undulation. Anyway, this study indicated in a quantitative
way that effective removal or minimization of terrain illumination effects was essential for applying LSMM. This paper
could also provide a new instance for LSMM applications in mountainous areas. In addition, the methods employed in
this study could be effectively used to evaluate different algorithms of terrain undulation correction for further study.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853S (2008) https://doi.org/10.1117/12.815656
Uncertainty is an integral component in thematic mapping, and descriptors such as percent correctly classified pixels
(PCC) and Kappa coefficients of agreement have been devised as thematic accuracy metrics. However, such spatially
averaged measures neither offer hints about spatial variation in accuracy, nor are they useful for error propagation in
derivatives due to the deficiency that spatial dependency is not properly accommodated. Geostatistics provides a good
framework for spatial uncertainty characterization, as conditional simulation is designed for generating equal-probable
realizations of often sparsely sampled fields of concern, which can be summarized for error statistics or subjected to
particular geo-processing to facilitate error propagation. Often, for modeling errors in area-class maps depicting
distributions of spatial classes, stochastic indicator simulation is employed. Unfortunately, indicator approaches suffer
from non-invariant behaviors in simulated classes as class labels are drawn from intervals of class probabilities that are
arbitrarily ordered. Discriminant space-based models have been proposed to enhance consistency in mapping spatial
classes and replicability in modeling spatial categorical uncertainty. This paper explores bivariate (rather than univariate)
discriminant models and extends uncertainty modeling from single-time to bi-temporal area-class maps. Experiment
using simulated data sets was carried out to quantify errors in area classes and their propagation in change analysis. It
was found that there are significant differences between the results obtained by discriminant models and those by
indicator geostatistics. Further investigations are anticipated incorporating real data for mapping and propagating errors
in area classes.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853T (2008) https://doi.org/10.1117/12.815915
For the application of high-resolution airborne SAR stereo positioning, a kind of approximately precise parameter error
model has been adopted in this paper to discuss the influence of the direct or indirect-inputted parameters' errors on the
final stereo positioning accuracy. Through the describing of the precise parameter error model and the analysis about the
error sources for the airborne SAR stereo positioning model, the corresponding simulation tests have been taken in the
test site, and the results have shown that most of the direct-inputted parameter errors have little influence on the final
plane stereo positioning accuracy, while almost all of the them will introduce more error into the elevation computation.
And the indirect-inputted phase error arisen from time delay is the main error source during the process of atmosphere
transmitting of radar wave.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853U (2008) https://doi.org/10.1117/12.815966
One quality estimate model was put forward. It combined the common-point comparison with the scale of wavelet
analysis. So, the study on uncertainty estimate based on single data set gained enormously advance. The result indicates
that when the ratio between the number of common-points and the number of wavelet low-frequency coefficients is 1.5,
the model can estimate the quality for multi-scale representation of linear feature. It provided the quality estimate model
for multi-scale representation of linear feature based on wavelet analysis.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853V (2008) https://doi.org/10.1117/12.812392
To use target information for space transformation in remote sensing data field, artificial immune network theory is
introduced to multi-spectral remote sensing information mining, based on the knowledge of target spectrum. First, the
target spectrums are fuzzy clustered into several subclasses, to retain different features of target in different subclasses.
Then we develop a novel Regional-memory-pattern Artificial Immune Idiotypic Network (RAIN) model based on
artificial idiotypic network theory, and train RAIN with subclasses samples. And then, the affinities of the target
spectrum and other objects can be calculated according to the immune microscopic dynamics including stimulation and
suppression effect. Finally, principal component analysis (PCA) is performed to affinities to explore more weak and
hidden information. With its application in Baoguto Area, Xinjiang Uyghur Autonomous Region China, choosing
tuffaceous siltstone as target object, the result supports the efficiency of the RAIN-affinity-PCA scheme.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853W (2008) https://doi.org/10.1117/12.815718
Developments of raster data capture technologies and demands from application fields call for advanced raster data
analysis methods. Visual data mining that involves human's visual analytical capability in data analysis attracts attention
in recent years. Raster datasets usually have large amount of pixels, which may cause serious clotting problem in
visualization and thus challenges visual data mining. The research reported here mainly focuses on this problem and tries
to construct a hierarchical framework for visual data mining of raster data. In the hierarchical structure, the first level
uses volume rendering to visualize the whole raster dataset in attribute space, which can greatly reduce the impact of
clotting. To avoid the loss of subtle patterns, the second level makes use of parallel coordinates plot to reflect detailed
attribute information. This hierarchical structure ensures that both global and local patterns embedded in data can be
detected. In both levels, visualizations of attribute space are linked with that of geographic space. Software prototype
was developed and then applied to find small clusters that may relate to possible soil types. Case study result
demonstrated the effectiveness of this proposed approach.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853X (2008) https://doi.org/10.1117/12.815757
This paper proposed a novel method, scaleable moving window (SMW), to mine spatial association rules
while fully taking the fact that spatial heterogeneity may widely exist. SMW is based on the traditional association
rule mining algorithm, Apriori. However, we integrated different moving windows (in terms of window size and
shape) with Apriori. During the spatial association mining process, various sizes of windows were used to move over
the region of interest. Each window, after moving through the whole region, will produce a set of association rules
within the current location of the moving window. The spatial association pattern was represented by the support
value and confidence value of spatial association within all the locations of the moving window by Apriori algorithm.
Different windows were tested to compare the effectiveness of the windows. Compared with traditional method
where the spatial association was assumed to be for the whole region, the proposed method could well reflect the
reality by giving the fact that spatial association spatially varies when spatial heterogeneity exists. This proposed
method was applied in the provincial capital city, Wuhan, Hubei province, China where the spatial associations
between residential buildings and roads showed spatially varied, which reflected the real condition of the city.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853Y (2008) https://doi.org/10.1117/12.815828
The spatial data in GIS-T database is huge and complicated, discovery knowledge from this database is very
important, region traffic network evaluation is one of the important contents. In this paper the author referred
to an integrated algorithm combined Ant colony algorithm with FCM to cluster the traffic data of 15 regions
of Hubei Province, then used the method of maximizing deviation to arrange the clustering result. From the
result we can evaluate the traffic conditions of the 15 regions.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853Z (2008) https://doi.org/10.1117/12.815880
Spatial distribution pattern is an arrangement of two or more spatial objects according to some spatial relations, such as
spatial direction, topological and distance relations. In the real world, spatial objects and spatial distribution pattern all
vary continuously along the time-line. Traditional spatial and non-spatial data dissevers this continuous spatio-temporal
process. Under analyzing relations among spatial object, its attributes and spatial distribution pattern, we brought metaspatio-
temporal process, spatio-temporal process and spatial distribution pattern spatio-temporal process. Rainfall in
Eastern China has a typical spatial distribution pattern, being composed of the northern rain area and the southern rain
area. Through constructing spatio-temporal process transactions, the association rules can be extracted from spatiotemporal
process data set by the Apriori algorithm. The result of the spaio-temporal process association rule mining is
consistent with the analysis of the theory. Finally, it is concluded that the spatio-temporal process can describe change of
a spatial object in a defined time range, and change trend of one entity can be forecasted through varying trend of others
based on the valuable spatio-temporal process association rules.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728540 (2008) https://doi.org/10.1117/12.815957
Spatial dependency describes the relationship between one dependent spatial variable and other related spatial
variables. This paper constructs two kinds of Fuzzy Neural Networks for spatial dependency mining, the modified fuzzy
neural network model and the fuzzy comprehensive assessment network model. The first model is built from general
fuzzy neural network model. It has four layers, input layer, fuzzy membership function layer, fuzzy reasoning layer and
output layer. The second model is built based on a fuzzy comprehensive assessment algorithm. It has five layers. The
first three layers are same as the first model, the fourth and the fifth layer are used to find the maximum membership
degree and give the output. We develop the training algorithm for these two models based BP algorithm and genetic
algorithm, respectively. This paper adopts a thematic spatial database of land evaluation to test these models. We use
experiential knowledge as original rules to build initial FNN models. We can see that original rules (spatial dependencies)
are corrected after training. It can be seen that these two models get almost the same revised dependencies, and this
indicates that these two models both correct the original ones and get the more objective spatial dependencies.
Experiments also indicate these two models are efficient.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728541 (2008) https://doi.org/10.1117/12.815993
A huge amount of geospatial and temporal data have been collected through various networks of environment
monitoring stations. For instance, daily precipitation and temperature are observed at hundreds of meteorological stations
in Northeastern China. However, these massive raw data from the stations are not fully utilized for meeting the
requirements of human decision-making. In nature, the discovery of geographical data mining is the computation of
multivariate spatio-temporal correlations through the stages of data mining. In this paper, a procedure of mining
association rules in regional climate-changing databases is introduced. The methods of Kriging interpolation, fuzzy cmeans
clustering, and Apriori-based logical rules extraction are employed subsequently. Formally, we define
geographical spatio-temporal transactions and fuzzy association rules. Innovatively, we make fuzzy data
conceptualization by means of fuzzy c-means clustering, and transform fuzzy data items with membership grades into
Boolean data items with weights by means ofλ-cut sets. When the algorithm Apriori is executed on Boolean transactions
with weights, fuzzy association rules are derived. Fuzzy association rules are more nature than crisp association rules for
human cognition about the reality.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728542 (2008) https://doi.org/10.1117/12.814898
Because of the unique geometry and radiometric characteristics of linear CCD satellite image pairs, methods
developed for aerial or perspective image pairs cannot be applied. This paper proposed stereo matching algorithms taking
the epipolar line of linear pushbroom sensors and scene geometry into account for satellite images. Firstly, the author
puts forward the approximate line constraint method of dynamic epipolar line, and sets up constraint conditions of
epipolar line in linear CCD stereo image matching, and proposes an imaging constraint method on the basis of
application analysis of epipolar line, with imaging characteristics taken into account. The method can eliminate the
distortion of geometry and make the primitives more prominent. At last we assess the performance of our strategy using
real satellite image data. The results show we can increase the accuracy of image match and minimize the computation
time with these techniques.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728543 (2008) https://doi.org/10.1117/12.814979
The project for the road information updating in geographical information system by using kinematic GPS method has
been finished for county and country roads in China. The kinematic positioning results of commercial GPS navigation
software, differential GPS positioning and an adaptively robust filtering are compared and analyzed. A synthetic adaptive
factor by combining two kinds of adaptive factors is proposed for adjusting the contributions of kinematic model
information and measurements on the state estimates, one is constructed with the statistics of discrepancy of kinematic
model predicted state and estimated state from the measurements, and the other is set up by using the statistic of
predicted residual vector. It is shown by experiments that the adaptively robust filtering with synthetic adaptive factor is
valid in the cases with or without adequate GPS measurements. The calculation procedure is similar to the standard
Kalman filter and navigation results are robust in controlling the influences of the outliers of the GPS measurements and
kinematic state disturbing of the vehicle. The accuracy of adaptively robust filtering with only the GPS pseudo-ranges
can meet the requirements of the road information updating for 1:250000 digital maps.
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Jianhu Zhao, Fengnian Zhou, Hongmei Zhang, Juanjuan Li
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728544 (2008) https://doi.org/10.1117/12.815000
In large-scope marine investigation, the traditional bathymetric measurement can not meet the requirement of rapid data
acquisition with lower cost of financial and material resources, while remote sensing (RS) technology provides a perfect
way in the work. RS can not only provide quickly and efficiently the information of underwater topography with respect
to the traditional method, but also present corresponding underwater topography with different-period RS images. In this
paper, we depict in detail the procedures and some key techniques in acquiring underwater topography by remote sensing
inversion technology based on self-organization feature mapping (SOFM). Firstly, we introduce some basic theories
about the acquisition of underwater topography by the RS inversion technology. Besides, we discuss the data acquisition
and preparation in the work. Moreover, we implement correlation analysis and find out the sensitive bands used for
building RS inversion model. In virtue of SOFM, we construct the mapping relation between water depth and the
reflectivity of sensitive band in the studied area, and test the it in two experimental water areas. The model achieves
satisfying accuracy and can meet the requirement of given bathymetric scale. Finally the mapping relation is used for the
water depth inversion in the studied water area. We also use the water depth from the model to draw the underwater
topographic map in the water area.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728545 (2008) https://doi.org/10.1117/12.815178
Because of their inherent advantages, Geographic Information System (GIS) and Remote Sensing (RS) are extremely
useful for dealing with geographically referenced information. In the study of epidemics, most data are geographically
referenced, which makes GIS and RS the perfect even necessary tools for processing, analysis, representation of
epidemic data. Comprehensively considering the data requirements in the study of highly pathogenic avian influenza
(HPAI) coupled with the quality of the existing remotely sensed data in terms of the resolution of space, time and spectra,
the data sensed by MODIS are chosen and the relevant methods and procedures of data processing from RS and GIS for
some environmental factors are proposed. Through using spatial analysis functions and Exploratory Spatial Data
Analysis (ESDA) of GIS, some results of relationship between HPAI occurrences and these potential factors are
presented. The role played by bird migration is also preliminarily illustrated with some operations such as visualization,
overlapping etc. provided by GIS. Through the work of this paper, we conclude: Firstly, the migration of birds causes the
spread of HPAI all over the country in 2004-2005. Secondly, the migration of birds is the reason why the spread of HPAI
is perturbed. That is, for some classic communicable diseases, their spread exhibits obvious spatial diffusion process.
However, the spread of HPAI breaks this general rule. We think leap diffusion and time lag are the probable reasons for
this kind of phenomena. Potential distribution of HPAI viruses (corresponding to the distribution of flyways and putative
risk sources) is not completely consistent with the occurrences of HPAI. For this phenomenon, we think, in addition to
the flyways of birds, all kinds of geographical, climatic factors also have important effect on the occurrences of HPAI.
Through the case study of HPAI, we can see that GIS and RS can play very important roles in the study of epidemics.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728546 (2008) https://doi.org/10.1117/12.815600
On May 12 in 2008, a Magnitude 8.0 earthquake hit Wenchuan in China, and the casualty shocked the whole world. The
landslide was a frequent secondary disaster in this earthquake, so to analyze the mechanism of landslides in the disaster
area is very important for post-earthquake reconstruction. The study area is located in PingWu County, which was also
hit by the earthquake severely. And the data sources are ETM+ image, DEM and interpreted ALOS image. This paper
considered four potential driving factors for landslides, and they are land cover, lineament, slope and drainage. The land
cover was classified based on the density of vegetation, and sub-pixel analysis was employed; Density of lineament was
calculated by Sobel operator and image segmentation; Slope was classified by using a threshold; Drainage was
considered without numerical analysis, because it is significant and simple in study area. To find out how they influenced
the landslides, conditional probability was utilized as a measurement. The result shows that areas in sparse vegetation,
dense lineament and steep topography were easy to meet landslides, while drainages also induced landslides.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728547 (2008) https://doi.org/10.1117/12.815717
A rough set based method for oil-gas reservoir rule extraction and automatic identification through petroleum logging
data is provided in this paper. Based on the traditional way of rough set data mining, this method makes adjustments to
the mining procedure and optimizes the reduction, discretization, and rule generation steps respectively via Sweep
Forward Neighborhood Fast Algorithm, Fuzzy Clustering FCM Algorithm, and CAAI Decision Tree Algorithm,
allowing itself more applicable to the issue of oil-gas reservoir rule extraction through petroleum logging data.
Afterwards, the automatic identification of oil-gas reservoir is enabled by a case-based reasoning method. This paper
analyzes the applicability of rough set method and case reasoning to petroleum logging data, and verifies algorithms'
feasibility through an actual set of petroleum logging data.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728548 (2008) https://doi.org/10.1117/12.815727
Digital elevation model (DEM) is indispensable for many applications in earth sciences, and there are many kinds
of DEM generation methods, such as interpolation between contour lines from topographic maps, stereoscopy from
aerial photographs or satellite images, and interferometry from Synthetic Aperture Radar (SAR) data.
Due to long years of coal mining activities, topographic changes have happened to Fushun city, northeastern China.
In this study, different DEM generation methods of Advanced Spaceborne Thermal Emission and Reflection Radiometer
(ASTER) stereoscopy, ERS tandem Interferometry Synthetic Aperture Radar (InSAR), and Shuttle Radar Topography
Mission (SRTM) InSAR were discussed. Multi-temporal and multi-source DEM data, with different spatial resolutions
of 15 m, 40 m and 90 m respectively, were combined to study the topographic changes in the past 10 years caused by
open coal mining activities in western Fushun city. ERS InSAR DEM and SRTM DEM data are free of weather
conditions, but ASTER DEM quality may be affected by cloud coverage in some local areas.
Results from multi-source of DEM data, i.e. ERS InSAR, SRTM and ASTER DEM, show that obvious topographic
changes associated with coal mining activities have occurred in Fushun area. The depth of the famous West Open Coal
Mine is increasing in the past 10 years, and the maximum depth change is 140 m between 1996 and 2006. Meanwhile,
the elevation of three waste rocks piling fields increased more than 10 m due to the coal mining activities.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728549 (2008) https://doi.org/10.1117/12.815742
Quantitative analysis of the temporal and spatial distribution characteristics of coastal nutrient substances enables to
adequately estimate the state of coastal marine environment and describe environmental change processes conditioned by
anthropogenic forces. Remote sensing has the potential to provide synoptic information and has been somewhat
successful in monitoring nutrient properties at rivers and estuaries. So taking total inorganic nitrogen (TIN) as typical
nutrient monitoring index, Sheyang River estuary located in middle part of Jiangsu coastline, China was chosen for water
quality simulation and variation trend analysis. Six correlation coefficient matrixes were calculated by using
synchronous TIN concentration and its corresponding normalized water surface reflectance data from 15 field samples.
Results showed that band combination of 804 and 630nm with the form of pseudo-sediment parameter could get the best
correlation capacity and minimized reversion error. Based on this selected parameter, an inverse model was built for TIN
quantitative reversion. R2 coefficients reached 0.97 and 0.9972 in calibration and validation period respectively. And
then the spatial distribution pattern of TIN in Sheyanghe River estuary was obtained using the inverse model via
Hyperion hyperspectral remote sensing image. A coupled wave-tide-surge model and material transport and diffusion
model were adopted for TIN concentration cross validation of the reversion precision exactly at river outlet. Comparison
results indicated that these two dataset made a good consistency for TIN diffusive characters in Sheyang River estuary
with the R2 reached 0.6549. The magnitude of TIN concentration was also agreed fairly well.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854A (2008) https://doi.org/10.1117/12.815765
Karst rocky desertification is a special kind of land desertification developed under violent human impacts on the
vulnerable eco-geo-environment of karst ecosystem. The process of karst rocky desertification results in simultaneous
and complex variations of many interrelated soil, rock and vegetation biogeophysical parameters, rendering it difficult to
develop simple and robust remote sensing mapping and monitoring approaches. In this study, we aimed to use Earth
Observing 1 (EO-1) Hyperion hyperspectral data to extract the karst rocky desertification information. A spectral
unmixing model based on Monte Carlo approach, was employed to quantify the fractional cover of photosynthetic
vegetation (PV), non-photosynthetic vegetation (NPV) and bare substrates. The results showed that SWIR (1.9-2.35μm)
portions of the spectrum were significantly different in PV, NPV and bare rock spectral properties. It has limitations in
using full optical range or only SWIR (1.9-2.35μm) region of Hyperion to decompose image into PV, NPV and bare
substrates covers. However, when use the tied-SWIR, the sub-pixel fractional covers of PV, NPV and bare substrates
were accurately estimated. Our study indicates that the "tied-spectrum" method effectively accentuate the spectral
characteristics of materials, while the spectral unmixing model based on Monte Carlo approach is a useful tool to
automatically extract mixed ground objects in karst ecosystem. Karst rocky desertification information can be accurately
extracted with EO-1 Hyperion. Imaging spectroscopy can provide a powerful methodology toward understanding the
extent and spatial pattern of land degradation in karst ecosystem.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854B (2008) https://doi.org/10.1117/12.815919
In order to manage the internal resources of Gulf of Tonkin and integrate multiple-source spatial data, the establishment
of region unified plan management system is needed. The data fusion and the integrated research should be carried on
because there are some difficulties in the course of the system's establishment. For example, kinds of planning and the
project data format are different, and data criterion is not unified. Besides, the time state property is strong, and spatial
reference is inconsistent, etc. In this article the ARCGIS ENGINE is introduced as the developing platform, key
technologies are researched, such as multiple-source data transformation and fusion, remote sensing data and DEM
fusion and integrated, plan and project data integration, and so on. Practice shows that the system improves the working
efficiency of Guangxi Gulf of Tonkin Economic Zone Management Committee significantly and promotes planning
construction work of the economic zone remarkably.
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Jiancheng Li, Shoujian Zhang, Xiancai Zou, Zhengtao Wang
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854C (2008) https://doi.org/10.1117/12.815935
Thanks to the high performance of the spaceborne GPS receiver and the availability of precise IGS orbit and clock
products, Zero-difference kinematic precise orbit determination (POD) has turned out to be a new method in orbit
determination for the LEO satellites. Zero-difference Kinematic POD, which is based on the GPS measurements only
from the spaceborne GPS receiver, is independent of force models and orbit design. From that point of view, kinematic
POD is well suited for the Earth Observation satellites at very low altitudes, such as CHAMP, GRACE and GOCE et al.
This paper reviews the basic zero-difference GPS model, and the corrections in the model are discussed. A block-wise
least squares algorithm, which firstly separates the parameters in to groups and then solves the parameter by elimination
and back-substitution, is discussed and proposed for the kinematic orbit determination. The orbit solutions for one week
of GRACE observations are calculated Comparisons with the published Rapid Science Orbit (RSO) indicate that the
accuracy in radial, along-track and cross-track direction can achieve 5.5cm, 5.5cm and 6.6cm respectively, and the RMS
in distance is better than 8.6cm.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854D (2008) https://doi.org/10.1117/12.815936
Even more than ten years passed after the reclamation completion in 1997, the residual settlement is still a critical issue
for the Chok Lap Kok Airport, Hong Kong. In this research, the main goal was to investigate this differential settlement
across the airport platform by using the PSInSAR-derived deformation measurement and local geological data. An
enhanced PSInSAR approach (the CPTA analysis) was applied to a total of 20 ENVISAT ASAR images acquired
between March 2003 and March 2008 for the deformation filed retrieval. Our results show that most of buildings are
stable but some of reclamation areas have still experienced a slight settlement. The results also suggest that the CPTA
approach has a potential to monitor the deformation of some special civil utilities (e.g. airfield). A statistic analysis with
the geological data indicates that the variability of residual settlement across the reclamation may be associated
reclamation fill (fill types and thickness) and geological conditions underlying the airport platform.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854E (2008) https://doi.org/10.1117/12.815985
In this paper, we create the geospatial data of three-dimensional (3D) modeling by the combination of digital
photogrammetry and digital close-range photogrammetry. For large-scale geographical background, we make the
establishment of DEM and DOM combination of three-dimensional landscape model based on the digital
photogrammetry which uses aerial image data to make "4D" (DOM: Digital Orthophoto Map, DEM: Digital Elevation
Model, DLG: Digital Line Graphic and DRG: Digital Raster Graphic) production. For the range of building and other
artificial features which the users are interested in, we realize that the real features of the three-dimensional
reconstruction adopting the method of the digital close-range photogrammetry can come true on the basis of following
steps : non-metric cameras for data collection, the camera calibration, feature extraction, image matching, and other
steps. At last, we combine three-dimensional background and local measurements real images of these large geographic
data and realize the integration of measurable real image and the 4D production.The article discussed the way of the
whole flow and technology, achieved the three-dimensional reconstruction and the integration of the large-scale threedimensional
landscape and the metric building.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854F (2008) https://doi.org/10.1117/12.816004
The Sichuan Earthquake, occurred on May 12, 2008, is the strongest earthquake to hit China since the 1976
Tangshan earthquake. The earthquake had a magnitude of M 8.0, and caused surface deformation greater than 3 meters.
This paper presents the research work of measuring the co-seismic deformations of the earthquake with satellite
differential interferometric SAR technique. Four L-band SAR images were used to form the interferogram with 2 pre-
scenes imaged on Feb 17, 2008 and 2 post- scenes on May 19, 2008. The Digital Elevation Models extracted from
1:50,000-scale national geo-spatial database were used to remove the topographic contribution and form a differential
interferogram. The interferogram presents very high coherence in most areas, although the pre- and post- images were
acquired with time interval of 92 days. This indicates that the L-band PALSAR sensor is very powerful for
interferometry applications. The baseline error is regarded as the main phase error source in the differential interferogram.
Due to the difficulties of doing field works immediately after the earthquake, only one deformation measurement
recorded by a permanent GPS station is obtained for this research. An approximation method is proposed to eliminate the
orbital phase error with one control point. The derived deformation map shows similar spatial pattern and deformation
magnitude compared with deformation field generated by seismic inversion method.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854G (2008) https://doi.org/10.1117/12.816090
Gross primary production (GPP) is the total amount of atmospheric carbon (CO2) assimilated by vegetation. In this
article, a regional terrestrial ecosystem GPP estimation model REG-PEM(REGion Production Efficiency Model) is
developed based on light use efficiency theory, and 8-day composite and annual GPP are calculated using REG-PEM
model in Jiangxi province. The REG-PEM model was designed on the basis of the production efficiency concept in
which gross primary production is calculated from the products of the photosynthetically active radiation (PAR)
absorbed by the vegetation(APAR) and light use efficiency, and all the input data get from remote sensing method. GPP
are calculated using MODIS 8-day composite products and total ozone mapping spectrometer (TOMS) reflectance data
in Jiangxi province in 2003 and 2004. GPP increases in spring, reaches maximum in summer and decreases in autumn,
and fluctuates in the year. The results indicate that the REG-PEM model is capable of tracking seasonal dynamics and
interannual variations in GPP at a 8-day temporal resolution.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854H (2008) https://doi.org/10.1117/12.811843
In a long period, arid area is in the special natural environment which is drought and lack of water. Land use/land cover
pattern is formed stably with the arid area characteristics. Nowadays, in the arid area of northwest China, with the
implementation of the great western development and the increased industrialization process, land use pattern is affected
by human activities significantly and the evolution of the land use pattern accelerates ceaselessly. Liangzhou county of
Wuwei city is one typical arid area of northwest China, so it is significant to choose it to be the research region to study
land use temporal and spatial characteristics of China's western arid area for understanding the arid area's land use status
and the national economy production by adopting remote sensing (RS) and geographic information system (GIS)
technologies. The research plays a guiding role for the reasonable land use in the future.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854I (2008) https://doi.org/10.1117/12.814848
With increasing volume of data in modern science, there has been a rapid expansion of interests and researches on data
mining, which is an increasingly popular tool in data analysis to obtain implicit knowledge. Decision Tree (DT), as one
of widespread used classification approaches in data mining, is used successfully in many diverse areas. This paper
attempts to show how to apply Decision Tree on land suitability analysis and make some conclusions for its application.
Firstly, the approach of application of DT on Land Suitability and the popular learning algorithm is discussed. Then 3
towns' land units in Hainan province are selected as study case to demonstrate our approach by C4.5 implemented using
C++ language, and the obtained results are compared to the results in the literature and are checked by random sample
investigation. The major conclusion is that DT is suitable for land suitability analysis, by which a high veracity result can
be obtained, and the obtained classifying knowledge is readable and can be interpreted well. In some sense, it can adjust
knowledge by updated training dataset naturally and avoid the highly dependence with experience.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854J (2008) https://doi.org/10.1117/12.814910
This study attempts to analyse the spatial pattern of land cover change trajectories derived through multi-temporal
remote sensing image processing. The study is based on a previous study which utilise the landscape metrics to analyse
the spatio-temporal pattern of farmland change trajectories in an arid environment of western China. The focus of this
paper is on the ephemeral farmlands that were cultivated and abandoned in succession during the study period. The
multi-temporal images were firstly classified independently and farmland change trajectories were established using GIS.
Then the "abandoned farmland" and "ephemeral farmland" trajectories were identified and further classified according to
the change scenarios. The spatial pattern of these ephemeral farmlands were analysed to explore the nature and causes of
the change, particularly the likelihood of farmland abandonment which has been recognised as a major reason for land
degradation of China's aridzone.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854K (2008) https://doi.org/10.1117/12.815330
The Grand Canal of China is the longest ancient canal in the world. It is an astonishingly huge project in the history
of Chinese civilization. However, some sections have already disappeared as the development of society and change of
environment. It can be detected by using very high resolution image. Object-oriented method based on image
segmentation is being actively studied in the high resolution image process and interpretation to extract a variety of
thematic information. It includes two consecutive processes: first the image is subdivided into separated regions
according to the spectral and spatial heterogeneity in the image segmentation process and then the objects are assigned to
a specific class according to the class's detailed description in the image classification process. The result shows that the
object-oriented approach can realize the full potential of the very high resolution image, have higher accuracy compared
with traditional classification and allow quantitative analysis of land use, simplification of Remote Sensing and GIS
integration.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854L (2008) https://doi.org/10.1117/12.815576
In the upper stream of Yellow River, the status of vegetation cover is not as good as other location in the east of
China. Considering the huge economic benefit of building hydroelectric stations, people took a lot of measures to
structure hydropower stations, including in the upper stream of Yellow River.
The objective of this study was to figure out the temporal variation and spatial rules of the vegetation cover based
the time-series Moderate Resolution Imaging Spectroradiometer (MODIS) 250m NDVI datasets and Landsat satellites
image data in the upper stream of Yellow River. The exact study region is the area along the Yellow River from Liujiaxia
hydropower station to Qingtongxia hydropower station (Liu~Qing section). The research adopted the rules of average
in-year NDVI changes extracted from MODIS data to modify the NDVI calculated from Landsat satellite images of
different months to obtain the spatial heterogeneity and temporal dynamics in vegetation variation. A series of statistical
analysis were applied to the NDVI and weather characteristics to identify the relation between them. Compared to the
effect of weather factors, the relations between hydroelectric development and vegetation cover changes were analyzed.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854M (2008) https://doi.org/10.1117/12.815577
A time series of Landsat Thematic Mapper (TM) satellite images are used to examine changes of cultivated land in
Xinxiang City, Henan Province of China. After data processing and interpreting, information of cultivated land is
extracted in the late 1980s, 1995, 2000 and 2005. Then, the paper mainly focuses on the spatio-temporal change study of
cultivated land in Xinxiang City. Time series model, cultivated land changed degree model and fragmentation index are
used to analyze the change of cultivated land and its subclasses in quantity. The results show that with time varying,
cultivated land area as well as area of its subclasses, dynamic degree and fragmentation extent has been changing all the
time and the size of change area is not the same at different periods. And both decreasing and increasing exit. Next, GIS
spatial analysis and barycenter transfer model are used to analyze the spatial change of cultivated land. The outcomes of
transfer matrixes reflect that the change course of cultivated land had two aspects including roll-in and roll-out, and
although there are many interchanges between cultivated land and forest, grassland, water region and unused land, the
urbanization and economic development are main reasons for the loss of cultivated land. Through calculating the
barycenter, the results show that on the whole, the cultivated land barycenter in Xinxiang has a trend of moving
southeast, reflecting that cultivated land in southeast part had a smaller reduction than northwest part.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854N (2008) https://doi.org/10.1117/12.815734
The authors introduce unsupervised Wishart classification technique for fully polarimetric SAR data based on H-alpha
decomposition of POLSAR images, and applied this technique to AIRSAR data of Flevoland, Netherlands. By applying
the Cloude H-alpha decomposition to the original L-band image, we segment the image to 9 classes. While take this as
the initial input, Wishart classification is followed. The most valuable in this paper is the section of application analysis.
We found H-alpha classification has lower classification accuracy than Wishart iteration which use coherence matrix, but
why? By analyzing the classification results for each type of land cover, this paper concluded the reason is that
parameters of entry and alpha angle lose the original polarimetric information. While coherence matrix does not lose the
original polarimetric information, we suggest that directly use coherence matrixes could derive much higher
classification accuracy. There is also another found. Middle entropy scattering such as low vegetation often does not a
single target while high or low entropy scattering, such as the deep forest and water, the coverage relatively much denser,
often has single component; thus, the classification accuracy of high of low entropy land cover will be much higher than
middle entropy scattering.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854O (2008) https://doi.org/10.1117/12.815747
Rapid land use change has take place in Wuhan, the largest mega-city in central China during the last decade.
Remotely sensed imagery together with geographical information system have long been utilized to monitor spatial and
temporal land use change. The aim of this paper is to find out the land use change and the trend of urban growth in
Wuhan, China using satellite images. The Landsat TM image acquired in 1991 and the Landsat ETM image acquired in
2002 were used to monitor land use change in Wuhan. The images were geo-referenced according to Gauss-Kruger
projection with Krasovsky spheroid, by using 1:50, 000 topographical maps. The image processing is implemented by
using Erdas Imagine package. The RMS error has been controlled under the limit of 1 pixel. The geo-referenced images
were classified as seven land use types: cultivated land, forest land, grassland, urban and villages, transportation, water
bodies and barren land. Two land use maps were produced for each date. The geo-referenced, classified images were
compared pixel by pixel to locate and quantify land use changes that took place from 1991 to 2002 period. The further
change detection analysis in a later stage is performed in ArcGIS. The transition matrix was produced and the
quantitative information on the size of land use change from one type to another was compiles. The results of study
indicate that the conversion of land use from cultivated land to urban was prominent, the rapid urban sprawl has
occupied lots of cultivated land and water bodies, the urban area significantly increased 30%, most of which are
converted from cultivated land. these valuable cultivated land need careful protection by providing land use plans to
guide urban growth going toward the right directions. The results obtained from this application also indicate that the use
of satellite imageries is very useful for mapping land use changes, and the monitoring land use change is essential for
land use planning and urban sustainable development.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854P (2008) https://doi.org/10.1117/12.815976
The optimization of land use structure is always considered as the quantitative optimization. Moreover, it's the
optimization of spatial allocation and different scales. This paper obtains the spatial elements of land use by use the
remote sensing technology. The optimization model and convolution algorithm of optimization is proposed based on
remote sensing and ecological green equivalent. We can use these model and algorithm to optimize the data of land use
structure from multi-scales for every region which do not rely on the administrative boundaries, and they are evaluated
by the image data of Huangpi which obtain from landsat7 in 2005.The result indicates that the method can be applied to
optimize the land use structure for actual land use planning. They can realize the multi-scales land use structure
optimization for each region by dynamic control based on the RS and the ecological green equivalent. The reasonable
and accuracy is improved in land use planning.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854Q (2008) https://doi.org/10.1117/12.816083
The Urumqi City which located at the foot of the northern slope of the Tianshan Mountains in
Xinjiang, has a special basin-type topographic feature, with the long, cold and serious air pollution
winter. With the rapid process of urbanization and development in the recent years, whether has the
effect of Urban Heat Island(UHI) has been widespread concerned these years. Land Surface
Temperature (LST) in urban regions is an important influencing factor and indicator of the Urban
Heat Island (UHI). Urumqi City was taken to be the typical study area in this paper, MODIS data in
December of every year from 2000 to 2007 were chosen to take the LST retriving with the Split
Window Algorithm (Qin, Mao, etc.), which is a mature algorithm, with higher precision and simple
method, and the average absolute error of LST retriving products were ± 1.2 °C, according to the
analysis of the temporal and spatial distribution and changes of LST, the following conclusions had
been made: From the Monthly Compositon LST of Urumqi in December from 2000 to 2007, Urban
Heat Island (UHI) effect of Urumqi City in winter is not obvious and there is no disciplinary changes
of LST and no visible changes in temporal and spatial distribution of LST, in despite of eruptible
development of urbanization.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854R (2008) https://doi.org/10.1117/12.816112
Extracting land-use information within rural residential area is one of the major applications in remote sensing today. In
this paper, a new method, which is auxiliary land-use knowledge method, is presented for this requirement. With the
abundant geographic knowledge in the thematic map, we first propose a simple and effective method to extract rural
residential out-border from RS image by overlapping analysis, and take the result as the basic data for further
interpretation. Secondly, the object-oriented approach is employed for further classification, whose basic cell isn't a
single pixel any more, but rather an image object from image segmentation. During the process, land-use knowledge is
also taken as auxiliary information to establish class system and class hierarchy, select feature presentation of image
objects, and examine classification result. Finally, a high-resolution RS image of Hubei Province is taken as testing data
to verify the above method. The experiment results are satisfying: the detailed land-use information is extracted and
categories with similar spectrum feature are divided effectively. It is obvious that this method offers a good solution to
extract land-use information within rural residential area.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854S (2008) https://doi.org/10.1117/12.811371
In recent years, the Global Positioning System (GPS) techniques have been widely applied to monitor the superficial
movements of landslides. The main objective of this paper is to ascertain the application of GPS in landslide prediction
practice, taking Baishuihe landslide as an example. The 1260 Mm3 Baishuihe landslide (Three Gorge Reservoir, China),
susceptible to evolve into a soil slide, is studied. This landslide has been periodically monitored since 2003 with GPS
and other conventional equipments. Influencing factors have been recognized through the analysis of the GPS
monitoring data. Forecasting the failure of the landslides is difficult because of nonlinear time dependency and seasonal
effects, which affect the displacements. According to Crosta's method, Voight model is suggested to forecast fictitious
failures and to assess alert velocity thresholds using GPS monitoring data. Voight's equation has been expressed in terms
of displacement and used to fit the data by nonlinear estimation techniques. Velocity threshold values have been
computed and be used for emergency management by assuming these parameters (α, Α, τ, f, mechanical behaviour of the landslide mass approaching failure.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854T (2008) https://doi.org/10.1117/12.813978
Practices of sandstone-type uranium exploration in recent years in China indicate that the uranium mineralization
alteration information is of great importance for selecting a new uranium target or prospecting in outer area of the known
uranium ore district. Taking a case study of BASHIBULAKE uranium ore district, this paper mainly presents the
technical minds and methods of extracting the reduced alteration information by oil and gas in BASHIBULAKE ore
district using ASTER data. First, the regional geological setting and study status in BASHIBULAKE uranium ore district
are introduced in brief. Then, the spectral characteristics of altered sandstone and un-altered sandstone in
BASHIBULAKE ore district are analyzed deeply. Based on the spectral analysis, two technical minds to extract the
remote sensing reduced alteration information are proposed, and the un-mixing method is introduced to process ASTER
data to extract the reduced alteration information in BASHIBULAKE ore district. From the enhanced images, three
remote sensing anomaly zones are discovered, and their geological and prospecting significances are further made sure
by taking the advantages of multi-bands in SWIR of ASTER data. Finally, the distribution and intensity of the reduced
alteration information in Cretaceous system and its relationship with the genesis of uranium deposit are discussed, the
specific suggestions for uranium prospecting orientation in outer of BASHIBULAKE ore district are also proposed.
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Hong-Wei She, Yan-Ning Zhang, Xue-Gong Liu, Na Zhao
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854U (2008) https://doi.org/10.1117/12.814900
The problem of Yellow River main-stream detection with multi-spectral remote sensing images is investigated in this
paper. Firstly, the flow characteristic of Yellow River was analyzed. The spectral similarity of the main-stream was
discussed in succession. Then, based on the principle of spatial continuity, a main-stream dynamic transmission model
was proposed. Finally, a main-stream detection approach called Main-stream Spectral Correlation Dynamic Transmission
Approach (MSCDEA) was presented. The experiment indicates that the proposed algorithm is effective and can be used
in practice.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854V (2008) https://doi.org/10.1117/12.816011
Forest resource is the important material foundation of national sustainable development. And it need to master the status
and change of forest resource timely for reasonable exploitation of forest and its renewal. Laos is located in the heart of
the Indochinese peninsular, in southeast Asia, latitude 14° to 23 °north and longitude 100°to 108°east, covered a total
236, 800 square kilometers, and country of nearly 6 million people. The forest of Laos dropped from close to two-third
in the 1970's to less than half by the 1990's. This deforestation has been attributed to two human activities : a
traditional of shifting cultivation or slash and burn farming, and logging without reforestation. Remote sensing and GIS
are the most modern technologies which have been widely used in the field of natural resource management and
monitoring. These technologies provide very powerful tools to observe and collect information on natural resources
and dynamic phenomenon on the earth surface, and ability to integrate different data and present data in different formats.
In this study, using forest cover map and Landsat 7 ETM data, we analyze and compare forest cover change from
1997 to 2002. And the maximum likelihood method of supervised classification was used to classify the remote
sensing data, we processed Spectral Enhancement, including Normalized Difference Vegetation Index (NDVI) ,and
re-classify data again base on Principle Components Analysis (PCA) and NDVI.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854W (2008) https://doi.org/10.1117/12.816018
With the deterioration of water pollution, monitoring of water environment is becoming more and more urgent.
However, there is no professional water environmental monitoring system in China. To overcome these problems, we
have developed a Surface water environmental monitoring System (WATERS for short) by VISUAL C++6.0 IDE.
WATERS is designed for the four kinds of remote sensing data of HJ-1 satellites, which are multi-spectral camera, ultraspectral
imager, infrared camera, and SAR. Besides, WATERS can also support other satellite remote sensing data. We
use some simulated HJ-1 satellites remote sensing data, as well as remote sensing data of similar satellite sensors, to test
the operation of WATERS. The operation results by these remote sensing data show that WATERS works well, and both
the efficiency and the precision of water quality monitoring are high.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854X (2008) https://doi.org/10.1117/12.816082
Recently, GPS has been more and more applicative in open pit mine slope safety monitoring. Daye Iron Mine open
pit high-steep slope automatic monitoring system mainly consists of three modules, namely, GPS data processing
module, monitoring and warning module, emergency plans module. According to the rock mass structural feature and the
side slope stability evaluation, it is arranged altogether to seven GPS distortion monitoring points on the sharp of Fault
F9 at Daye iron Mine, adopted the combination of monofrequent static GPS receiver and data-transmission radio to carry
on the observation, the data processing mainly uses three transect interpolation method to solve the questions of
discontinuity and Effectiveness in the data succession. According to the displacement monitoring data from 1990 to 1996
of Daye Iron Mine East Open Pit Shizi mountain Landslide A2, researching the displacement criterion, rate criterion,
acceleration criterion, creep curve tangent angle criterion etc of landslide failure, the result shows that the landslide A2 is
the lapse type crag nature landslide whose movement in three phases, namely creep stage, accelerated phase, destruction
stage. It is different of the failure criterion in different stages and different position that is at the rear, central, front
margin of the landslide. It has important guiding significance to put forward the comprehensive failure criterion of seven
new-settled monitoring points combining the slope deformation destruction and macroscopic evidence.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854Y (2008) https://doi.org/10.1117/12.812376
It is a widespread lack of data to support the assessments of hydropower cascade exploitation (HCE)
induced impacts over long periods. From 1977 to 2006, variations of land cover for successively eight dam
constructions were investigated by the application of RS data. The MSS and TM data were applied to
produce land cover maps in 1977 and 2006. In combination with data from national land cover database,
the data in these four years are applied to analyze land cover dynamics. The six first-level types land cover
change principles were concluded after calculation. The grassland was the most extensively converted type,
which reduced from 2162346 hato 2041691 ha. Other five categories land cover area increased during
HCE. Furthermore, the converted area was mapped out by transformation matrix analysis, which assess the
impact range for dam disturbances. The findings help future environmental impact prediction and improve
regional environmental management capabilities.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72854Z (2008) https://doi.org/10.1117/12.815788
In order to enhance the spectral characteristics of features for clustering, in the experiment of wetland extraction in
Sanjiang Plain, we use a series of approaches in preprocessing of the MODIS remote sensing data by considering
eliminating interference caused by other features. First, by analysis of the spectral characteristics of data, we choose a set
of multi-temporal and multi-spectral MODIS data in Sanjiang Plain for clustering. By building and applying mask, the
water areas and woodland vegetation can be eliminated from the image data. Second, by Enhanced Lee filtering and
Minimum Noise Fraction (MNF) transformation, the data can be denoised and the characteristics of wetland can be
enhanced obviously. After the preprocessing of data, the fuzzy c-means clustering algorithm optimized by particle
swarm algorithm (PSO-FCM) is utilized on the image data for the wetland extraction. The result of experiment shows
that the accuracy of wetland extraction by means of PSO-FCM algorithm is reasonable and effective.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728550 (2008) https://doi.org/10.1117/12.815822
The paddy rice is humanity's important crop. Jianghan plain is the important paddy rice planting area in China.
However, comparing with others, the study of paddy rice remote sensing is less in there. This study takes the MODIS
data from 2001 to 2007 as the main data resources, combines with the land use data, depends on the kind of paddy rice
growing periods, and extracts the paddy rice planting area. According to the test, the accuracy surpasses 85%. It attained
each various time average NDVI, EVI value by the each year various times paddy rice NDVI, EVI. Then this study takes
the grey system theory as a new method, and introduces it to the paddy rice remote sensing monitoring. Taking the paddy
rice yield per unit area as the referenced sequence and the each year various times paddy rice NDVI, EVI as the
comparative sequence, calculating the gray correction degree, finally the study selects the best time to remote sensing
monitoring for the paddy rice yield, and makes the yield estimation model.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728551 (2008) https://doi.org/10.1117/12.815860
Leaf area index (LAI) is one of the most important parameters of canopy structure as it related to many biophysical and
physiological processes, including photosynthesis, respiration, transpiration, carbon cycling, rain intercepting, net
primary productivity, energy exchanging etc. Rapid, accurate and reliable estimations of LAI are required in these
studies above. There are two main categories of procedures to estimate LAI: direct and indirect methods. The objective
of this study is to evaluate LAI estimations obtained by different methods in HeiHe River forest sites. These methods
include the LAI-2000 plant canopy analyzer, HemiView, fifty-seven degree photography method, fisheye photography
method, the tracing radiation and architecture of canopies (TRAC), and Multi-Purpose Canopy Observation System
(MCOS). HemiView shows a large variation on gap fraction measurements compared to LAI-2000, fifty-seven degree
photography method is the superior choice to provide initial LAI values compared to other methods. To determine the
non-photosynthesis elements and foliage clumping effects for optical methods, a new device named MCOS (Multi-
Purpose Canopy Observation System) and TRAC were used. Finally, the results show that with the combination of
MCOS or TRAC and LAI-2000 or hemispherical photography can provide accurate and efficient LAI values.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728552 (2008) https://doi.org/10.1117/12.815914
In order to improve the precision of phytoplankton chlorophyll-a (chla) concentration retrieval, this study classified the
data into two groups (the high and the low) by chla concentration with the threshold of 50μg·L-1. And then build the
statistical models for each group. Particularly, a modifying factor OSS/TSS was used to unmixing the spectra in the low
model to improve the low relationship between spectral reflectance and chla concentrations. As a result, the
concentration classification model allowed estimation of chla with a root mean square error (RMSE) of 21.12μg·L-1 and
the determination coefficient (R2) was 0.92, comparing with RMSE of chla estimation was 35.72μg·L-1 and R2=0.72 in
the traditional model. It shows that concentration classification is a helpful method for accurate remote chla retrieval in
eutrophic inland waters.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728553 (2008) https://doi.org/10.1117/12.815925
Spatial and temporal distributions of suspended sediment concentration (SSC) are greatly important for analyzing the
deposition and erosion variety of estuaries and evaluating the fluxes from river to sea. A model based on data in situ
measurements for estimating concentration of the suspended sediment with MODIS band 2 images are developed by
taking Yangtze River estuary as an experimental site in this study. Numerous field spectral measurements are carried out
in the Yangtze River estuary, and SSC are obtained concurrently. By analyzing the remote sensing reflectance (Rrs) and
SSC, we observed that Rrs increases with SSC and their correlation coefficient is beyond 0.8 at near-infrared
wavelengths (750-900nm). A linear relationship was established between SSC and Rrs at 858.5nm wavelength (the
middle point of 841-876nm wavelength). Compared to MODIS band 15, 16, 17 (resolution of 1km) data, the MODIS
band 2 (resolution of 250m) data is suitable to detect the horizontal distribution of suspended sediment in narrow
estuaries because of relatively high spatial resolution. The linear function is applied to corrected MODIS Terra band 2
data. As a result, the horizontal distribution of SSC is retrieved in the Yangtze River estuary. This study demonstrates
MODIS band 2 (250m) data provides data well suited for the study of suspended sediment in dynamic estuarine waters.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728554 (2008) https://doi.org/10.1117/12.815929
Sanjiang Plain was chosen as the study area in this paper, based on the relationship between species and their habitats,
using principles of landscape ecology and protection biology, "3S" technique, same surface areas of hexagons as
forecasting and evaluating units to analyze protection status of state protection wetlands birds and diversity of their
habitats, to find the unprotected biodiversity hotspots there and then analyze the priority protection. The study results
showed that nationally protected bird categories I, such as Ciconia boyciana and Haliaeetus albicilla have been protected
well, the area which protects in the protected occupies its distribution area 41.5% and 31.2%, simply has obtained the
very good protection. The Mergus squamatus, Grus japonensis and Aquila chrysaetos also occupy their always dispersal
area in the protectorate dispersal area above 20%, but their main distribution area not in protectorate, mainly is nature or
half natural ecosystem. Some birds under second class state protection as Bubo bubo, Falco peregrinus, Accipiter
gentilis, Falco tinnunculu, and Strix uralensis have not been well protected. Specially Bubo bubo, only protects its
dispersal area 0.6%, simply h as not obtained the very good protection. Looked from various ecosystem type that, the
typical meadow and the island forest to protect well, but the islands, the Reed marshesand the rivers ecosystem to
protect relatively bad. Thirteen hotspots have been discovered in this area, which are mainly distributed in surroundings
near nature reserve and coast of some great rivers.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728555 (2008) https://doi.org/10.1117/12.815940
Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images in 1988 and 2002 were used to
quantify the land use and land cover changes (LUCC) in Wuhan area using supervised classification method with a new
vegetation index based on universal pattern decomposition method (VIUPD). Land use dynamic index is also used to
analyze the temporal character and internal rule of number and construction of land use/land cover change. It shows that
the annual change ratio of different classification from 1988 to 2002 in Wuhan is -1.93% for river and lake, 4.86% for
breed water, 2.74% for construction, 0.58% for evergreen, 3.35% for deciduous, -1.08% for one harvest in one year farm,
-0.23% for multi-harvest in one year farm, 4.70% for other land use. And the formation and change mechanism of land
use/land cover in Wuhan is also analyzed systematically. It is found that the flat terrain of Wuhan provided a wide space
for land use expanding; the rapid increasing population accelerated the urbanization of the villages and towns nearby the
center city zone; and the economic benefit of land use made the change of different land cover.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728556 (2008) https://doi.org/10.1117/12.816075
Vegetation includes all plant communities that cover the earth surface. And vegetation cover is the most important
index to scale the status of the vegetation of the region, so the vegetation is the composition and the function body of
ecological system. Vegetation cover in different districts of Wuhan were calculated based on remote sensing images (TM
images and ETM+ images) in 1988, 1991, 1996 and 2002 by employing NDVI method for dimidiate pixel model, and
the vegetation cover maps of different periods were generated to analysis the temporal change of vegetation cover of
Wuhan area. The results showed that, the vegetation cover changed much from 1988-2002; the average vegetation cover
of the whole area was decreased from 58.41% to 50.45%, especially in Jiangxia district and the central district. From
1996 to 2002 is the period which vegetation cover decreased the most sharply in this period. From 1991 to 1996 the
vegetation cover was lightly increased in the whole study area. Analyzing spatial changing characteristics in the whole
study area we can see that, the whole area was in the decreasing moment, especially in Jiangxia district and the central
district, this was the result of urban development, and led to the huge development of the environment, worthy of all
aspects of attention.
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Shaogang Wang, Guojin He, Dingsheng Liu, Xiaoqin Wang
Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728557 (2008) https://doi.org/10.1117/12.813355
Digital Elevation Models (DEM) data (90mx90m) reflected by the NASA Shuttle Radar Topography Mission (SRTM)
are used as basic information source to overlay digital slope models and digital aspect models, which are applicable to
the mountainous terrain of astronomical solar radiation distributed model. This paper uses ray-tracing method and
integral by subparagraph to calculate the conditions of terrain shading information, and through an integral way to make
a visualization of monthly astronomical solar radiation (ASR). The result shows that the geographical and topographical
factors do visible effect to the spatial distribution of astronomical solar radiation over Wuyishan area, especially in
January, it does the most obvious effect to terrain shading, while in July it does the lightest effect to terrain shading. This
method can accurately reflect regional differences of solar radiation, and through accumulating daily solar radiation in
the region, we can obtain the total amount of solar radiation in every month of the year. This result can provide
prerequisite conditions as an important reference and then be useful to biomass estimating of vegetation, agricultural
production, climatic resources development and exploiture.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728558 (2008) https://doi.org/10.1117/12.813451
Unreasonable exploitation and administration of underground engineering are a great menace for people's lives and
properties. The traditional handmade safe administration can't meet the need of the modern development, which
will strongly accelerate the development of a dynamic, visual and interactive 3D administrative system. But present
GIS technology has its disadvantages in solving the 3D problems, which greatly restrict the application of GIS to the
underground engineering. This paper projects the surface safety visualization administration system of underground
engineering. It studies on the establishment and arithmetic of 3D spatial TIN side slice model, and puts forward a
mixture modeling method with the 3D spatial data of surveying and multilayer TIN side slice, and adopts point
cushion analysis with restriction conditions and fill-in arithmetic to realize the combination of graph and data. It
displays data from multi-dimensions, reveals the relations between data and analyzes the information behind the
data by visualization platform, and discusses the process of data collection, data analysis, data modeling,
topological modeling and three dimension deformation visualization based on a project in Tang Mei company of Zi
Xin Bureau of Coal in Hunan. and provides. It can provide the government and the related departments with an
alternate visualization platform for safety analysis and decision support.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728559 (2008) https://doi.org/10.1117/12.815597
This paper analyzed the features and limitations of several typical spatio-temporal data models. "spatio-temporal cube":
the main disadvantage is that the target change will produce great data redundancy when under non-consecutive
circumstances. "Snapshots": it repeatedly saves graphics and attribute of no changes which resulted in waste of storage
spaces, and it is impossible to reflect space objects under the same domain and the relationship between the attributes.
"Base State with Amendments": merely modify changing object, but it's not suitable for continuous variation space
object. "space-frame composite": currently, the model is lacking of sound framework structure and application model.
"Object-oriented spatio-temporal model": The modeling concept, theoretical foundation and technical realization has not
yet reached a consensus, it's not mature enough.
In allusion to the features of the spatial database of water and soil loss, this essay expounded the characteristics of spatiotemporal
databases. Spatial features in many practical circumstances ( such as thematic maps in soil and water
conservation projects and space elements of soil erosion distribution map) have spatial data features, and also change
with time, consequently, required us to establish spatio-temporal database, STDB, which can capture time data and space
data at the same time. This analysis based on "ArcSDE versioning mechanisms" temporal and spatial database
implement technologies, discussed the construction methods, process and data features of the database, and introduced
the implementation of historical data rebuilding and version merging.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855A (2008) https://doi.org/10.1117/12.815716
Global brightness temperature simulations were performed at 0.25 degree resolution both including the atmospheric
effect and pixel heterogeneity in wide wave band. For surfaces such as snow, deserts, and vegetation, volumetric
scattering was calculated using a two-stream radiative transfer approximation. The reflection and transmission at the
surface-air interface and lower boundary were derived by modifying the Frenel equations and QP model to account for
cross-polarization. Several models were utilized to compute the optical parameters for the medium. Global Land Data
Assimilation Systems (GLDAS) provided time series of the main input variables. These simulations were compared with
Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) measurements in January, April, July,
and September 2003, including both the spectral and temporal variations. A sensitivity study was also carried out to
access the relative contributes of the main parameters (particularly the roughness and soil moisture). Difference between
simulated and measured TBs were analyzed, discriminating possible issues either linked to the radiative transfer model
or due to land surface parameters .
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855B (2008) https://doi.org/10.1117/12.812413
The urban heat island (UHI) refers to the temperature rise of any man-made area, which can make it distinctively
protrude as a 'warm island' among the 'cool sea' that the lower temperature of their natural landscape represents. This
paper focuses on the monitoring of UHI effect with seasonal change using Advance Spaceborne Thermal Emission and
Reflection Radiometer (ASTER) data which is onboard the satellite Terra. Our study area is in central urban area of
Beijing within fifth ring road. The ASTER data on January, 27, April 9, June 4, August 31, 2004 in daytime were
collected and regarded as winter, spring, summer, and autumn respectively. In order to calculate the urban heat island
intensity, the land surface temperatures were retrieved using an iterative way to compare the temperature difference
between the urban and surrounding rural area. Some pre-processing procedures such as geometric rectification,
radiometric correction, delineating and masking of features, and land cover classification should be performed using
satellite images before calculating the UHI. The UHI was divided into normal, weak, strong, very strong, severe and
extreme based on the calculated UHI intensity. Our result indicates that the UHI effect is weak, strong and extreme in
sprint, summer and autumn respectively, and in winter, the central urban area of Beijing is in an urban heat sink. It means
that the UHI effect is different with the seasonal change.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855C (2008) https://doi.org/10.1117/12.815262
Interferometric Synthetic Aperture Radar (InSAR) magtitude map, extracted from Differential- Interferometric
Syntheric Aperture Radar (D-InSAR) technology, has a low-resolution, so it has a certain limitation to the explanation
and analysis of subsiding area. In order to solve the problem of lacking enough spatial information of D-InSAR image, in
this essay we take a data fusion between D-InSAR image and high resolution Remote Sensing (RS) image, obtaining an
image containing subsiding information and high-resolution spatial information. This paper mainly focuses on the study
of a Mag-Phase algorithm (MPH) algorithm and other fusion algorithms including Hue-Intensity-Saturation (HIS)
transformation, Principal Component Analysis (PCA) transformation, Product fusion, Ratio fusion, Wavelet fusion for
magtitude map and deformation map, and we take the deformation map and panchromatic (PAN) image of Enhanced
Thematic Mapper + (ETM+) (magtitude map) of Xi'an area as an example to do data fusion according to the algorithms
above. At last, a comprehensive evaluation and analysis for fusion images is made with subjective and objective
evaluation criteria, and a conclusion that MPH fusion algorithm is better than others is also obtained.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855D (2008) https://doi.org/10.1117/12.815354
The base land value evaluation plays an important role in urban land value system for a long time. To establish a simple
and feasible method to evaluate the urban land value is always the target for scholars. According to the traditional
method of base land value evaluation, combining the theory of K-means clustering and trend surface analysis, this paper
proposes a new method for base land value evaluation, which fully considers the spatial correlation, inherent similarity
and regional continuity of the land value samples. Additionally, in this method, we propose some measurement indices of
evaluation results, which are wanting in traditional methods. At last, we evaluate the industry land value in Shanghai
with this method for instance.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855E (2008) https://doi.org/10.1117/12.815527
This paper studies on urban fire station layout planning based on GIS. Compared and analyzed the results of traditional
method and the method based on road network and service area in GIS. Paper indicated the shortcoming of traditional
model used in planning, and proposed a new method based on GIS service area analysis model for improving the layout
of fire stations in order to without or reduce the blind spots and overlapping. In the end, on the basis of the analysis result
and the actual cases study, an optimized adjustment scheme is proposed.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855F (2008) https://doi.org/10.1117/12.815602
One Landsat5 TM image of 1993/6/15 and one Landsat7 ETM+ image of 2001/5/12 about Tianjin whose path/row are
both122/33 have been used for this study. An integrated RS and GIS approach is presented for change detection. Based
on summarizing the methods of change detection and analyzing the disadvantages of traditional approaches, multivariate
alteration detection based on the canonical correlation analysis is introduced. Firstly, canonical transform is adopted for
the preprocessed images. Then, the sixth component containing the maximal change message is processed and the
change message is extractd. Moreover, the binary image is vectorized and the vectorized maps are overlapped with the
original images separately. So the change about two time phases is compared. Subsequently, the database is established
based on the basic space data such as road maps and maps showing present condition of land utilization and urban
planning maps as well as humane and socio-economic data. The results rooting in the image change detection are entered
into GIS by vectorization and spatial overlay analyzed with already existent data. Finally, the urban built-up area is
extracted and the validated precision is high. The urban expansion areas and dynamic change characteristic and reasons
in Tianjin from 1993 to 2001 have been revealed and discussed. Comparing with the Tianjin city master planning
(1996-2010), it shows that urban expansion change is coincident with urban planning implementation.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855G (2008) https://doi.org/10.1117/12.815753
In recent decades, research on survey for urban planning has become an important issue. Monitoring the nature condition
of urban is an important precondition for urban planning. This paper integrates Geographical Information System (GIS)
and remote sensing (RS) to study land use/cover change and urbanization trends in Hangzhou urban area from 1976 to
2005. The study explores the temporal and spatial characteristics of urban expansion and land use/cover change from
1976 to 2005. The remotely detected land use/cover change shows that the land use/cover was largely changed.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855H (2008) https://doi.org/10.1117/12.815911
Impervious surfaces (IS), as one of the most important land cover types and characteristic of
urban/suburban1 environments, are known to effect urban surface temperatures by altering the sensible
and latent heat fluxes. This study examined the effect IS spatial patterns have on land surface
temperature (LST) in Wuhan, China. LST were retrieved from the corrected TIR band (10.4~12.5μm)
of Landsat images using Single-Channel method. IS distribution, together with vegetation and soil
distribution, was estimated through a fully constrained linear spectral mixture model. Four
endmembers, vegetation, soil, low albedo, and high albedo were selected to model heterogeneous
urban land cover. Impervious surface fraction was estimated by analyzing low and high albedo
endmembers. Correlation analyses were conducted to investigate the changing relationship of LST with
impervious surface. The result indicated there was a strongly positive relationship (r2>0.85) between
LST and percent impervious surface for all seasons, which suggested the variations in LST could be
accounted for very well by percent impervious surface.
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Proceedings Volume International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72855I (2008) https://doi.org/10.1117/12.815931
The paper took TM/ETM+ Landsat images in the year of 1986, 1995, 2000, 2001, 2002 and 2003 as the main
information sources and the scopes of Chongqing's construction land during each period were extracted automatically
and accurately. The space-time expanding of construction in Chongqing city for the past 20 years was monitored. And
then, the motive force mechanism was analyzed combining topographical information data and social economic statistics.
The result indicates: Although slope was the limited factor of urban expansion, there was no obvious correlativity with
expanding rate in certain ranges. the slope played role to development of city only within a certain period. Expansion
rate (y ) of construction land and the population growth rate (x ) present the relation of y = 1.8234x + 0.0763; The area
(y ) of the construction land in Chongqing city has close relation with the per capita gross national product (x ) with
coefficient correlation up to 0.9878, and they have a mathematical relation of y = 0.03x3-0.6852x2+34.987x+0.015 on
number value.
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