The fusion of panchromatic image and multispectral image is one of the significant issues in the application of remote
sensing , by which it can integrate multispectral and panchromatic images with their respective strengths to compress the
data size and improve data utilization. In this paper, an IHS (Intensity-Hue-Saturation) image fusion method is presented
based on Bidimensional Empirical Mode Decomposition (BEMD).Firstly, multispectral image is transformed form the
RGB color space to HIS color space, then I component and panchromatic image are carried out decomposition
respectively using BEMD method. The intrinsic mode surface of decomposed panchromatic image is used to replace that
of decomposed I component. Finally the image is transformed back to original RGB color space from IHS color space,
achieving the image fusion. The experiment shows that the new image fusion method is superior to the traditional
methods.
In this paper, the feature selection rules of patches were regarded as the breakthrough point, based on data analysis and
experiments, the computing method of area balance control of land types was put forward in order to solve the problem
of area changes of every land type before and after synthesis. The computing method of area balance control of land
types can be used not only to check up the rationality of rules before cartographic generalization, but also to provide
assistance advice for revising feature selection rules according to the requirement of the synthesized results. It is helpful
to enhance the rationality and reliability of synthetic rules, to achieve the area balance of various land types before and
after it is synthesized, and to guarantee the quality of the diagram.
KEYWORDS: Geographic information systems, Spatial analysis, Data modeling, Data mining, Visual system, Detection and tracking algorithms, Systems modeling, Geography, Distance measurement, Solids
With the widespread use of spatial data technologies, enormous and complex spatial data have been accumulated, thus
the traditional GIS (Geographic Information Systems) spatial analysis methods are confronted with great challenges.
Therefore, we need a new spatial analysis method of data-driven rather than model-driven, exploratory rather than
reasoning. Spatial clustering, which groups similar spatial objects into classes such that the intra-cluster similarity is
maximized and the inter-cluster similarity is minimized, is an important method of spatial data mining [1].
In the article, by virtue of Delaunay diagram, we propose a spatial clustering algorithm, which incorporates spatial
relationships with non-spatial attribute. Then the objects whose characters are less obvious are classified into clusters
that are more obvious and the precondition is that they are neighbouring, namely they must share the same Delaunay
edge. Along with rescaling, the same spatial object presents different states of distribution. We show via experiment of a
synthetic data set that our algorithm can integrate spatial relationships and non-spatial attribute. The obtained clustering
result is highly consistent with that perceived by human eyes and is capable of recognizing clusters of arbitrary shape.
KEYWORDS: Databases, Control systems, Geographic information systems, Data communications, Web services, Telecommunications, Computing systems, Decision support systems, Local area networks, 3D modeling
Forest is a finite resource and fire prevention is crucial work. However, once a forest fire or accident occurs, timely and
effective fire-fighting is the only necessary measure. The aim of this research is to build a computerized command
control system based on WEBGIS to direct fire-fighting. Firstly, this paper introduces the total technique flow and
functional modules of the system. Secondly, this paper analyses the key techniques for building the system, and they are
data obtaining, data organizing & management, architecture of WebGIS and sharing & interoperation technique. In the
end, this paper demonstrates the on line martial symbol editing function to show the running result of system. The
practical application of this system showed that it played very important role in the forest fire fighting work. In addition,
this paper proposes some strategic recommendations for the further development of the system.
KEYWORDS: Geographic information systems, Data modeling, Databases, Web services, Integration, Spatial analysis, Software development, Agriculture, Computing systems, Systems modeling
How to deal with the relationship between GIS and normal management system is one of the most frequent problems that the developers meet when they are developing application system by using GIS. The reason is: the users have already had their own database or management information system before GIS, and the GIS developers always put all of the exiting data into the management of GIS but they always concentrated on GIS without concerning the different levels of the users. But, because the database function of many GIS softwares is very weak, it is difficult to achieve the task of managing normal database, which created some difficulties for developing the system. In addition, only a few functions of GIS have been used, even if all the exiting data have been put into GIS management. As a result, the cost of developing increased. Focusing on this problem, the authors proposed three developing models which combined management system with the advantages of GIS and based on analyzing users' demand in this paper. The authors also introduced the key techniques during developing this kind of application system in this paper.
Principles of colour science have been widely used in applications of remote sensing, but few papers have reported the quantitative application of color principles in the processing of multi-spectral remote sensing images. in this paper, authors have developed a colour difference technique for the classification of multi-spectral remote sensing image according to the principles of colour science. it is demonstrated that the colour difference technique can be used in the classification of IKONOS multi-spectral remote sensing image, the results of image classification are correspond to human eye 's interpretation very well. in addition, the colour difference classification technique is very sensible to chromatic information in the multi-spectral remote sensing image, but has a luminance latitude. Therefore, the colour difference classification technique seems very adaptable to the classification ofuneven irradiance multi-spectral remote sensing image.
There are abundant metallic mineral resources on the sea floor, polymetallic nodule is an important one of them. A polymetallic nodule ore includes nickel, copper and manganese elements, etc. So the polymetallic nodule is very important and precious to industry. In order to know the distribution and reserves in the west and east pacific areas, a deep-tow optic system is imported from U.S. to acquire deep sea-floor images. Processing the images, we can extract some information and calculate some parameters: coverage, grain size and abundance, which stand for distribution and reserves of the polymetallic nodule. In the paper, features of the deep sea-floor image are analyzed, considering the characters, a processing procedure for the deep sea-floor pictures is presented. Methods are presented to rectify radiative uneven and geometric distortions, at last, the correlations of coverage, abundance and grain size are analyzed and the formulas for computing abundance are respectively derived from that.
This paper describes the use of semivariogram as a parameter for image comparison which is a commonly used method in content-based image retrieval. The authors first review various applications of spatial statistics to image and signal processing, and recent literature of image comparison, with the emphasis to global image structure description and distance-based image retrieval techniques. The difficulty arising in this field is the definition of image similarity. A new parameter based on semivariogram is putted forward by the authors. Bearing in mind that semivariogram is a parameter not only describes the global structure of a data set but also describes the local continuity of that data set, it is shown in the paper that semivariogram is suitable for global image comparison, and can be used to reveal local features of the image as well. Based on this property, a new index for image similarity is constructed and a practical program using it is developed. By applying the approach to a practical problem, the results show that this approach has the following merits: (a) high sensitivity to structure differences of an image. (b) low computational complexity, and (c) high robustness to lightening conditions.
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