This PDF file contains the front matter associated with SPIE Proceedings Volume 6753, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committees listing.

In recent years, some methods are available for multi-scale databases, for example, Reactive-tree, BLG-tree and GAP tree. However, these methods paid more attention to the multi-scale data structure rather than map generalization knowledge rules. This paper makes an attempt dealing with the integration of multi-scale data structure model and thematic generalization knowledge rules for land use area partitioning map (Terra-type parcels). Inheriting the idea of GAP-tree, the MAPL-tree (Multi-scale data structure for Area Partitioning map of Land use) is built for describing the generalization process of the terra-type parcels. The MAPL-tree is suited for different scale retrieval. Some generalization rules are discussed for landuse area partitioning map, especially for semantic-based merging rules. Based on MAPL-tree and merging knowledge rules, this paper develops a progressive display prototype system. In the last part, we conclude the paper and our further research.

When modeling spatio-temporal applications, the spatial, temporal but also spatio-temporal aspects like change or motion have to be expressed (Brisaboa, N.R., 1998). For spatio-temporal object (ST-Object), it's necessary to store its correlation link which can be used to track an object's various states over time easily. In this paper, we propose a solution based on spatio-temporal data model to resolve how to detect ST-Object's various states over time and build correlation link and correlation tree into database for different temporal. DLG (Digital Line Graphic) source data of the same area interested.

This paper proposed RHIG: R+ tree-based Holistic Index of GML after sufficiently extracting character of GML spatial data and analyses of traditional spatial and XML index technology. RHIG possesses following characters: Fully utilizing structure information in schema, RHIG encode both schema document and GML document, which enable each element in GML document take relevant schema structure information and thus enhance efficiency of GML attribute querying; support simultaneously indexing and querying on both non-spatial and spatial information contained in GML document; RHIG could be stored in relational database to avoid repeatedly construct index. Experiment substantiates usability and generality of this index approach.

Query processing of XML data stream is one of the hottest issues in database research area. However, most of the popular methods on processing the XML data stream can not handle the continuous query which contains spatial-temporal queries. While the tremendous increase in the use of road-side sensors in transportation application area, the transportation data information gathered as data stream are pervasive. Deploy a processor specifically for continuous query on dynamic transportation information is important. In this paper, we present a continuous query method on processing dynamic transportation information modeled by XML/GML. It first explores how the spatial-temporal aspect of dynamic transportation information can be described by XML/GML document, and then proposes a simple method on incorporating the spatial-temporal functions into the commercial XQuery engine. Furthermore, we integrate the extended XQuery engine with the SAX processor to handle the spatial-temporal queries on XML data stream. How the method can be used in querying the transportation data stream is also given at the end.

With increasing demands of GIS applications system in a complex, integrated, and other areas, the spatial data are required rapid growth for the systems, and users are more and more on the demand spatial data. The method which traditional documents express spatial data is obviously unable to meet these needs. The SDE is at present the widespread application intermediate technology in the system integration, and is one kind of realization in the spatial database application. The spatial data can be expressed by vector data structure and raster one which may be managed thought ArcSDE. In this paper, regarding ArcSDE as the space data engine and using the large-scale relation database (RDBMS), we has set up three layers system structure, realized the effective organization and management to spatial data, and gotten very good application in practice.

Spatial index is one of the key techniques in the field of spatial database. This paper presents a brand-new node-choosing algorithm in the insertion procedure of R-tree spatial index, which is very different from the current algorithms. From the beginning of the leaf-node layer, firstly from bottom to top then inversely, the proper leaf-node is chosen, and this scheme can solve the problems caused by node overlapping. Meantime, the concept of Rtree_Cauchy is firstly put forward, and the sum of overlay, overlap and Rtree_Cauchy is introduced as selection criterion to guarantee that shape of node is average and avoid generating long-strip-shape nodes. A comparative performance analysis on the current and improved methods shows that not only the query performance but also the generation performance of the improved method is higher than the current methods such as R*-tree.

This paper analyses the human's cognitive process of nature at first, then establishes the hierarchical framework of theoretical research to geographical information sharing, takes spatial cognition theory and information communication theory, geographical spatial conception, geographical data model and standardization of geographical information for essential contents, expatiates each theory finally.

With the increasing application of geographic information system (GIS), GIS is faced with the difficulty of efficient management and comprehensive application of the spatial information from different resources and in different forms. In order to solve these problems, ontology is introduced into GIS field as a concept model which can represent object on semantic and knowledge level. Ontology not only can describe spatial data more easily understood by computers in semantic encoding method, but also can integrate geographical data from different sources and in different forms for reasoning. In this paper, a geo-ontology "GeographicalSpace" is built with Web Ontology Language (OWL) after analyzing the research and application of geo-ontology. A geo-ontology reasoning framework is put forward in which three layers are designed. The three layers are presentation layer, semantic service layer and spatial application server layer. By using the geo-ontology repository module and reasoning module in this framework, some more complex spatial location relationships in depth can be mined out. At last, an experiment is designed to demonstrate geo-ontology's ability to execute more intelligent query that can't be implemented in traditional GIS.

In this paper, the concept of pseudo-3D visualization in mobile GIS is firstly defined, then a pseudo-3D visualization model is proposed and a simplified pseudo-3D projection transformation algorithm of building pseudo-3D map based on existed 2D vector data is designed. Furthermore the spatial data organizing and processing principles regard to limited hardware and software resources of mobile devices are introduced. To show the stereo vision effect of geographical scenes smoothly, preprocessing measures of pseudo-3D visualization and necessary 3D scene enhancement technology are applied. Finally, an agisNavigator project is implemented with the pseudo-3D visualization technology based on 2D vector spatial data in PocketPC and some experiment results are presented and analyzed.

Spatial dynamic prediction in GIS is the process of spatial calculation that infers the thematic maps in future according to the historical thematic maps, and it is space-time calculation from map to map. There is great application value that spatial dynamic prediction applied to the land planning, urban land-use planning and town planning, but there is some imperfect in method and technique at present. The main technical difficulty is excavation and expression of spatial state conversion rule. In allusion to the deficiency in spatial dynamic prediction using CA, the method which excavated spatial state conversion rule based on spatial data mining was put forward. Stochastic simulation mechanism was put into the prediction calculating based on state conversion rule. The result of prediction was more rational and the relation between the prediction steps and the time course was clearer. The method was applied to prediction of spatial structure change of urban land-use in Jinan. The Urban land-use change maps were predicted in 2006 and 2010 by using the land-use maps in 1998 and 2002. The result of this test was rational by analyzing.

Using GIS, network and database technologies, Beijing underground pipeline information system is established. After detailed analysis of the actuality and specialty of the present underground pipeline database managed by Beijing Institute of Surveying and Mapping (BISM), the paper systematically presents the studying purpose, meanings and primary contents. According to the study of pipeline data features, a spatio-temporal pipeline database classified by pipeline types is built. Based on the database, the urban underground pipeline information system is designed and developed by BISM, which unifies data from planning department and other departments, realizing modernized managements of underground pipeline data input, management, analysis and output.

The core of geographic information visualization is map making, which is characterized by the map maker usually being the map user. Potential map makers are becoming more and more, most of them are deficient in the knowledge background of cartography. It is necessary for them to derive popular map design knowledge from the complex map theories and methods to guide the practice of geographic information visualization. As an exploration into methodology, this paper has initially probed into and formed the conceptual model of geographic information visualization duality with dualistic analysis as the basic method, in the hope of establishing a framework which is easy to understand and to follow as a "map-making guide". The paper firstly expounds the theoretical basis of dualism from such aspects as geography, linguistics and philosophy; then elaborates the object matter of the methodology of dualism in geographic information visualization by developing from such two aspects as the signifier and the signified of geographic information visualization, with the semiotic linguistics as the paradigm; and finally draws a conclusion. Studies show that: the geographic information and the map design are of duality each other; the duality model of geographic information visualization is "easily understand" and "easily follow".

Spatial data mining and knowledge discovery (SDMKD) and remote sensing knowledge representation (KR) are important for the realization of intelligent and automatic image processing, so the mechanisms of knowledge acquisition, utilization, representation and storage are worthy of being researched. In this paper, an object-oriented image analysis (OOIA) is discussed and its knowledge will be summarized. Based on the object-oriented image analysis, a method of object-oriented knowledge representation and storage in XML will be proposed and the way to acquire and utilize knowledge in image analysis will also be described in a typical practice. Based on principle proposed, the authors implemented a prototype system and obtained expected results in extensive experiments.

Neither Random nor stratified sampling can reflect the Dependence among land-price monitoring. Hence, based on Semi-variogram and analysising the anisotropy of different sites of land-price, some useful references are provided. Systematic unaligned sampling with a grid cell size of 1000×500 m was chosen on the basis of semi-variogram analysis, and the length of side is equal to 1/2 of range. At last, part region of the Changzhou city is selected as a study area to examine this method.

To make the diverse organizations access the massive distributed heterogeneous spatial data easily, we build a Spatial Data Grid in peer-to-peer way, which composed of several spatial datacenters distributed in different agencies. Given a query, which often a range query in spatial application, the query parser will decompose the global query into several sub-queries and disseminate them to the peers who take responsibility for storing data of that area. In order to accelerate the query dissemination process, we utilize distributed index to locate object more quickly and accurately. We propose an adaptive indexing mechanism, Fully Distributed R-Tree Index, which is appropriate for efficient range query dissemination. It composes of two layers, on top of which is the spatial range of each peer. The under layer stores part of the R-Tree of each peer's neighbors, which can be adjusted according to the capacity of peer. There is no centralized control on top of the entire system, and it could adaptive to the environment change.

A framework to express the changes and the causalities within the object's evolution is proposed based on a general inspection of the interactions among the Spatiotemporal Objects (STOs). Why the STOs can evolve is that they can exchange the material, the energy and the information mutually. The result of their evolution is the changes of their features and mechanism. Feature changes can be categorized into 2 levels: the changes of the feature statuses and the changes of the feature structures. The former result in just the increment of the data quantity of the database, the later can furthermore result in the increment of data structures defined in the database. Any a change of a STO is caused directly by a behavior of either itself or another STO. Feature changes can be directly expressed by spatiotemporal data or data structure, but the mechanism changes of a STO can only be indirectly reflected by its feature and behavior description. The proposed framework consists of five key elements: the essence, the features, and the behaviors of the STO, the information flow and the material flow within the spatiotemporal interactive process.

GIS data can be updated using the larger scale GIS data based on map generalization. Matching is a critical first step for extracting updates in this process. This paper presents an approach for road data matching based on level analysis. Matches of objects between road networks are divided into three levels, i.e. decomposed level, basic level and abstracted level. The matching of edge end point as the decomposed level, the node matching as the basic level, and the route matching and between node and edge matching as the abstracted level are discovered. Based on the order relationship of three matching levels and the interdependent among them, matches of objects are accomplished by a set of algorithms developed. Meanwhile during this process, the exceptional matching can be as the index for manual checking to improve the matching accuracy. Matches of objects meet the requirement for searching data unmatched. The experiment results of matching road data at 1:10,000 and 1:50,000 show higher matching accuracy.

Traditionally, the description of the scale of geographical information is mainly concerned with spatiality and its temporal character and semantic character is ignored. With a few of new techniques and way such as 3D geographical information system, temporal geographical information system, virtual geographical environment, electronic map appears, the traditional description of scale of geographical information shows its deficiencies to make certain of every aspect of it. At first, in this paper we try to extend the connotation and the dimension of scale of geographical information to full the need of describing the every aspects of it, and give three-tiered conceptualization of its scale as: kinds of scale; dimensions of scale; components of scale. The dimension of scale of geographical information is consisted of spatial dimension, temporal dimension and semantic dimension. The classifications of scale of geographical information are of phenomena scale, measure scale and token scale. The components of scale of geographical information are of extension, granularity (resolution) and interval. It is through the Cartesian product of kinds of scale and components of scale can we define the particulars of every aspects of scale of geographical information. At last in this paper the transform of scale of geographical information and issue of scale choice is discussed.

With the integration of geo-visualization theory and data mining technology, this paper uses geo-visualization assisted association mining method to discover, extract and express the potential spatial distribution relations among census data and other related socio-economic statistical data by using data mining technology. The paper accomplishes the association rules for mining process based a newly constructed knowledge database framework, and the knowledge based geo-visualization method for further researches and decision making.

Since the last decade of the past century, GIS has being applied in more and more fields. With the development of the technique, more and more people pay attention to the factor of time, i.e. the new GIS system should be able to analyze spatio-temporal factors in the real world. This paper presents a research project suggesting the use of spatio-temporal techniques as navigation aid onboard ships. Firstly, we analyze the differences of change between the oceanic elements and the land elements. Secondly, we set up a conception system of navigable area. Thirdly, we build up some related mathematical models to take a numerical research, the models are the instantaneous water level model, the triangulation model of soundings, the navigable area creating model and so on. Lastly, by the research, we come to a conclusion that the spatial data includes a lot of information, some of them are well-marked and the others are connotative, by digging the connotative information, some new functions may be developed.

Land-use pattern is spatially correlated and scale-dependent, so doing research on land-use pattern based on raster format data requires making clear how to scale the data and which grain domain is suitable for scaling. The major objective of this study was to explore whether the landscape metrics and spatial autocorrelation index-Moran's I can detect the grain effect of land-use spatial pattern. At first three kinds of scaling methods were carried on the original data to get multi-resolutions images. After comparing several statistics, the better results were interpreted to multi-grains land-use maps. Twenty-three landscape metrics and Moran's I were performed on these maps. Only a few indices were chosen to help delimiting the appropriate grain domain in which the majority of grain-sensitive indices were stable and can be extrapolated or interpolated across spatial grains. The results showed that landscape metrics were grain dependent and could be categorized into three types: regular changing type with obvious inflexions-AI, FRAC_AM, LPI, SPLIT, DIVISION, SHDI, SIDI, MSIDI, SHEI, SIEI and MSIEI; regular changing type without obvious inflexions-NP, PD, LSI, PARA_AM, PARA_MN, PLADJ; unpredictable changing or no changing type-TA, PAFBAC, CONTAG, SHAPE_AM, SHAPE_MN and FRAC_MN. Only the first type was suitable to detect the grain effects of the land-use spatial pattern. Then correlation analysis was performed on these metrics and FRAC_AM, DIVISION and SHDI were picked out as representatives to decide the appropriate grain domain cooperated with Moran's I. This study highlights the need for multi-grain analysis in order to adequately characterize and monitor land-use spatial pattern characteristics, and provides insights into the scaling of land-use spatial pattern.

R is an open source (GPL) language and environment for spatial analysis, statistical computing and graphics which provides a wide variety of statistical and graphical techniques, and is highly extensible. In the Open Source environment it plays an important role in doing spatial analysis. So, to implement spatial analysis in the Open Source environment which we called the Open Source geocomputation is using the R data analysis language integrated with GRASS GIS and MySQL or PostgreSQL. This paper explains the architecture of the Open Source GIS environment and emphasizes the role R plays in the aspect of spatial analysis. Furthermore, one apt illustration of the functions of R is given in this paper through the project of constructing CZPGIS (Cheng Zhou Population GIS) supported by Changzhou Government, China. In this project we use R to implement the geostatistics in the Open Source GIS environment to evaluate the spatial correlation of land price and estimate it by Kriging Interpolation. We also use R integrated with MapServer and php to show how R and other Open Source software cooperate with each other in WebGIS environment, which represents the advantages of using R to implement spatial analysis in Open Source GIS environment. And in the end, we points out that the packages for spatial analysis in R is still scattered and the limited memory is still a bottleneck when large sum of clients connect at the same time. Therefore further work is to group the extensive packages in order or design normative packages and make R cooperate better with other commercial software such as ArcIMS. Also we look forward to developing packages for land price evaluation.

An improved fractal measurement, the weighted radial dimension, is put forward for highway transportation networks distribution. The radial dimension (DL), originated from subway investigation in Stuttgart, is a fractal measurement for transportation systems under ideal assumption considering all the network lines to be homogeneous curves, ignoring the difference on spatial structure, quality and level, especially the highway networks. Considering these defects of radial dimension, an improved fractal measurement called weighted radial dimension (D_WL) is introduced and the transportation system in Guangdong province is studied in detail using this novel method. Weighted radial dimensions are measured and calculated, and the spatial structure, intensity and connectivity of transportation networks are discussed in Guangdong province and the four sub-areas: the Pearl River Delta area, the East Costal area, the West Costal area and the Northern Guangdong area. In Guangdong province, the fractal spatial pattern characteristics of transportation system vary remarkably: it is the highest in the Pearl River Delta area, moderate in Costal area and lowest in the Northern Guangdong area. With the Pearl River Delta area as the centre, the weighted radial dimensions decrease with the distance increasing, while the decline level is smaller in the costal area and greater in the Northern Guangdong province. By analysis of the conic of highway density, it is recognized that the density decrease with the distance increasing from the calculation centre (Guangzhou), demonstrating the same trend as weighted radial dimensions shown. Evidently, the improved fractal measurement, weighted radial dimension, is an indictor describing the characteristics of highway transportation system more effectively and accurately.

Traffic location is one of the most important factors which affect the development of rural settlements. However, there is no effective method to evaluation traffic location of rural settlements at present. Focusing on large numbers of scattered rural settlements with complicated and fragmentized traffic networks, a weighted euclidean distance method for rural settlements traffic location evaluation is put forward in this paper. In order to differentiate the affection that different levels of roads put on rural settlements, roads are sorted into two classes: the level-roads (such as national and provincial roads, county and town roads) and the village-roads. Then the total quantized value of traffic location of rural settlements, obtained by weighing traffic location quantized values on different road levels, was calculated by GIS spatial analysis module. This method was put into practice to analyze the traffic location of Tonglu County, Zhejiang Province, which showed that it has obtained a fairly good result on the evaluation of the traffic location of rural settlements.

Recently, many extended database languages have been designed for handling spatial data. However, most research is limited to compute and manage discrete data. Little remarkable work has been done on the query processing for field data, especially on the management and querying temporal continuous field data using the databases technology. A method of representation and computation of continuous fields is introduced and a spatio-temporal query language for continuous field model data CFQL through object-relational database technology is proposed to manage and query continuous data. Examples of Field data management using CFQL are described.

The LOD technology has an impact upon the multi-scale representation of spatial database. This paper takes advantage of LOD technology to express the multi-scale geographical data, and establish the exchange of multi-scale electronic map, further attain the goal that the details of geographic features such as point, line and polygon can be displayed more and more clearly with the display scale being enlarged to be convenient for the personnel of all offices of industry and commerce administration to label the locations of the corporations or enterprises.

Geographic data should be described by spatial, temporal and attribute components, but the spatio-temporal queries are difficult to be answered within current GIS. This paper describes research into the development and application of spatio-temporal data management system based upon GeoWindows GIS software platform which was developed by Chinese Academy of Surveying and Mapping (CASM). Faced the current and practical requirements of spatial information application, and based on existing GIS platform, one kind of spatio-temporal data model which integrates vector and grid data together was established firstly. Secondly, we solved out the key technique of building temporal data topology, successfully developed a suit of spatio-temporal database management system adopting object-oriented methods. The system provides the temporal data collection, data storage, data management and data display and query functions. Finally, as a case study, we explored the application of spatio-temporal data management system with the administrative region data of multi-history periods of China as the basic data. With all the efforts above, the GIS capacity of management and manipulation in aspect of time and attribute of GIS has been enhanced, and technical reference has been provided for the further development of temporal geographic information system (TGIS).

Time and space are ubiquitous aspects of reality. The spatio-temporal data is our cognition to external matter and the spatio-temporal data model is the theoretical foundation to manage the spatio-temporal data. But now the research of the spatio-temporal data model still is on the stage of theoretical research and can not implement the real application. Those how to uniformly manage the Spatio-Temporal multi-data source and different structure data and how to implement the Spatio-Temporal data model practically need to be crucially solved. We use the principle and the construction idea of the data engine for reference, build the spatio-temporal data engine by applying the notion and function of the data engine into the theory of the Spatio-Temporal data model and then use the Spatio-Temporal data engine to implement the application of the spatio-temporal data. The article mainly introduces the construction idea, the design, the implement of the spatio-temporal data engine and provides the example of using the spatio engine--ArcSDE to implement the application of the spatio-temporal data which explains our thinking of implementing the spatio-temporal data engine. The article is an attempt to resolve how to effectively and uniformly manage the Spatio-Temporal multi-data source and how to make the Spatio-Temporal data used in practice.

In this paper we present preliminary results and lessons learned in an effort to design an automatic Chinese address segmentation algorithm using self-organizing neural network (SONN). The SONN design is composed of an input layer and an output layer, fully connected with random initial weights. Unparsed addresses are transformed into activation patterns on the input layer by activating corresponding neurons simultaneously. The training process is controlled by the Hebbian learning rule and the "k winners take all" (KWTA) competing function. After the self-organization process, each unparsed address will be represented by k (multiple) winners with each winner representing a sub-pattern of the address. The goal of the algorithm is to make these sub-patterns correspond to the word segments of the addresses. Two tests were carried out using a prototype system implementing the algorithm. The results show that the current design can achieve the purpose conditionally and we will discuss the limitations of the SONN for actual applications and the possible improvements of the model will be also discussed.

Networked Virtual Reality (NVR) is a system based on net connected and spatial information shared, whose demands cannot be fully meet by the existing architectures and application patterns of VR to some extent. In this paper, we propose a new architecture of NVR based on Multi-Agent framework. which includes the detailed definition of various agents and their functions and full description of the collaboration mechanism, Through the prototype system test with DEM Data and 3D Models Data, the advantages of Multi-Agent based Networked Virtual Reality System in terms of the data loading time, user response time and scene construction time etc. are verified. First, we introduce the characters of Networked Virtual Realty and the characters of Multi-Agent technique in Section 1. Then we give the architecture design of Networked Virtual Realty based on Multi-Agent in Section 2.The Section 2 content includes the rule of task division, the multi-agent architecture design to implement Networked Virtual Realty and the function of agents. Section 3 shows the prototype implementation according to the design. Finally, Section 4 discusses the benefits of using Multi-Agent to implement geovisualization of Networked Virtual Realty.

Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

This paper proposes a new method to parse various application schemas of Geography Markup Language (GML) for understanding syntax and semantic of their element and type in order to implement uniform interpretation of the same GML instance data among diverse users. The proposed method generates an Integrative GML Syntactic and Semantic Schemas Database (IGSSSDB) from GML3.1 core schemas and corresponding application schema. This paper parses GML data based on IGSSSDB, which is composed of syntactic and semantic information, nesting information and mapping rules of GML core schemas and application schemas. Three kinds of relational tables are designed for storing information from schemas when constructing IGSSSDB. Those are info tables for schemas included and namespace imported in application schemas, tables for information related to schemas and catalog tables of core schemas. In relational tables, we propose to use homologous regular expression to describe model of elements and complex types in schemas, which can ensure model complete and readable. Based on IGSSSDB, we design and develop many APIs to implement GML data parsing, and can process syntactic and semantic information of GML data from diverse fields and users. At the latter part of this paper, test study is implemented to show that the proposed method is feasible and appropriate for parsing GML data. Also, it founds a good basis for future GML data studies such as storage, index and query etc.

POI abbreviation matching is one difficult aspect of POI name matching, since Chinese POI abbreviations have Eastern Language specialty and are mostly formed without strict rules. Examinations of existed website that contains POI name matching are made and approaches proposed are analyzed. To catch the special regularities of POI abbreviation, a statistical model consists mainly of Markov Chain is built to simulate the process of POI abbreviation forming. Detailed algorithm, corpus-building instructions and test results was presented in this paper. A future improving direction was also presented as a result of error analyses.

Approaches to displaying 3D images (e.g. stereoscopic display, volumetric system and integral photography.) currently used can not present real 3D images for users. Holography is an intriguing technique for visualizing 3D objects because it is the only 3D display technology known today that is capable of creating the most authentic illusion of observing volumetric objects by the naked eyes, therefore, the visualization of 3D models using a kind of holographic display is an appealing task. In this paper, a new approach to 3D Terrain Model display is proposed, and in which the computer-generated hologram (CGH) is used in the holographic stereography instead of recording a hologram by interfering coherent light in conventional holography. An example in which the terrain display using holographic stereography is preliminarily simulated with computer, however, it shows that the proposed approach is theoretically feasible and promising.

Based on the Real Right Law, this article analyzes the entity objects of the realty uniform registration, and establishes the model of the logical relations among the entities, from which the dada relation model is proposed, and from which the data relation model of the realty uniform registration is proposed, and is compared with the current land registration data model and the real estate data model. It is proved that this uniform registration data model has not only maintained the close links with the land registration data model and the real estate registration data model, but also met the need of the uniform registration by comparing with the existing land registration data model and the real estate data model. In the end, this article discusses the method of data storage for the uniform registration of the land and the real estate to improve the efficiency of storage and access by adopting split technology to store the alteration data logically.

A natural language interface can make a geographic information system (GIS) easy to use. It allows one to use the natural language quickly and conveniently to operate in such as digital city management system or traffic guidance system. This paper discusses the method of nature language understanding in GIS based on ontology. Natural language understanding is general apply in computer or artificial intelligence research area, yet in GIS the natural language understanding is mainly concerned about spatial information. In order to implement the natural language understanding for spatial information perfectly we use the ontology model. First we put forward a generally process of natural language understanding in GIS, defined the conception of the ontology, next set up the ontology structure, ontology-based understanding model, also indicate the mechanism of natural language understanding based on ontology. Finally are a case study and a prototype, a discussion about the research deficiency and the development forecast of my research.

Computational fluid dynamics (CFD) models are powerful computational tools to simulate urban-landscape scale atmospheric dispersion events. They are proven to be very useful for security management and emergency response. Essential inputs to CFD models include landscape characteristics, which are often captured by various GIS data layers. While it is logical to couple GIS and CFD models to take advantage of available GIS data and the visualization and cartographic rendering capabilities of GIS, the integration of the two tools have been minimal. In this paper, we took the first step to evaluate the use of GIS data in CFD modeling. Specifically, we explore how efficient is to use GIS data in CFD models and how sensitive the CFD results are to different GIS data formats. Using campus topography and building data, and the FEFLO-URBAN CFD model, we performed atmospheric release simulations using topographic data in contour and raster formats. We found that using raster format was quite efficient and contour data required significant effort. Though the simulation outputs from the two data formats were not identical, their overall outcomes were similar and did not post alarming discrepancies. We concluded that using GIS data have tremendous potential for CFD modeling.

Dynamic monitoring of land use is a perennial and persistent process now in Shanghai. Therefore, the cumulated amount of monitoring data will be very large. It is an exigent problem how to manage and use this data effectively. The key issue is finding a suitable spatio-temporal data model that must take into account space, time and attribute factor adequately. In dynamic monitoring of land use, it is change that is of direct interest. With analyzing the feature of land use dynamic monitoring and the shortage of some spatio-temporal data models when they are used in the field, this paper proposes a Hierarchical Spatio-Temporal Data Model (HSDM) that stores elements of change and makes these available for direct query and analysis.

Visualization is an important means of understanding and explaining the natural phenomena. The visualization of ocean can help us understand and utilize the undersea world. As we know, the ocean is a real three-dimensional space, so the visualization includes not only the simulation of interface terrain (such as sea water surface, sea bottom, etc.) but also the hydrographic feature (such as salinity, temperature, pressure, current directions etc.). In this paper, taking the temperature field in the sea as the example, we discussed the visualization of data of space-fulfilled field from a viewpoint located in the field. We analyzed the acquisition and interpolation of 3-D oceanic data in section 2, proposed an Octree model in section 3, introduced visualization in scientific computing and implemented temperature field visualization based on volume rendering in section 4. Lastly, some conclusions are given in section 5.

This paper presents a method for solving main problems in the multi-source data integration of land and sea including the inconsistent horizontal and vertical datum, the differences of data model and format and the discrepancy of a geographical feature derived from different data source,. Firstly, based on the transformation of horizontal coordinate and calibration of vertical datum, spatial data are reconciled. Secondly, DEM of digital coastal zone are established by the combination of topographic and bathymetric data from sampled soundings and simplified contours. Finally, the visualization and multi-scale representation of the DEM is realized. Experimental results demonstrate that the proposed method could seamlessly integrate multi-source land and sea data.

The pattern recognition of polygon clusters is a most attention-getting problem in spatial data mining. The paper carries through a research on this problem, based on spatial cognition principle and visual recognition Gestalt principle combining with spatial clustering method, and creates two innovations: First, the paper carries through a great improvement to the concept---"visual distance". In the definition of this concept, not only are Euclid's Distance, orientation difference and dimension discrepancy comprehensively thought out, but also is "similarity degree of object shape" crucially considered. In the calculation of "visual distance", the distance calculation model is built using Delaunay Triangulation geometrical structure. Second, the research adopts spatial clustering analysis based on MST Tree. In the design of pruning algorithm, the study initiates data automatism delamination mechanism and introduces Simulated Annealing Optimization Algorithm. This study provides a new research thread for GIS development, namely, GIS is an intersection principle, whose research method should be open and diverse. Any mature technology of other relative principles can be introduced into the study of GIS, but, they need to be improved on technical measures according to the principles of GIS as "spatial cognition science". Only to do this, can GIS develop forward on a higher and stronger plane.

An accessibility computing method and process based on grid partition was put forward in the paper. As two important factors impacting on traffic, density of road network and relative spatial resistance for difference land use was integrated into computing traffic cost in each grid. A* algorithms was inducted to searching optimum traffic cost of grids path, a detailed searching process and definition of heuristic evaluation function was described in the paper. Therefore, the method can be implemented more simply and its data source is obtained more easily. Moreover, by changing heuristic searching information, more reasonable computing result can be obtained. For confirming our research, a software package was developed with C# language under ArcEngine9 environment. Applying the computing method, a case study on accessibility of business districts in Guangzhou city was carried out.

Geostatistical method can reflect quantitatively variable spatial distribution characteristic, and through produces many different theoretical models to reflect quantitatively the uncertain attribute because of lacking material. But geostatistics is taken a new discipline, it also exists the probability of extension. The extension of ordinary geostatistics includes mainly three aspects: the treatment of outliers in geostatistical spatial data, fitting the variogram and selecting Kriging estimate neighborhood. And it introduces the basic mentality of applying geostatistical space analytical model to appraise datum land price base on analyzing the feasibility.

In remote sensing image processing, the conversion from raster data to vector data always needs to be made. In previous research of this conversion, researchers mainly focus on the algorithms and efficiency, neglecting the uncertainties in the conversion. This paper reviews the input uncertainty and model uncertainty, and mainly focuses on the analysis of error and uncertainty, together with their propagation in data conversion from raster image to vector. In the conversion, the uncertainty comes from source image data uncertainties, data processing uncertainties and model uncertainties. An experiment was made on analysis of data processing uncertainties in the conversion.

In recent years, the Chinese government has attached great importance to the increasingly upward trend in housing price and many regions have developed the monitoring and reporting system of housing price. However, the factors which influence the housing price is so complex that traditional sampling approaches used in the land price monitoring could not play well in housing price monitoring. By analyzing the disadvantages existed in classical spatial sampling and specific characteristics of housing price, taking the dwelling houses in Wujin section of Changzhou city for example, the author brought the adaptive spatial sampling to the allocation of housing price monitoring sites. Through the experiments, we could come to the conclusion that based on spatial-relative matrix, through comprehensive analysis, spatial adaptive sampling would lead to the samples that are representative both on special attributes and spatial location. Finally, the paper also discussed practical approaches that may work to improve the efficiency of adaptive spatial sampling in further study.

Two kinds of terrain representation error which extracted from the Digital Elevation Model (DEM) with different spatial resolutions and different convolution resolutions are studied respectively, and the comparison between them are made. An average slope error estimation model validated suitable for Beijing with a relative error less than 20% is proposed, which can simulate quantitatively the variation of the average slope error according to the DEM resolution. The contour data with the scale of 1:10000 is treated as data source in this paper.

One goal of the IERS to define and maintain the ITRF is to combine all major space geodetic techniques (GPS, VLBI, SLR, LLR and DORIS solution in the SINEX format) into an integrated consistent set of high-accuracy products. In such a combination, estimating and removing the systematic errors between different SINEX files is an important issue. For this purpose software GNAS (Geodesy Network Analysis System) is developed, which is able to estimate 7 Helmert transformation parameters of station coordinates within the process of combination. Besides, the GNAS software enables us to combine EOPs and station coordinates not only separately, but also simultaneously. We discuss the advantages and disadvantages when systematic parameters are estimated for each Analysis Center (AC) or for each SINEX file. One can estimate either the whole 7 Helmert parameters or only a set of them (e.g. without 3 rotation parameters). Different procedures have different effects on the combined solutions, especially when EOPs and station coordinates are combined simultaneously. Detailed discussions, numerical examples and some results analysis are given in this paper.

Geospatial data are being increasingly produced, shared, and analyzed in GIS community, and data users are always interested in "good" quality data, which means "fitness for use". However, the complex peculiarities of geographic data bring many difficulties for providing such good quality data according to users' requirements or a product specification. The diverse data quality demands of different users or specifications need to be clearly stated and described, in order that data quality information can be easily applied to data involved activities, such as data capture, data process and data integration. In GI Science, a widely used means for representing quality information is to adopt constraints or rules, for example, spatial integrity constraints are used to deal with spatial relations of geographic entities and also containing semantic information. In order to handle data quality rules, extensive spatial data quality elements need to be investigated. In this paper, international standards relating to spatial data quality are emphasized for studying detailed quality elements. Moreover, a methodology for representing data quality rules in a logical way is given, and various examples corresponding to different data quality elements are used to demonstrate its usages.

Taking Yaoxian County as an example, applying with the Indices of landscape pattern and DEM, this paper studied the relation of vegetation Spatial characteristics and terrain factors, the difference of the landscape pattern under various degree of human disturbance in alp-clough, Plateau, plain and land between ravines, ravine slope land and ravine bottom land .The results showed that: in ravine slope land, ravine bottom land and alp-clough, the natural landscapes were in the absolute dominant position. However, from northwest to southeast, with human disturbance intensity increasing, anthropogenic features of landscapes became more and more outstanding In Plateau, plain and land between ravines, the landscape structure appeared to be simpler with coarse grains and a less rich diversity. Conversely, in alp-cloug, ravine slope land and ravine bottom land, the landscape showed a complicated shape with a relatively richer diversity. This reflected that the impact of human activities to natural landscape behaved a gradually-growing trend from northwest to southeast, in addition ,the paper also shows that vegetation characteristics in different elevation, slope and aspect of slope, are very different and manifest some rules In addition, the paper also shows that in different topography areas, various vegetation appears different hobby to water and With the distance increasing from towns, various vegetation appear different rules.

In this article, the GMM based estimation of a typical family of spatial panel models with spatially lagged dependent variables and error components that are both spatially and time-wise correlated is addressed. We derive the best GMM (BGMM) estimator within certain class of optimal GMM estimators. We also discuss the asymptotic efficiency of BGMM estimator relative to the panel analogue of generalized spatial two stage least squares (GS2SLS) estimators and maximum likelihood (ML) estimators. We show that by including GS2SLS estimators as a special case, the BGMM estimator is generally more efficient than GS2SLS estimator and able to be as efficient as ML estimator under normality.

Spatial data mining and knowledge discovery (SDMKD) is a whole process of discovering implicit but useful knowledge from GIS databases. From the first law of geography, spatial association patterns are the realizations of processes that operate across the geographic space. This paper attempts to present a decision tree framework to assist in analyzing spatial association patterns. Based on the problem, the representation of data or data model should be identified firstly. Secondly, geostatistical, lattice and point pattern data can be distinguished through the characteristics of spatial domain. The main task of third level of the decision tree is to apply different spatial data analysis methods to different spatial data types. For lattice data, the work is to apply exploratory spatial data analysis (ESDA) to find spatial association patterns, and then identify the driving forces which cause the observed spatial association patterns by confirmatory spatial data analysis (CSDA). The fourth level is to verify the precision and accuracy of spatial association models. All in all, spatial association pattern analysis is a process of acquiring useful spatial patterns by circulation and repetition.

Land use patterns are governed by a broad variety of potential driving forces and constraints which act over a large range of scales and multi-scale investigation of land use patterns is essential for full understanding of its complexity. The main purpose of this paper was to perform a multi-scale analysis of arable land distribution pattern of Fujian province by means of statistical analysis through overall study and each agro-zone respectively. 27 variables were selected as the candidate land use drivers representing bio-geophysical, socio-economic and infrastructural conditions. The basic spatial organization in the analysis was a 1km×1km geographical grid. Through aggregations of these cells, a total of 10 artificial aggregation levels were obtained. The independent models of the whole study area and each 6 agro-zones of arable land distribution patterns were constructed at multiple scales respectively. The results showed that Land use models varied with aggregation level and also between agro-zones. Independent variables explained more of the variance for the explanation of land use type at higher aggregation levels. Except slope, the highest ranking variable, other variables of the arable land use model vary between agro-zone I to VI. But the general rule is that arable land in all 6 agro-zones is strictly restricted by topographic factors which changes little along with time. It is argued that these types of analyses can support quantitative multi-scale understanding of land use, needed for the spatially explicit land use change models.

Geostatistics analyst is based on the fundamental geographic principal, namely, things that are closer together tend to be more alike than things that are farther apart and widely used in many fields. In this paper, taking Ganjiang Drainage as sample region, we select IDW, Ordinary Kriging and Simple Kriging interpolation of geostatistics analyst to interpolate rainfall data and use cross-validation to compare the results of interpolation. In order to find out the most suitable interpolation method, we respectively use different interpolation methods with same parameters, same method with different semivariogram model as well as considering trend influence and anisotropy to interpolate the rainfall data. Comparing the results, we draw the following conclusions: (1) Under the premise of knowing mean, Simple Kriging owns the highest interpolation precision. (2) Kriging has fine feature to reflect rainfall trend changing of larger-scale extent. On the contrary, IDW can depict local detailed changing well. (3) Rainfall data exists weak autocorrelation. (4) Exponential model of semivariogram has the highest precision than others. (5) Ignoring trend influence and anisotropy will not decrease the precision of interpolation.

There is only a static state of the real world to be recorded in conventional geographical information systems. However, there is not only static information but also dynamic information in geographical phenomena. So that how to record the dynamic information and reveal the relations among dynamic information is an important issue in a spatio-temporal information system. From an ontological perspective, we can initially divide the spatio-temporal entities in the world into continuants and occurrents. Continuant entities endure through some extended (although possibly very short) interval of time (e.g., houses, roads, cities, and real-estate). Occurrent entities happen and are then gone (e.g., a house repair job, road construction project, urban expansion, real-estate transition). From an information system perspective, continuants and occurrents that have a unique identity in the system are referred to as objects and events, respectively. And the change is represented implicitly by static snapshots in current spatial temporal information systems. In the previous models, the objects can be considered as the fundamental components of the system, and the change is modeled by considering time-varying attributes of these objects. In the spatio-temporal database, the temporal information that is either interval or instant is involved and the underlying data structures and indexes for temporal are considerable investigated. However, there is the absence of explicit ways of considering events, which affect the attributes of objects or the state. So the research issue of this paper focuses on how to model events in conceptual models of dynamic geographical phenomena and how to represent the causal relations among events and the objects or states. Firstly, the paper reviews the conceptual modeling in a temporal GIS by researchers. Secondly, this paper discusses the spatio-temporal entities: objects and events. Thirdly, this paper investigates the causal relations amongst events and states. The qualitative spatiotemporal change is an important issue in the dynamic geographic-scale phenomena. In real estate transition, the events and states are needed to be represented explicitly. In our modeling the evolution of a dynamic system, it can not avoid fetching in the view of causality. The object's transition is represented by the state of object. Event causes the state of objects changing and causes other events happen. Events connect with objects closely. The basic causal relations are the state-event and event-state relationships. Lastly, the paper concludes with the overview about the causal relations amongst events and states. And this future work is pointed.

In this paper we attempt to assess the patterns of spatial association of technical market in China spanning from 1998 to 2005 by using GIS and ESDA. The study starts from exploring global spatial association of technical market by means of a global indicator of spatial autocorrelation. Secondly, in order to analyze the local patterns that the global indicator would not pick up, local indicator of spatial association is applied to technical market in China. Thirdly, analysis on stability of spatial pattern is carried out to evaluate similarities and dissimilarities during the whole period. We can draw a conclusion that spatial pattern of Chinese technical market has been stable along the time. Significant global spatial clustering is presented in the first two years, while the remaining years display a global spatial randomness. In terms of local patterns, clear spatial clustering of different pattern is found in some regions.

Urban parks are the important recreation site for citizens, viewed as basal green infrastructure and crucial amenities in urban areas, and usually perform important ecological and socio-economic functions. With socio-economic development, Chinese people and governments pay much more attention to urban green spaces, especially urban parks, and more and more citizens have the desire for contact with nature, and are willing to live and work close to urban parks. Consequently, governments plan to optimize urban parks allocation in order to meet citizens' increasing needs. Quantification of accessibility of urban parks is a prerequisite to appraise and allocate them with equity as a tool for decision-making in planning. In this paper, supported by Remote Sensing and GIS, the accessibility of urban parks based on high resolution data was analyzed with minimum nearest distance method at the house level and container method at block groups scale, through a case study of Qingdao city, China. The distances between houses (origins) and urban parks (destinations) are measured as the Euclidian (straight-line) distance. Four levels of access, very good, good, poor and very poor, were classified based on the distance between residence and the nearest urban park, and the area of urban park per capita. Results demonstrate that the spatial patterns of accessibility are consentaneous on the whole by using two different methods, for the spatial pattern is relation to the distribution of urban parks. However, the accurateness in results is quite different. The accessibility of urban parks acquired by the minimum nearest distance method is more accurate and appropriate than under the container method. The results calculated with the container measure show that 58.07 % of block groups have very poor or poor access level, which means the accessibility of urban parks is not good in Qingdao city as a whole. In addition, the spatial pattern of the accessibility is not equipoise. The southern and north-eastern areas appear to have good access to urban parks. The results calculated with the minimum nearest distance method illustrate that 92.15 % of houses have very good or good access level, which means that the accessibility of urban parks is good in Qingdao city as a whole. The results also show that the distribution of urban parks has a comparatively high level of equity and fairness at house level, and the spatial pattern of the accessibility of urban parks based on the minimum nearest distance measure is much more equipoise than the one based on container measure. Theses models from this paper can provide planners and policy-makers with substantial information that can be used in urban parks develop planning and assessment.

This paper sets up 5 Census database in 1953,1964,1983,1990,2000 based on GIS. The population gravity centers of main nationalities were calculated using gravity model in 1953, 1964,1983,1990,2000. Then, the characteristics and the influence factors of the moving of the minority population are analyzed. Study results show that population gravity center move to capitals are obvious. The move velocities of minorities' population gravity centers are slowdown, while the move velocities of HAN is Accelerated. Movement distances of east-west direction are generally greater than that of the north-south direction. The population gravity center are continued moving to southeast all the while. Finally, the factors of Natural conditions, Economic development, Policies as the mainly reasons were discussed.

Non-linear Semiparametric model is a statistical model consisting of both parametric and nonparametric components, and the form of the parametric part is non-linear. The efficiency problem for a semiparametric model has been widely studied presently. Since non-linear parametric models have been studied deeply, and a set of basic theory have been set up, such as the measurement of the non-linearity of non-linear models and the statistics property of non-linear parametric estimation. Based on the nearest neighbor estimating theory of non-linear semiparametric models under the least squares principle, this paper proved the nonsingularity of coefficient matrix of normal equation under certain conditions. The nonsingularity of coefficient matrix of normal equation in least squares estimator of non-linear semiparametric models can be expanded to other least squares estimator of non-linear semiparametric models.

This paper firstly summarizes the research progress of the spatialization about regional statistic data. It is concerned with problems arising when a region is divided into different sets of zones for different purposes, and data available for one set of zones are needed for a different set. The areal interpolation is usually used to solve this problem of statistic data. In the study, we take Beijing Chao Yang District as study area (source zone), and we successfully apply three methods to translate the industrial output value from the administrative zones of Chao Yang (source zones) to regular zones of 1km grid lattice (target zones), including areal weighting; point-in-polygon and raster representation based on zone centroid locations.It shows that the spatialization result can express the spatial characteristic of socioeconomic assets more accurately and objectively.

The objective of this study is to present a novel model for simulating the evolution of gradual change systems. The proposed model, named SDCA-state delay cellar automata, extends the traditional cellar automata (CA) to include state delay, variable time step, and state-delay cell evolving to aid prediction making for the gradual systems developments. The model can perform microcosmic changing happens in one time step through changing state-delay time. In this article, the SDCA model used to simulate the forest fire spreading which is a typical gradual changing system under different external conditions. As experiments' result shown, SDCA model can simulate the forest fire spreading and perform gradual changing with time step varied accurately and simply. Finally, it is concluded that the SDCA model is an effective model in simulating the gradual changing systems' propagation.

Urbanization is a major trend in recent years all around the word. Changes of land use due to urbanization is the main cause of urban natural recourses loss or fragmentation and consequently brings the worsening conditions of urban environment, as well as increase urban ecological problems. In this paper, the land use, especially the built-up land spatial pattern and changes, were monitored and quantified in the study periods 1989-2004 with GIS and moving window method. The application of moving window method could examine the land use change process and link pattern and process easily in the local area. The study shows a rapid increase in built-up land but mostly at the expense of green spaces and agriculture land. The changes of urban built-up land were not distributed evenly. In a general, the urban development of Jinan City is an irregular monocentric pattern. The orientation of urban development policy and the special topography were considered the major reasons. Besides, the attraction of green space amenity is also an important factor that can not be neglected. The results will be contributed to guide the urban land use planning and management, especially the urban natural resources conservation.

Slope spectrum is defined as a statistic model of slope distribution in a certain area. Previous researches mainly focus on morphology depiction of the slope spectrum; its spatial distribution is unknown yet, especially in the Loess Plateau. Theory and methodology of information entropy and statistics are applied for the objective of quantitatively analyzing the slope spectrum and its spatial distribution in the Loess Plateau in North Shaanxi province. Experiment results show that slope spectrum's information entropy (H), skewness of slope spectrum (S) and terrain driving force factor (T_d) can appropriately depict the slope spectrum and its spatial distribution from different points of view. Spatial distribution of the slope spectrum represents spatial distribution of loess landform types, and it is correlatable with spatial distribution of soil erosion intensity in the Loess Plateau. H, T_d and gully density, surface incision depth show positive correlation: gully density and surface incision increase as H, T_d increase. On the contrary, the S and gully density, surface incision depth show negative correlation. Lastly, spatial relationship between slope spectrum and loess landform types are qualitatively analyzed, and loess landform evolution as well.

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. One of the main causes resulted in these biases is overlooking of sub-pixel variability of topography, especially in a mountainous area. This study analyzes the significance of topography to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. Its application to a remote sensing process-based model estimates made at a 1-km resolution over a mountainous forested watershed located in Baohe River Basin in China. Results of this study show that NPP spatial scaling in complex terrain depends on the amount of the distortion of the soil moisture field at the coarse resolution, and the spatial redistribution and movement of soil water in complex terrain tightly affect NPP distribution, suggest that it is indeed necessary to consider topography in NPP spatial scaling.

Urban flow is a phenomenon of the interaction and relation between the cities in the region based on the transport network and urban synthetic strength. And, because of the difference in traffic conditions and the level of economic development in different city, the intensity of the urban flow of each city is different and the primary effecting factor is dissimilar. The traditional analysis on the effecting factors of urban flow concerns the background of the entire region as a whole entity, which would be too vague and ignore the difference in the effecting factors of different cities as well as the micro differences and spatial non-stationarity in the dominant factor. The research on spatial difference in the effecting factors of the urban flow in this paper focused on the analysis of the diverse effecting factors of urban flow caused by the regional disparity; found out the primary factors; and analyzed the spatial characteristics of effecting factors using GIS. We established a mathematical model, which was applied to the urban agglomeration of the Yangtze River Delta, the intensity of the urban flow of every city in this district was figured and the regression model was constructed. The principal effecting factor of the urban flow of every city and its characteristic of the spatial distribution was analyzed. we summarized the effecting factors of the urban flow is an indication of the persistence of spatial difference among Yangtze River Delta, and the spatial pattern of it was investigated.

In this paper, spatial autocorrelation analysis, ordinary least square (OLS) and spatial regression models were applied to explore spatial variation of soil salinity based on samples collected from the Yellow River Delta. Generally, spatial data, like soil salinity, elevation height etc., are characterized by spatial effects such as spatial dependence and spatial structure. Inasmuch as these effects exist, the utilization of OLS model may lead to inaccurate inference about predictor variable. Moreover, the traditional regression models used to analyze spatial data often have autocorrelated residuals which violate the assumption of Guess-Markov Theorem. This indicates that conventional regression models cannot be used in analyzing variability of soil salinity directly. To overcome this limitation, spatial regression model was introduced to explore the relationship between soil salinity and environmental factors (including elevation height, pH value and organic matter concentration). By verifying Moran's I scatterplot of residuals, we found no autocorrelation in spatial regression model compared with high significant (p < 0.001) positive autocorrelation in the OLS model; besides, the spatial regression model had a significant (p < 0.01) estimations and good-fit-it in our study. Finally, an approach of specifying optimal spatial weight matrix was also put forward.

This paper explains the basic points of earth science research, reviews the notion of digital earth and suggests the basic concept of digital earth platform. Taking the theory of digital earth as an essence point and the framework of digital earth platform as a main clue, we mainly discuss: the basic theories of digital earth platform, a comparatively flawless model of earth science research framework based on the digital earth platform. The discussing issues involves the unified coordinate projecting, data updating, data transferring, data processing and analyzing and data displaying and a series of researches relating to energy sources, eco-system and disasters monitoring and forecasting with a combination of the suggested model of earth science research framework.

Terrain is one of the essential elements on geography. A Digital Elevation Model (DEM) is one of the methods to represent the elevation of the earth's surface. It contains abundant landform information. It is very important that we can extract relevant information form DEM for GIS to analyze and apply. And it is very meaning that Mini-watersheds are classed with data mining yielding knowledge. This paper shows that some problems can be addressed using GIS technology. Firstly, TIN and DEM are formed. Secondly, 28 Mini-watershed of the study area separated by Hydrology Analysis and factors of other terrain are extracted. Such as drainage density, average slope, average slope length and topographic relief. Thirdly, Mini-watersheds are classed again by clustering based on data collecting C5.0 (Algorithm). In the end, model are set up and discussed. In this paper, we have discussed that (a)the topological gurgitation and slope grade relation great with each other (0.93); (b)most Mini-watershed are orientation south; (c) the results and models showed correlation clearly between terrain and agriculture landuse in the study area.

The "digital reservoir" is usually understood as describing the whole reservoir with digital information technology to make it serve the human existence and development furthest. Strictly speaking, the "digital reservoir" is referred to describing vast information of the reservoir in different dimension and space-time by RS, GPS, GIS, telemetry, remote-control and virtual reality technology based on computer, multi-media, large-scale memory and wide-band networks technology for the human existence, development and daily work, life and entertainment. The core of "digital reservoir" is to realize the intelligence and visibility of vast information of the reservoir through computers and networks. The dam is main building of reservoir, whose safety concerns reservoir and people's safety. Safety monitoring is important way guaranteeing the dam's safety, which controls the dam's running through collecting the dam's information concerned and developing trend. Safety monitoring of the dam is the process from collection and processing of initial safety information to forming safety concept in the brain. The paper mainly researches information collection and processing of the dam by digital means.

The paper discusses a new method of acquiring small watershed terrain data from 3D laser scanner to make a High-resolution DEM with the help of GPS technology; and develops Distributed Hydrological modeling system based on TOPMODEL and linear reservoir theory. Resolution of DEM is an important factor which has decisive influence on the modeling veracity of Distributed Hydrological Model. The DEM built here can improve the precision to as high as 1m at the most. With the high-resolution DEM providing source data, the modeling system is applied in small catchments of Loess plateau. Finally the paper makes a comparative analysis on the two systems' stimulating precision, which is derived from a high-resolution DEM and a traditional DEM respectively. The result indicates that the precision of the hydrological modeling is much more enhanced; and that hydrological processes can be interpreted much more precisely, and the soil and water loss mechanism is more comprehensible.

This paper makes research on the methods of automatic-generation of 3D virtual city from the view of urban cellular automata model. The evolution process of the urban land units can be simulated by constructing urban cellular automata model, and then the results of evolution will determine the space location and corresponding building types of land units. Our research makes use of MultiGen Creator to build 3D scenes, and scene management technology of OpenGVS to generate buildings at random, then these buildings will be set on corresponding locations of 3D scene so as to generate 3D virtual cities. We develop 3D virtual city automatic-generation system and also discuss the application potential and value of it in the field of municipal administration, urban planning, urban research, etc.

In this paper, a method to generate a digital elevation model (DEM) from contour lines is proposed. The generation of DEM can be described as an iterative procedure, in which new contours are obtained by a weighted Euclidian distance transformation and a consequent extraction of boundaries of the Voronoi diagram. It is characterized by the linear interpolation with each iteration for generating contours with half contour interval of earlier ones. The performance of the method is analyzed by both numerical tests and a topographic map test. Five mathematical surfaces are employed in numerical tests. DEMs generated by the method proposed are comparatively evaluated with other methods, including TLI (triangulated irregular network with linear interpolation) and TOPOGRID in ArcGIS. This algorithm gives an effective method for producing DEM with acceptable accuracy and simple operations.

Earth science data and information are generated, collected, and archived at geographically dispersed locations and computers by different organizations including government agencies, companies, and others. To leverage the legacy resources for discovering earth science information and knowledge, we need a convenient access to the resources in an integral and timely fashion. This paper presents a joint effort in developing the Earth Information Exchange, an earth science portal, to support this need by approaches based on interoperability and cyberinfrastructure. ESG, an interoperable portal, is used to provide interoperability support to accessing heterogeneous resources. GMU Grid, as part of the cyberinfrastructure, is utilized to support time-consuming preprocessing, modeling, decision support tools operation. Semantic search is utilized in bridging different domains for sharing cross domain information and knowledge and refining research results. The functions are integrated into the Earth Information Exchange developed by the partnership of National Aeronautics and Space Administration, The Federation of Earth Science Information Partnership, and George Mason University to support the objective for integral and timely exchange of earth science information. The on-going effort will also provide a spatial web portal to access and improve earth science information holdings at different government agencies, educational and research institutions, and Non Government Organizations (NGO).

Gradient Slope, as a basic topographic parameter, is widely used in many research fields such as agrology, meteorology, ecology and hydrology, etc. However topographic parameters extracted from DEMs have distinct scale effect, which can lead large degree uncertainty to application results. This paper investigates the scale effect of slope derived from DEMs and builds its transforming model. The research takes 48 sample sites as test areas which are located in different landforms in loess plateau of North Shaanxi province, and a series of multi-scales DEMs as test data, slope scale effect is investigated in both point slope and mean slope respectively. The experiment shows that each point slope fluctuates and decreases with the decreasing of DEM resolution. It presents the characters of both local fluctuation and global decreasing. While mean slope varies inversely and regularly with the increasing of DEM grid size. In certain range of DEM scales, mean slope meet the law of fractal geometry. Fractal dimension has relationship with the elevation differences and complexity of landforms. According to the slope scale effect, slope scaling model is established, which can effectively realize slope downscaling. The scaling result shows that those downscaled slope can efficiently approach target value on the aspect of spatial distribution structure, statistic index and slope histogram. More work should be paid mainly on solving transformation errors in the area of mixed landforms and the errors of slope histogram with two peaks.

Digital terrain data are useful for all kinds of applications in digital terrain analysis (DTA). Recently, terrain feature extraction are generally based on grid DEM because most terrain data are organized in a raster format. Terrain complexity is very important terrain feature in digital terrain analysis, however, unlike aspect or slope, terrain complexity is an ambiguous conception that till now no optimal index to quantify it. The traditional terrain complexity definitiones can be classified as statistical, geometrical and semantic indices, these indices can quantify terrain complexity to some extent, but can not evaluate some special terrain. This paper wants to seek an optimal Terrain complexity index (TCI) to evaluate the terrain complexity. The total curvature is a synthesis idex of latitude derivative fxx, longitude derivative fyy, and diagonal derivative fxy, it is a sound solution to the terrain anisotropy. In order to test this index, 3 study area with typical terrain of plain, gully, and hill are selected for experimentation, the result shows total curvature is a sound terrain parameter to evaluate terrain complexity. Terrain complexity is a regional feature, while total cuvature is a local index, so the statistic (Mean TCI, Maximum TCI and SD TCI) are proper indicator to evaluate terrain complexity. The derivative of specific points on the mathematic curve is the ratio of the change in the angle of a tangent that moves over a given arc to the length of the arc, the shorter the arc is, the more arcurate the ratio curvature is. As to grid DEM, the length of arc can be consier as the DEM resolution. Result shows, the Mean TCI, Maximum TCI and SD of TCI have strong correlation with DEM resolution according to regression analysis, the R2 is higher than 0.96.

Paper discusses the function and meaning of AR in the aerodrome construction project. In the initial stages of the aerodrome building, it applies the advanced technology including 3S (RS, GIS and GPS) techniques, augmented reality, virtual reality and digital image processing techniques, and so on. Virtual image or other information that is created by the computer is superimposed with the surveying district which the observer stands is looking at. When the observer is moving in the district, the virtual information is changing correspondingly, just like the virtual information really exists in real environment. The observer can see the scene of aerodrome if he puts on clairvoyant HMD (head mounted display). If we have structural information of the aerodrome in database, AR can supply X-ray of the building just like pipeline, wire and framework in walls.

The quality control of 3D city reconstruction projects mainly depends on interactive checking and rectification, which is original, random and unreasonable. This paper puts forward an automatic quality control (AQC) strategy for it. Firstly, this paper discusses the principle of AQC, then, develops some methods for it, including automatic algorithms for error detecting, constraint and compensation, and an AQC management system. Finally, the authors cite several international joint projects to prove the validity and feasibility of this strategy.

DEM (Digital Elevation Model) is a commonest basic data in different geospatial applications. It is one of the fundamental issues for geo-science to extract the different kinds of terrain's waving characteristic in DEM self-adaptively and automatically. This paper presented our research on the basic mathematical model for rupture terrain characteristic extraction with variable-scale method. After the rupture edge characteristic point is obtained, the irregular line of rupture edge is generated in Terrain Characteristic Hypergraph Relationship (TCHR) ^[1] method, then combined into rupture's region object. Through experiment about submarine grid DEM, the comprehensive terrain characteristic of rupture can be obtained accurately and effectively, and its result matched the submarine terrain precisely.

This paper shows a method to combine the imaged-based modeling technique and Laser scanning data to rebuild a realistic 3D model. Firstly use the image pair to build a relative 3D model of the object, and then register the relative model to the Laser coordinate system. Project the Laser points to one of the images and extract the feature lines from that image. After that fit the 2D projected Laser points to lines in the image and constrain their corresponding 3D points to lines in the 3D Laser space to keep the features of the model. Build TIN and cancel the redundant points, which don't impact the curvature of their neighborhood areas. Use the diluting Laser point cloud to reconstruct the geometry model of the object, and then project the texture of corresponding image onto it. The process is shown to be feasible and progressive proved by experimental results. The final model is quite similar with the real object. This method cuts down the quantity of data in the precondition of keeping the features of model. The effect of it is manifest.

The DEM concerns only the elevation of each cell instead of the landform feature such as valley, ridge, saddle, pit and peak. But these features play a significant role in the terrain generalization. Only when cartographers firstly identify and assess these features and their spatial structure correctly could terrain generalization obtain a satisfactory result. This paper proposes an approach to generalize DEM based on the simplification of valley system, which means that the valley systems are extracted and structurized beforehand. Based on the structured valley system, the process of DEM generalization is subdivided into three sub-processes: valley lines generalization, which results from the simplification of the structured channel network; and valley coverages generalization, which consists of a gradual incorporation of the associated valley coverages; and valley surface fitting, which results from the smoothing of the little catchment basins within the extended valley coverage. In this study, the valley system has been taken into consideration and the generalizing decision has been made on the level of hydrological significance. Hence this approach, in contrast to the conventional algorithms which are based on the image processing, can more properly maintain the primary geographical characteristics and discard the fragmental ones.

An increasing number of applications of automatic extraction of building information have been taken in, such as in city plan, city development, military affairs, national defense, and high resolution remote sensing imagery provides these applications with new data sources. Based on differential morphological profile (DMP) algorithm in mathematical morphology, we introduce and develop a set of accurate and automatic scheme for figure information extraction, combining with MHN filter algorithm, region marking algorithm, area threshold segmentation algorithm and so on. First, the Maximum Homogeneity Neighbour Filter Method (MHN) was used to improve the quality of the image. Then, the derivative of the opening profile from the DMP algorithm of variable step size was in use for extraction of buildings' figure. At last, area marking and area threshold segmentation algorithm were introduced for post processing. DMP algorithm in classic definition requires constant step operator with different radius for differential. This means extraction of regular figure of buildings will get good results, but buildings with more complex shapes of will lapse by DMP. Aimed at the characters in the test field, we adopted a variable step size. By changing the constant step size for differential, our method can effectively detect not only buildings with regular shape, but also buildings with complex shape. In the end, accuracy evaluation was carried out for the extraction results in the test field and the precision reached 79.6%.

This article proposes a data structure of a 3D engine based on rapid indices. Taking a model for a construction unit, this data structure can construct a coordinate array with 3D vertex rapidly and arrange those vertices in a sequence of triangle strips or triangle fans, which can be rendered rapidly by OpenGL. This data structure is easy to extend. It can hold texture coordinates, normal coordinates of vertices and a model matrix. Other models can be added to it, deleted from it, or transformed by model matrix, so it is flexible. This data structure also improves the render speed of OpenGL when it holds a large amount of data.

A set of multi-flow direction algorithms for extracting drainage network form digital elevation model (DEM) based on ground water overflow model is introduced. As single-flow direction algorithms, the algorithms perform some tasks as following: depression identification and treatment; relief increment of flat areas; flow vector determination and drainage network. But in the flow vector determination process, we use multi-flow direction algorithm. We extract drainage network form a set of digital elevation model in Changsha, Hunan Province using this method to test these algorithms. The experiment result shows that these algorithms are efficient and avoid parallel currents, the shortcoming of single-flow direction algorithms.

This paper describes a method to estimate FAR based on SRTM3 data and land use data. SRTM3 is DSM which includes height of objects on ground than DTM, so we can get general height information of buildings in city to estimate FAR. In the paper, a method is designed as the buildings' height information is gotten from SRTM3, building density and floor height are gotten from investigation varied by land use types. Then a model is built to calculate FAR used of SRTM3 and land use data. A case study in Shanghai central city is done to test the feasibility and accuracy of this method. Finally we analyze the factors affects the accuracy of estimation and discuss some improvement.

The Lancang River Basin is so narrow and its hydrological and meteorological information are so flexible. The Rainfall, evaporation, glacial melt water and groundwater affect the runoff whose replenishment forms changing notable with the season in different areas at the basin. Characters of different kind of distributed model and conceptual hydrological model are analyzed. A semi-distributed hydrological model of relation between monthly runoff and rainfall, temperate and soil type has been built in Changdu County based on Visual Basic and ArcObject. The way of discretization of distributed hydrological model was used in the model, and principles of conceptual model are taken into account. The sub-catchment of Changdu is divided into regular cells, and all kinds of hydrological and meteorological information and land use classes and slope extracted from 1:250000 digital elevation models are distributed in each cell. The model does not think of the rainfall-runoff hydro-physical process but use the conceptual model to simulate the whole contributes to the runoff of the area. The affection of evapotranspiration loss and underground water is taken into account at the same time. The spatial distribute characteristics of the monthly runoff in the area are simulated and analyzed with a few parameters.

The existence of shoulder line is a typical and important characteristic of loess relief, which also plays a significant role in the study of loess landform and erosion process. The construction of a classification and quantifying indexes system are the essential work in the cognition of loess shoulder line. On one hand, along with the development of stream networks, shoulder lines extend themselves in the drainage area, the type and the indexes vary correspondingly as well; on the other hand, a specific type of a shoulder line and its character are the representation of gully development phases. High precision DEMs proves to be a suitable information source in the extraction of loess shoulder lines. Experiment in this study show that 5 meter resolution DEMs is available in extracting of loess shoulder lines after some specific processing. Mathematic morphological method is employed in the process to creating a consecutive shoulder line. Based on proper derivation method and the quantifying indexes system, a deep study of shoulder could be achieved. Shoulder line spatial distribution result is accordant to that of the loess relief character. The study of shoulder line temporal distribution gives an even deeper and comprehensive understanding to the development of loess relief development.

Iris feature extraction is the crucial stage of the whole iris recognition process. A brief introduction of iris recognition system is made firstly in this paper, then presented the method of iris feature extraction and matching using Scale Invariant Feature Transform (SIFT). Through analyzing iris feature extraction and matching method, we found in conventional iris recognition system, Iris features are not consistent because most feature extraction techniques are sensitive to the variations of captured iris image data, are impacted of natural illumination or other variant conditions easily. So this paper used SIFT feature which is invariant to image scaling and rotation, and partially invariant to change in illumination. They are also well localized in both the spatial and frequency domains. SIFT feature shows a higher feasibility in the iris feature extraction and matching process.

The spatial interpolation of meteorological elements has more important application value. The interpolation methods of air temperature data have been wildly applied in the large scale region. It has been paid more attentions that taking altitude as a variable was introduced into the interpolation models so as to improve the interpolation precision of air temperature data. In a large area, it is difficult to find the relationship between annual cumulative temperature and altitude according to the distribution of meteorological stations. Compared whit it dividing the study area, introducing interpolation models modified by DEM in the smaller region, we can availably improve the spatial interpolation precision of the annual cumulative temperature. The result shows that: Applied in the partition study area, inverse distance squared method modified by DEM can reduce complexity of spatial data analysis in the process of annual cumulative temperature interpolation. Partition interpolation methods take into account some factors that affect the interpolation results, such as the spatial distribution imbalance of the meteorological stations, altitude and region difference. The methods are fit for the interpolation analysis of the large-scale region. Compared with the tradition interpolation methods such as Kriging, Inverse distance interpolation method, etc., inverse distance squared method modified by DEM has higher interpolation precision of annual cumulative temperature in China.

A novel approach for camera self-calibration is addressed in this paper. It is well known that one of problems for camera self-calibration is the matrix of the dual image of absolute conic (DIAC) is must positive definite. Then calibration matrix can be gotten by cholesky factorization from DIAC. In this paper, calibration matrix is directly optimized with nonlinear method which means that the solution of DIAC matrix is not necessary. It can help us avoid the positive definite problem. The algorithm builds on the basement of projective reconstruction, and it includes two steps. Firstly, the initial value of calibration matrix can be estimated from the manufacture explanation, then initial guess of infinity plane vector is searched out. Secondly, 8 parameters containing calibration matrix and infinity plane vector are optimized with Levenberg-Marquardt algorithm. Experiments validate the method.

Difference is the key method for deriving topographic parameters from grid digital elevation model (DEM). Its accuracy is the vital factor affecting the accuracy of topographic parameters. The research validated that the accuracy of difference is associated with topographic surface complexity, difference algorithm, DEM data accuracy and DEM data property including grid orientation, grid size, grid origin and data precision. The high accuracy results of difference could not derived from small grid size DEM if there are DEM data errors. There is one and only suitability DEM grid size which the difference calculation has the least RMSE (root mean square error). The research further perfects the theory and method of accuracy analysis in digital terrain analysis.

The three-dimensional spatial description of city construction provides key relationships between the real world and the data model. In the researches of the essential attribute and existence about object, ontology plays an important role in the process of spatial description. It not only provides theoretical foundation for the composition of space entities, but also has a description about spatial relationships of the entities. As an important concept of ontology, Part - Whole itself is a kind of level spatial relationship, and is associated with the nature of the object. In this paper, the description level and the geometry definition of city construction according to the geometry characteristics of entities in space is presented based on the Part - Whole theory of ontology. Then, the relation between each level of three-dimensional spatial entities from two parts of the spatial relationship of ontology (horizontal relation and vertical relation) is analyzed. Next, a framework for describing three-dimensional spatial relationship of city construction based on the ontology is proposed. In the end, a prototype system is designed and realized.

It is difficult for traditional photogrammetry techniques to reconstruct 3D model of close-range objects. To overcome the restriction and realize complex objects' 3D reconstruction, we present a realistic approach on the basis of multi-baseline stereo vision. This incorporates the image matching based on short-baseline-multi-views, and 3D measurement based on multi-ray intersection, and the 3D reconstruction of the object's based on TIN or parametric geometric model. Different complex object are reconstructed by this way. The results demonstrate the feasibility and effectivity of the method.

Now, use close-range sequential images getting from ordinary digital camera to reconstruct building 3D model is becoming to a convenient, fast and economical method. In the traditional building 3D model reconstruction, always use feature points. Considering there are abundant of lines and planes on the building, a new method was carried out in this paper is that the automatic matching of line segments across images of scenes containing buildings, and the output is a 3D plane combination of the building. The system is largely line feature based, starting with line segments, matching, grouping, and proceed them to higher level features. The approach has been tested on a triplet of close-range sequential images of a common building in the campus.

Analysis and interpretation of spatial variability of soil salinity is a keystone in site-specific farming. To better understand patters of multi-scale spatial variability in soil salinity, soil samples (30 to 40 cm depth) were collected with separation distances of 0.04, 0.2, 1 and 6 km in the Yellow River Delta of China. Laboratory measurements of soil salt content were also made from these samples (n = 239). Moran's I autocorrelation coefficient was computed at preselected lag distances and correlograms were plotted to examine trends in autocorrelation. Spatial autocorrelation was found at scales ranging from 0.7 km to more than 75 km, depending on the sampling scale considered. A correlation range in regional scale appeared to be associated with elevation height, while a shorter range in field scale was likely influenced by alternating land use/land cover or microtopography types. Moran's I correlogram calculated with salinity data from all of the sampling locations suggested spatial pattern detection for soil salinity can be achieved with a sampling interval of approximately 2 km or less. The magnitude and spatial patterns of soil salinity have implications for devising appropriate schemes to improve land productivity and design of soil sampling strategies in the Yellow River Delta.

Arid area is classical mountain-oasis-desert ecosystem in North-west China. As the ecosystem has its nature geography character obviously, it has superior to research with remote-sensing and geography information system. The study on arid ecosystem in RS-GIS' way is focused on that the landscape spatial pattern of complex MODS ecosystem, the dynamic development of Land use/land cover, the security of ecological environment of eco-tone and so on. At the same time, the research on the single system is more and more, which has provided more ways and deeper fields of arid area using RS-GIS. Through the use of RS-GIS, desertification, oasis' development, urbanization etc. can be known, which would provide precaution for human-being and suitable ways to adjust the problems.

Digital Terrain Analysis (DTA) is an important way for interpreting and understanding natural landform. Scale, an essential subject for realizing pattern and process in nature, is a fundamental issue in DTA. River basins are the basic natural system of many hydrologic phenomena. Multi-scale analysis of channel network can explore structural characteristic and spatial pattern of drainage basin, make basis on drainage evolution and provide suitable scale for drainage research. This paper investigates the structural characteristic of channel network under multiple scales and finds out accurate critical points of scales. Two kinds of lacunarity algorithms, i.e. gliding box algorithm and 3TLQV are adopted. Several conclusions can be drawn from the experiments. Firstly, there are five scale patterns in WE direction and three scale patterns in NS direction in channel network of Jiuyuangou drainage basin. Each scale pattern indicates a kind of hydrologic process. Secondly, anisotropy is between WE and NS direction in channel network. Thirdly, at each scale examined there's fractal pattern and fractal dimensions in different scales have little difference. Fourthly, an effective way for interpreting spatial pattern under different scales is put forward and it can be used for other network, such as ridgelines, population distribution etc.

The ocean is multidimensional and dynamic in spatial-temporal structure, and effective marine data modeling and representing of marine multidimensional geographic information system is a new hot topic and challenge. This paper proposes a new dynamic real three-dimensional marine data model based on time series multi-surfaces. It utilizes various surfaces to model different marine water bodies and creates three-dimensional topologic relations of objects in marine environments, then uses time series snapshots to delineate dynamic changes. The model is tested in safety estimation of navigation and motion of marine objects, and proved to be effective for the ship navigation.

The arid and semiarid region of northern China is one of the most fragile regions in ecological environment. Humidity index that was proposed and recommended by UNCCD (United Nations Convention to Combat Desertification) was utilized to investigate the aridity tread and its variations from 1960 to 2000 in northern China by means of the daily observed datasets of 382 meteorological stations in China. Spatial-temporal changing principles and zonation variations of aridity trend of the region were quantitatively analyzed from spatial-temporal attribution, the severity, and the significant level test by using the ESDA (Exploring Spatial Data Analyst) and Mann-Kendall rank statistical test. The results indicated that: 1) the extent and severity of extreme arid, arid, semi-arid, arid sub-humid and humid climate zones in northern China fluctuated dramatically from 1960 to 2000; 2) the west part of northeast China, north part of northern China and mostly part of northwestern China tended to be wet;; 3) In 1960s and 1970s, the aridity trend in northern China was significant. But since 1980s, the humid extent increased distinctly, especially in the middle and west part of western China, where the humid tread in some part of the region was so evident that it exceeds the significant level test of 99%.

The trend prediction of urban construction land increasing offers a scientific basis for land use decision-making. The data analysis models such as the exponential model, the logistic model, the gray system model and the binary linear regression model are generally used in the trend prediction of urban construction land increasing. Due to the different requirement for data and various fitting models, the prediction results based on above models sometimes have some differences and can't be selected rationally when the difference is larger. The optimized combination model based on non-linear programming, taking the constrained condition of minimal error into account, can synthetically analyze and compare above mentioned single prediction model and reduce the error of construction land prediction. Taking Wuhan as an example, the exponential model, the logistic model, the gray system model and the binary linear regression model are used in this paper to forecast the demand for construction land of Wuhan in the year 2010, 2015 and 2020. Based on this, confirming the weight coefficient of the four prediction models in optimized composite model, optimized prediction result can be obtained. The results indicate that optimized composite model can simulate the trend of construction land increasing much better.

Rangeland in Inner Mongolia is an arid ecosystem with vulnerability. Anthropogenic activities especially over-grazing have been believed to be a leading factor shifting the vulnerability into actual degradation in the ecosystem. Net primary productivity (NPP) is an important indicator for vulnerability monitoring in arid ecosystem. In this study we use the vegetation photosynthesis model to estimate NPP of rangeland ecosystem in Inner Mongolia. The objective is to examine the spatial variation of NPP in Inner Mongolia and to highlight vulnerable areas for sustainable development. Several improvements have been done to the model especially in its parameterization. Land surface temperature required by the model was estimated from split window algorithm proposed for MODIS thermal band data. Using the MODIS image data and the ground climate datasets, we applied the improved model to estimate the NPP in 2003 in Inner Mongolia. Our results showed that mean NPP was 192.03gC m-2 Gr-1 in Inner Mongolia in 2003. Spatial variation of the NPP was very obvious. Very low NPP was observed in the western parts while relatively high NPP could be seen in the eastern and northeastern parts. For various type rangelands, temperate alpine meadow is the highest. Although the mean NPP of temperate steppe is not high, its area is the largest in Inner Mongolia, so it has the highest ratio to total NPP. Comparison of our NPP with similar studies from conventional methods confirms the accuracy of our estimation.

This paper presents methodology using dasymetric mapping from remotely sensed imagery, geographic information system (GIS), spatial analysis and spatial statistics to explore relationship between asthma and air pollution in the Pensacola metropolitan region of Florida. Health outcome indicators thought to be sensitive to increased exposure of airborne environmental hazards are mortality and morbidity rates for total population asthma patients. Environmental data for the time around the year 1999 include point source pollution sites and emissions, traffic count with emission estimates, and a Landsat ETM+ image. Standardized mortality/morbility ratios (SMRs) were used as dependent variables for the analysis. A centroid map was created from the zip code map with each centroid assigned the corresponding SMR values. Then spatial interpolation using the Kriging method was used to generate continuous SMR surfaces. An emission or point count based kernel density raster map was created from each of the air pollution maps. A raster layer 'greenness' was extracted using tasseled cap transformation from the Landsat ETM+ image. The dasymetric mapping technique was employed to limit the analysis and modeling to the area where human activities occur. The ETM+ image was classified into a thematic land use/cover map and the developed area extracted. A road network was combined with the developed area to generate a buffer (buffer distance=1.5 km). A random sample with enough number of points was generated across the study area and 505 points were found within the developed area and the buffer. Data values at these sample points were extracted and used for statistical modeling. Two spatial autoregressive models (spatial error and spatial lag) were fitted. Both models show relationship between the asthmas outcome indicators and air pollution (positive) and 'greenness' (negative).

Stability of the tidal flat in silt-muddy coast is the ability to keep its terrain from erosion under the ocean dynamic processes. Evaluating the stability of the tidal flat is one of the most important issues insediment dynamics research field , and has been attached more and more importance. Dongsha Sandbank is one of the largest sandbanks of the radial sand ridges, and serves as an important barrier to the inner sandbank and has a direct impact on the process of Tiaozini Sandbank merging into mainland. To evaluate the stability of Dongsha Sandbank will provide guidance for coastal zone environmental protection (such as environmental protection and coast protection, etc.) to make a rational use of tidal flat resources for sustainable development. In the study, 63 scenes of remotely sensed imageries from 1973 to 2007 were collected, taken by different sensors such as MSS, TM, ETM+, SPOT, ASTER and CBERS. GIS & RS technology was used in the stability analysis of Dongsha Sandbank tidal flat based on field investigation, RS classification and overlay analysis. Major relate factors such as sediment dynamic environment, tidal channel and tidal creek system were discussed in the paper. Some conclusion can be summarized as follows :( 1) Integral stability of Dongsha Sandbank tidal flat has been gradually declined from 1973 to 2007. This trend was embedded in two aspects: both area of stable tidal flat and maximum value of stability coefficient degraded. (2) Tidal flat with high stability is mainly distributed on the sand ridges of Dongsha Sandbank, and has an integrally contractive trend: in the mid-continental region, one region with high stability coefficient has been broken into two small parts-- the northern part has a southwards movement while the southern has a northern wards movement; within the north part, stability of the tidal flat reduced with the northwards movement of the shoreline; in the west part, the tidal flat is in an unstable state due to the lateral swing of Xiyang Tidal Channel and strengthen of tidal creek activity; and in the south part, the tidal flat has a low stability due to the unstable flow path of Doufuzhayaomen Tidal Channel.

This paper takes Nanjing city as an example, analyzes diurnal and seasonal characteristics of UHI by eight granule and sixteen scenes MODIS, respectively. The land cover index (LCI) has been constructed to get a quantitative analysis about the changes of land use/land cover how to affect the distributional characteristics of urban thermal space. The results indicate the diurnal intensity of UHI is stronger than night's no matter whichever season it happens, but different season has different UHI intensity. The strongest intensity of UHI happens in autumn, the second in summer, the third in spring, the last in winter. The most extensive in scope occurs in summer, the second in autumn, the third in spring, the last in winter. There are three centers of heat island in Nanjing, mainly locating in industrial region, not in commercial or residential region. The spatial distribution pattern of land use/land cover affects wholly the distributional pattern of the urban heat space. The difference of surface material's thermal and biologic feature is the essential reasons of surface temperature distribution difference. Artificial heat has important effect on heat island. The LCI can reflect surface soil water content and vegetation cover and explains the essential reasons that each land use/land cover contributes differentially to urban heat island. Such an index can allow changes in land use at neighborhood-scale to be input in the initialization of atmospheric and hydrological models, as well as provides a new approach for urban heat island analysis. The LCI of urban land use is smaller than that of water, forest and cropland. Smaller is LCI, stronger the intensity of urban heat island is. For a special region, LCI will increase gradually per unit area with higher urbanization level. At last, remote sensing scale how to affect UHI time and space character is discussed. The intensity and scope of urban heat island results are different with different remote scale. The intensity and scope using ETM+ are all lager than that using MODIS.

Based on the new idea of harmony for human with water, a macro strategy for the flood-control and for the lake storage during low water standing period in Dongting Lake watershed and the middle reach of Yangtze River is suggested in the paper under normal operations of the Three Gorges Reservoir. The strategy includes three components that the first region must maintain suitable water level through low construction projects to keep original scene for the natural lake and wetland in low water standing period, the followed is the construction flood storage when water level over the limitation level of the bank, the last one is the planning extended flood storage areas to regulate extreme floods like 1954, 1935 and 1931, as well as 1870. The strategy not only meets the sustainable development of human society, but can also protect the nature. It provides a new approach to basically moderating or effective solve various problems among human, water and land in the Dongting Lake area.

This paper aims to monitor desertification evolution of different stages and assess its factors using remote sensing (RS) data and cellular automata (CA)-geographical information system (GIS) with an adaptive analytic hierarchy process (AHP) to derive weights of desertification factors. The study areas (114°E to 117°E and 39.5°to 42.2°N) are one of the important agro-pastoral transitional zone, located in Beijing and its neighboring areas, marginal desertified areas in North China. Desertification information including NDVI and desertification area were derived from the satellite images of 1987TM, 1996TM (with a resolution of 28.5), and 2006 CBERS-(with a resolution of 19.5 m) in study areas. The ancillary data in terms of meteorology, geology, 30m-DEM, hydrography can be statistical analyzed with GIS technology. A CA model based on the desertification factors with AHP-derived weights was built by AML program in ArcGIS workstation to assess the evolution of desertification in different stages (from 1987 to 1996, and from 1996 to 2006). The research results show that desertified areas was increased by 3.28% per year from 1987 to 1996, so was 0.51% per year from 1996 to 2006. Although the weights of desertification factors have some changes in different stages, the main factors including climate, NDVI, and terrain did not change except the values in study areas.

The snow resources takes a very important part in the water resources especially in the arid and semiarid areas, plays a key role in the social manufacture, subsistence and environment, by the way, the flood caused by the snowmelt in the spring may result in the huge losing, so it is significant to take the accurate observation of snow information and snowmelt process monitoring. The limitation of the traditional "point observation" is unassailable, but with the completely application of RS, GIS and GPS ("3S") technologies, have gained revolutionary progress in the snow observation and the foundation of Distributed Snowmelt Runoff Model. Based on the "3" technology, this paper chose the Juntanghu Basin, which located in the North-Tianshan Mountains, as the representative study area, used MODIS data which has high resolution of time, spectrum and special, also imposed mass observation data of weather, hydrological and snow cover on the spot of the corresponding period, extracted the snow cover index and snow depth information, calculated the relevant snow information such as snow cover index, snow depth and its transformation, built the Distributed Snowmelt Runoff Model based on the GIS software exploited by ourselves, contrasted with the homologous observed data obtained in the field, the observation of snow information has a mean precision up to 0.9, and the average precision of the simulation of snowmelt runoff is up to 0.82.

With Binghai Road in Dalian city as an example, we quantitatively evaluated the subjective impressions of the beautiful satisfaction of environment of urban scenic road with different urban dwellers using the methods of Semantic Differential Method and Factor analysis. The results show that the conditions of scenic roads, the orderings of landscape and audience feelings of psychological environment account for a very large component in quantitatively evaluating the beautiful satisfaction of environment of urban Scenic Road.

With the singular development of Internet technique and 3DGIS as well as VR and the imminence demand of 3D visualization from Groundwater information management field, how to display, roam, anatomize and analyze of 3D structure of Groundwater system on Internet have become a research hotspot in hydrogeology field. We simulated the 3D Groundwater resource structure of Taiyuan basin and implemented displaying, roaming, anatomizing and analyzing functions on Internet by Java 3D.

The result of land use in coalfield is important to sustainable development in resourceful city. For surface morphology being changed by subsidence, the mining subsidence becomes the main problem to land use with the negative influence of ecological environment, production and steadily develop in coal mining areas. Taking Panyi Coal Mine of Huainan Mining Group Corp as an example, this paper predicted and simulated the mining subsidence in Matlab environment on the basis of the probability integral method. The change of land use types of early term, medium term and long term was analyzed in accordance with the results of mining subsidence prediction with GIS as a spatial data management and spatial analysis tool. The result of analysis showed that 80% area in Panyi Coal Mine be affected by mining subsidence and 52km² perennial waterlogged area was gradually formed. The farmland ecosystem was gradually turned into wetland ecosystem in most study area. According to the economic and social development and natural conditions of mining area, calculating the ecological environment, production and people's livelihood, this paper supplied the plan for comprehensive utilization of land resource. In this plan, intervention measures be taken during the coal mining and the mining subsidence formation and development, and this method can solve the problems of Land use at the relative low cost.

The Sustainable Development Information Sharing System (SDINFO) of China is a distributed information management network system composed of databases of different types. This system consists of one general data center and 19 sub-centers. Housing the information provided by sectional administrative authorities, the system contains 1 TB volume of data that can be shared in 224 fields of 37 categories under 5 major sectors. Of the volume, 30GB can be shared through the central system. This paper introduces the content of those data, then the system architecture, and presents the key technologies to manage the mass and varied data in the Sustainable Development Information Sharing System, which are laid emphasis on. These technologies include multiple resource data standardization and reconstruction technology, heterogeneous databases integration technology, mass spatial data manipulation technology, distributed information publication technology, and information search technology, which are all discussed in details in this article.

Along with the development of computer network, Grid has become one of the hottest issues of researches on sharing and cooperation of Internet resources throughout the world. This paper illustrates a new architecture of SIG-a five-hierarchy architecture (including Data Collecting Layer, Grid Layer, Service Layer, Application Layer and Client Layer) of SIG from the traditional three hierarchies (only including resource layer, service layer and client layer). In the paper, the author proposes a new mixed network mode of Spatial Information Grid which integrates CAG (Certificate Authority of Grid) and P2P (Peer to Peer) in the Grid Layer, besides, the author discusses some key technologies of SIG and analysis the functions of these key technologies.

In this paper a method that applied Voronoi diagram based on Delaunay triangulation to delimitate the area coverage of different seabed materials has been introduced to replace the manual delimitation for current chart products in China. Actually, the natural delimitation of seabed materials is always ambiguous or nonexistent at all. In order to make the result more reasonable, we can increase the sampling density or take another two effective measures: one is to establish buffer zones around Voronoi edges and intersections to describe the mixed sediment among the overlapped regions; the other measure is named as spatial division which uses Voronoi diagram twice to identify the percentage of spatial certainty at a seabed location. These methods have improved the practicability of traditional/digital submarine charts. Especially they have enhanced the capability of spatial analysis in Marine GIS.

This paper takes the Ebinur Lake region in Xinjiang as a study area. Based on summarized analysis of the monitoring index system and evaluation methods of desertification now available on hand, the concept of composite desertification has been resulted. Through time changed remote sensing image data, the status of desertification and information about dymanic changes had been obtained. The analytic results show: desertification area influenced by the single dominant factor accounts for 82.29% of the total land desertification area, while that of composite desertification accounts for 17.71%. From 2002 to 2005, the area of Ebinur Lake had reduced 322.5073 km², overall land desertification's area had increased by 7.18%, and that of composite desertification had increased by 133%. The process of land desertification changed on the same time: the area of wind-erosion and composite desertification increased, while that of salinization-desertification declined. The expansion of composite desertification extends from previous brush forest land and psammophytic forest land to other land types.

Soil and water conservation project in the loess plateau of China is focus on improving its feasibility with new technology. This paper discussed on the application of "3S" technology in a soil and water conservation project of selected small watershed of Jingjiahe, Loess plateau. The research presents an approach to apply RUSLE to quantify soil and water loss by the help of "3S" technology, the suitability evaluation for each piece of land is implemented with the assessment indices. Finally, according to the nature condition and economic development trend, by accomplishing the analysis of the comprehensive control benefits for the small watershed, establishing rational land use pattern. Through five years construction of soil and water conservation, the controlling soil erosion area up to 2369.98 hectares, harnessed degree reaches 80.66%, the per capita net income will float up from yen 944.72 to yen 1049.75, the annual preserved area of endangered soil will be 90,000t with the efficiency increased by more than 22%, eventually the soil and water loss shall be well under control. This indicates that "3S" technology make the work more cost-effective, more efficient and more reliable taking into account the precise data which are processed in the planning.

A new way called compositive inversion is presented in the paper to derive albedo over cloudy areas with multi-angular satellite remote sensing data. It combines complementary angular clear observations of pixels having same BRDF shape and directly retrieves BRDF parameters and albedo with RossThick-LiSparse Reciprocal model when the minimum multi-angular observations meet its requirement. Contrastive retrieval experiments with five continuous 16-day Terra MODIS data over the Tibetan Plateau (30 cases in total) showed that its retrieval capability is much higher than that of the magnitude inversion, a backup algorithm adopted by the U.S. BRDF/albedo products, and accuracy of its retrievals is rather equivalent to those with magnitude inversion. Since the unique ancillary data used in which is the land-cover type classification data, which is superior over a priori BRDF database, so the compositive inversion can give more accurate albedo information, and is an applicable and practical way to derive albedo of cloudy areas. The idea of compositive inversion provides a new way to derive albedo in shorter temporal cycle and a particular view for use of multi-angular remote sensing data to derive land surface information.

Potential evapotranspiration (PET) was estimated by applying Penman-Monteith Method recommended by FAO with climatic data from 96 stations during 1961 to 2000 in Xinjiang. The spatial and temporal variations of the potential evapotranspiration in Xinjiang are analyzed. The whole potential evapotranspiration has decreased in all seasons. The average annual evapotranspiration rate decreases by 29.87 mm/decade. Superimposed on this general decline are fluctuations with above average rates in the 1970s and 1980s. Decreasing PET rates are more pronounced in spring and summer as compared to autumn and winter. Through correlation analysis, the major climate factors that affect the temporal change of the potential evapotranspiration are analyzed. Changes in relative humidity and to a lesser degree wind speed and sunshine duration were found to be the most important meteorological variables affecting PET trends in Xinjiang while changes in temperature played an insignificant role. Negative evapotranspiration trends are thought to a general decrease under global warming scenarios.

Recently, "Global Change and Terrestrial Ecosystem (GCTE)" and "Land-Use and Land-Cover Change (LUCC)" have become the core project and the important direction of the global change research.. The land cover is closely related to the climate and they mutually affect each other. The paper created Zhejiang land cover change map based on MODIS Enhanced Vegetation Index (EVI) products and climate change maps. A study of the relationship between the land cover change and the climate change was conducted on the maps. The conclusion was the land cover change has the relation with the local temperature change in the certain degree, does not have the relation with the precipitation change and the humidity change.

The concept of GIS has experienced continues changes, from Geographical Information System (GISystem) to Geographical Information Science (GIScience), and then the development of Geographical Information Services (GIServices). Now, the concept of Geographical Information Services, which is in vigorously development, is the main stream of GIS development and the characteristics of the times. This paper expounds the GIS inevitable development trend from the Geographical Information System to Geographical Information Services, discusses service and research targets, methods and techniques, introduces a lot of successful applications of geographical information services research to the business and public daily life, furthermore, aggregates the existing problems in current geographical information services, and puts forward the suggestions and countermeasures to promote the quality of services and development of services.

The present study was conducted to evaluate the relationship between the growth of high quality rice and climatic conditions, climatic resources of high quality rice in Chongqing, climatic disaster and main eco-climatic factors impacting on the distribution of high quality rice. Guidelines were built based on this study. In addition, by using 1:25 DEM, spatial distributed guidelines and GIS technique, precision eco-climatic division of high quality rice was established.

Battlefield environment is a general designation for all kinds of objective things and conditions which surround battlefield and affect military actions. With the development of modern high technology, and information technology, traditional battlefield environment is developing in the both factors of space and constitutive, and takes on an integrated tendency. The U.S. military consider that the war of information age is NCW, and to successfully implement the theory of the NCW capabilities, the four domains of warfare-physical, information, cognitive, social, and their relationship must be understood. According to the theory of system, this paper puts forward the conception of Battlefield Environment System and its tetrahedron structure. The correlation of constitutive factors in Generalized Battlefield Environment System and the relationship between Generalized Battlefield Environment System and NCW are analyzed. Moreover, the spatial scope and constitutive factors of Specific Battlefield Environment System are also discussed.