During the past years, it is well known that data mining has made a lot of achievement in business-typed fields. In this case, the research emphasis on data mining and knowledge discovery has inevitably be shifted from non-spatial data into spatial data. Spatial data mining is is a key technology of "3S", as well as important research content of "Digital Earth". The first thing come into contact with is to decide tuples to be dealed with while carrying out algorithms concerned. In this paper, a new kind of tuple, which is named "mesh-shaped" tuple, is proposed. This kind of tuple takes on larruping characters, it has fields similar to spatial entity and attributes similar to pixel of images. To test feasibility of the new tuple, a practical study case is designed. The whole process of operation demonstrates how to use "mesh-shaped" tuple, and the results indicates that our technical notion is feasible and successful. The new tuple provides a novel technical means to spatial data, and this performance enrichs approach of spatial data mining. The research notion in this paper has shown its significance in science and applications.

With the development of digital city, 3D City Models (3DCM) are created and applied in more and more fields in recent years. In 3DCMs, buildings are the main components. The real-time visualization of large 3D city models requires the representation of the buildings in different levels of detail. Aiming at the automatic generation of multiple levels of detail of 3D linear building groups, this paper presents a generalization framework which extends the cartographic generalization algorithm mainly based on the operation of aggregation for the geometric simplification of linear 3D building groups. This framework is mainly composed of clustering buildings, the extraction of the generalization constraints, and generalization procedures. Experimental results illustrate that the proposed framework is useful to the real-time visualization applications of large-scale 3DCM.

3D spatial data model and modeling method is the core of 3D GIS application in different domains. There have been many 3D data models or data structures investigated in the past years. In geology exploration domain, most stratums are stratified and can be modeled by using multi-DEMs. In terms of a ore deposit, it is necessary to model its inner structures. For achieving this purpose, a modeling method based on Quasi Tri-Prism Volume (QTPV) can be adopted, which has the advantage of close integrating with samples data. Therefore, it is a feasible modeling method that adopting hybrid 3D data model based on multi-DEMs and QTPVs in the 3D modeling of geology body. In this paper, a hybrid 3D spatial data model based on multi-DEMs and Quasi Tri-Prism Volume (QTPV) is proposed. The proposed model is composed of six primitives and six objects. The primitives are vertex, segment (edge, triangle side), triangle, side quadrilateral, QTPV and DEMs, and the objects are point, line, face, solid, complex and spatial object. Data structures and topological relations of the six primitives and two geological objects are designed in detail. Two modeling methods, which are based on samples points and interpolation points, are designed separately. A set of simulation data and a set of real borehole sample data are used to verify the prototype system developed in VC++ program language by us. The research results show that the proposed model has better abilities of describing the surface and the inner structure of spatial objects, and it is suitable for 3D modeling in geology exploration field.

In recent years, the research on models of spatial relation computation can be divided into two types: the spatial relation among intersected entities and the spatial relation among the non-intersected entities. Currently, the latter is often used distance, direction and coordinate systems and other methods to study. But these quantitative methods are difficult to sympathize with human natural language understanding and space cognitive habits. Nature neighbor relationship is a vital space relationship. It can answer such questions as "Which hospital are adjacent to the moving object?" "Which schools are adjacent to the McDonald's shop?" In this paper, we analyzed two methods to compute the nature neighbor relationships: Voronoi diagram method and Delaunay triangulation method. We found the main problems for applying these methods to spatial selection are the overall and repetitive calculation. In some basic theory: (i) Define function f in order to distinct different types of triangle. According to the different sources of the nodes, the f is individually equal to 0, 1 and 2. And then the 3×3 matrix C is built on the f. According to the different values of |C|, we can divide the triangles as three types: α, β, γ. (ii) Taking into account that the triangles of type α is not entirely internal concave polygon, we divide the type α into type α and δ on the condition whether the polygon includes the focus of the triangle or not. Then the D(P) composed by Q includes four types of triangles: α, β, γ and δ. (iii) Demonstrate that the space scope of Q in R² is equal to the space scope of triangle set T of type α in D(P) , reasoned out the complement of Q in R² is equivalence with the set {Tβ union Tγ union Tδ} and the nature neighbor relationship can only exist in the set {Tβ union Tγ union Tδ}. (iv) For β and γ-type triangle we posed a subset of their sources and demonstrated the certainty in the context of natural subset of the space adjacent to the existing relationship, and regarded the space scope of every subset as a Unit, defined the structure of UnitsDelaunay and proposed the construction algorithm of the UnitsDelaunay. For the Quad GridFile: (i) Respectively approximated the Units composed of β and γ-type triangles by two methods of MBR of MCR and MBR. (ii) Demonstrated the completeness of the closure of the result set of point querying. (iii) Taking into account the update of GridFile, we proposed the Quad GridFile index structure, i.e. the structure added into quad tree spatial partition, replacing the update of structure by the reconstruction of GridFile structure, which the space scope of GridFile is represented by every leaf node. We utilized the extraction of candidate set of point spatial selection and self-join spatial selection as the instances. In the environment of Oracle 9.2.1 and Eclipse 3.1, we accomplished the proposed structures and related algorithm. Finally, we gave illustrations of the experimental results.

Spatial Information Multi-grid (SIMG) is regarded as a new method of spatial information expression considering the characters of nature and attributes of society. The focus of this paper is on a dynamic spatio-temporal expression for spatial information based on the framework of SIMG. Traditional Spatio-temporal Data Models (STDMs) lack enough abilities to meet the requirements of expressing and organizing spatial information based on the framework of SIMG. In this paper, the three characters (space, attribute, time) of SIMG spatial features are studied, systematic classification of spatio-temporal changes of SIMG spatial feature are described, and a Spatio-temporal Semantic Model based on SIMG is proposed.

This paper separates the GML document into structure and content according to the XML's semi-structure feature, and optimizes them individually. On the one hand, we adopt extending coding scheme based on full k ary tree to quantitate the nodes which present GML path information, then optimize the path expression with POEM(Path Oriented Extensible Model) to improve query efficiency. On the other hand, to GML contents stored separately as node sets, we study GML spatial index based on R-tree and establish GML spatial data index for spatial data. Concerning GML query, This paper considers that the key of GML query is how to deal with the spatial relational query,except for querying spatial data attribute. So by integrating the characteristics of spatial data, we give a suit of expanded query functions, including basic operation functions, spatial relational operation and spatial analysis functions. Finally we expand XQuery and realize a query system based on an opening source code software-XQEngine. Our experimental results show that the GML spatial query method based on full k ray tree expanding coding and R-tree spatial index can meet spatial query effectively.

With the widespread use of spatial data technologies, enormous and complex spatial data have been accumulated, thus the traditional GIS (Geographic Information Systems) spatial analysis methods are confronted with great challenges. Therefore, we need a new spatial analysis method of data-driven rather than model-driven, exploratory rather than reasoning. Spatial clustering, which groups similar spatial objects into classes such that the intra-cluster similarity is maximized and the inter-cluster similarity is minimized, is an important method of spatial data mining ^[1]. In the article, by virtue of Delaunay diagram, we propose a spatial clustering algorithm, which incorporates spatial relationships with non-spatial attribute. Then the objects whose characters are less obvious are classified into clusters that are more obvious and the precondition is that they are neighbouring, namely they must share the same Delaunay edge. Along with rescaling, the same spatial object presents different states of distribution. We show via experiment of a synthetic data set that our algorithm can integrate spatial relationships and non-spatial attribute. The obtained clustering result is highly consistent with that perceived by human eyes and is capable of recognizing clusters of arbitrary shape.

This paper briefly describes the structure and characteristic of large-scale streaming network in AM/FM/GIS, and dissertates in detail how to express the streaming network by complex nodes and complex arcs. At last, the paper illustrates how the network analysis works in applications.

By analyzing the characteristic and limitations of several typical spatio-temporal data models, the extension methods of improvement are presented for an event-based spatio-temporal data model in the paper. This model takes the current geographic state as the base, quickly recovers the spatial data of any past time. Because recording the changes of spatial objects and cause of changes, model can query spatial objects' historical data (geometric and thematic) and reason the changes of spatial objects. Separate storage and management of spatial data, thematic data and time is effective in reducing storage space and redundancy of data, improve the efficiency of query. Model can be implemented on object-relation database or extending static GIS database. An example about land subdivision is adopted to realize the data model. The instance indicates this model can quickly recover regional state, query time, space and attribute mutually.

Establishing a geospatial cyberinfrastructure is essential for the future development of geospatial information systems and services. Geospatial cyberinfrastructure will foster seamless integration of heterogeneous geospatial information, web-based mapping and geo-analytical services across the Internet. This paper will first discuss the significance of geospatial cyberinfrastructure for the GIS community and highlight several underpinning techniques of geospatial cyberinfrastructure, including Grid computing, Web Services, OGC (Open Geospatial Consortium) interoperability standards and Semantic Web. Emphasis is given to the discussion of developing intelligent and analytical geospatial information services in the geospatial cyberinfrastructure. An analytical problem solving multi-tier architecture is proposed as a theoretical foundation for the geospatial cyberinfrastructure. Part of the architecture is demonstrated by a simplified prototype which is used to test the feasibility of the proposed multi-tier geospatial cyberinfrastructure.

This paper describes an approach to compress the discrete data by triangle irregular network. Before conducting the compress, the triangle network should be built for the data. Two kinds of methods that creating the 2D and 3D TIN are introduced before introduce the mathematical model of compression. Since the compression threshold can not be decided by computer program, an algorithm and its procedure are described to complete the process of compression. Two cases are studied to show the results of compressions using this model.

Due to the rapid development of approaches to geographic representation, dynamic field model was derived in this paper. The dynamic field model is designed by taking the temporal dimension into account. It is further classified into two sub types of DCF (Dynamic Continuous Field) and DDF (Dynamic Discrete Field), which were designed in detail as well. After bringing forward the concept model of the dynamic field, the authors implemented it in PostgreSQL and input some pollution sampling data for testing. Running effects indicate the dynamic field works well for temporal operations and enhances the geographic representation, offering simple solutions to manipulation and complex analysis to spatio-temporal objects.

Data modeling is a baffling problem in 3DGIS, no satisfied solution has been provided until today, reason come from various sides. In this paper, a new solution named "Ontology method" is proposed. GIS traditional modeling method mainly focus on geometrical modeling, i.e., try to abstract geometry primitives for objects representation, this kind modeling method show it's awkward in 3DGIS modeling process. Ontology method begins modeling from establishing a set of ontology with different levels. The essential difference of this method is to swap the position of 'spatial data' and 'attribute data' in 2DGIS modeling process for 3DGIS modeling. Ontology method has great advantages in many sides, a system based on ontology is easy to realize interoperation for communication and data mining for knowledge deduction, in addition has many other advantages.

It is important to unify the model of geological structures with subsurface engineering structures in digital underground space (DUS). This paper puts forward a 3D model, feature constraints based (FCB) for DUS, which integrates the model of these two objects in the point of 3D continuous field of underground space. The FCB model describes spatial objects in DUS as composition of their features which is modeled from various constraints. A trial modeling system, ExpoDUS, developed with MS VC++ 6.0, MS Access and OpenGL, proves the feasibility of this model and demonstrates spatial query and analysis using actual data obtained from a key project of electric substation special for Shanghai Expo 2008 in China. Although designed to meet the requirements of underground engineering, our methodology could also be applied in superstructure modeling.

In this study, a marine and atmospheric spatio-temporal data model (MASTDM) based on satellite remote sensing has been developed to support the global oceanic and atmospheric research and application in the Marine and Atmospheric Geographical Information System (MAGIS). MASTDM conceptualizes the spatial distribution and temporal sampling of the satellite remote sensing data. The model has provided a mechanism service to store data and some subroutines to retrieve and manipulate data. These subroutines can be classified into the fundamental functions (definition, access, inquiry, export) and the advanced functions (transform, operation, validation and mend and etc). MASTDM is not only a solid foundation of the three modules (database management, spatial-temporal analysis and visualization) of MAGIS, but also a key to integrate these three modules seamlessly. In this paper, the conceptual and logical designs of MASTDM have been presented. A prototype system based on MASTDM has been implemented in MAGIS, it is also illustrated by some case study.

Recently, there has been a fast proliferation of applications creating spatio-temporal data that has to be processed, stored and queried efficiently. Consequently, there is a need for spatio-temporal data management systems that are able to support such storage or query operations. Spatio-temporal data management based on ORDB was derived in this paper. After bringing forward the structure model of spatio-temporal data management, one actual STDMS (Spatio-Temporal Database Management System) TspatialService was designed and then implemented. The system is based on data model of Dynamic Field and accomplished through spatio-temporal extension on PostgreSQL. Various spatio-temporal operations could be carried out in the system through simple SQL statements as well. By using the system, effective spatio-temporal data management was achieved.

GML is an XML encoding for the modeling, transport and storage of geographic information, which has been making a significant influential on the ability of organizations to share geographic information among their Web based GIS applications. Ontology has been acknowledged to be the kernel methodology for capturing and sharing semantics of spatial information. This paper proposes a framework for integrating spatial information based on GML schema matching by using ontology technologies, in which GML is adopted as the common format for spatial information wrapping and mediation, and ontology is used to overcome the heterogeneity when matching different GML schemas. A prototype is also implemented based on the proposed framework.

Metadata plays important roles in the description, definition and exploration of geospatial data, therefore, underpinned greatly geospatial data exchanging and information sharing. We proposed here a metadata-based method for modeling geospatial objects. In our method, geospatial data managing was divided into three phase within a data modeling hierarchy. Geospatial metadata modeling phase constructed geospatial information model which form the underground of geospatial data management. Geospatial data model development was based on it and defined the data object and relationship between each others. On the top of the architecture was open-ended tools and applications used to support metadata design, spatial data model design and domain-specific application development. An exemplificative spatial data model demo was presented to argue the availability of this methodology.

We introduce the challenges of address geocoding for Chinese cities and present a potential solution along with a prototype system that deal with these challenges by combining and extending current geocoding solutions developed for United States and Japan. The proposed solution starts by separating city addresses into "standard" addresses which meet a predefined address model and non-standard ones. The standard addresses are stored in a structured relational database in their normalized forms, while a selected portion of the non-standard addresses are stored as aliases to the standard addresses. An in-memory address index is then constructed from the address database and serves as the basis for real-time address matching. Test results were obtained from two trials conducted in the city Beijing. On average 80% matching rate were achieved. Possible improvements to the current design are also discussed.

When GIS are constructed primarily for the inventory and analysis of geographic phenomena, the data requirements for map production are often not considered. Such systems are also used to produce cartographic products including maps and mapping datasets. However, existing mapping systems built on GIS databases fail to make high quality map, mainly because most systems can not allow one to interactively change individual cartographic graphic representations to protect geo-data from modifications. This paper presents an alternative approach that considers the map requirements from the outset, then defines the unique characteristics and requirements for geo-cartography data to support a GIS-based cartographic system, as well as the process models to create the maps. Any representation is free to be intervened, and will not change geo-data. The geo-cartography data closes the relation between the geographic data and the cartographic data, and performs the function of describing the GIS connection tables or expression rules in visualization mechanism, and the function of supporting and saving the mapping edit in the map-making method. The cartographic representation adopts the geo-cartography data having been edited, not the default cartographic symbols, thus carries out map-making based on GIS, and is easy to renew maps.

It is troublesome to set the display parameters of every feature class in feature-based zoom view. In order to solve that problem mentioned above, this paper used some data to verify raster-based map information measurement, expanded raster-based map information measurement to vector map, and then discussed how to use information amount to automatically control feature classes' display or not, rather than setting all kinds of display parameters in advance. That adaptive visualization technology would dynamically calculate the current information amount in map view. If the current information amount was below the minimal allowance value, the more detailed feature class would be overlaid on view. The technology presented in this paper was more adaptive than that technology to set display parameters beforehand.

On the basis of analysis of the principle and nature of the two-dimensional Douglas-Peucker algorithm, this paper puts forward the three-dimensional Douglas-Peucker algorithm and applies this algorithm to the automated generalization of the three-dimensional discrete points or the basis of DEM. The last part of this paper introduces the verification experiments by computer programs for this new algorithm. Preliminary experiments have proved that the main geomorphologic feature points for both the general or local areas of the DEM can be correctly extracted with satisfactory computational efficiency.

Cartographic language has the characteristics of natural language. As the vocabulary in cartographic language, cartographic symbols are composed of exterior form and idealistic content. Geographic concepts are the essential attribute of geographic objects and cell of geographic thinking. Geographic concepts are thinking form of human brain and are invisible, which only needed to be represented by a certain form. Aiming at the problem of symbolic representation in geographic concepts and their mutual relationships, the geometrical composition of symbols of large scale topographic maps and the semantic and geometrical relationships among symbols were analyzed, the symbols system of topographic maps was regarded as a two-dimensional graphic language, and the relationship between symbols and geographic concepts was discussed. According to concept of logic and geometrical shape of symbols the represented categories of geographic concepts and their mutual relationships on the basis of symbols of topographic maps were defined and the actual examples were given, which provides the use for reference for studying cartographic language by logic method.

The symbology of the QR Code and the traditional techniques for recognizing the finder pattern of the QR Code were introduced and the disadvantages of these techniques were analyzed. Based on the symmetry of the finder pattern of the QR Code, an algorithm for locating the center of the finder pattern was proposed. By this algorithm, the center of the finder pattern of the QR Code can be located accurately even though one module of the QR Code image occupies only 2.8 pixels or the image is skewed seriously or the image is illuminated not uniformly.

Embedded GIS requires exigent real-time response. When the hardware platform is given, it can speed up the system response by suitably designing the physical storage format and creating high-activity index for the geo-spatial data. Region quadtree index is one of the common methods to make indexes for data. It is mainly used for expressing spatial hierarchical relationship in two-dimensional coordinates. According to the region access characteristics of geo-spatial data and customers' use mode, we use region quadtree to make indexes for geo-spatial data, and then design the file storage format based on quadtree access for embedded GIS. At last we give the performance analysis of the file storage format based on quadtree access, which shows its effectiveness in embedded GIS.

In order to handle massive spatial data quickly and efficiently, a superior solution is to store and handle them in parallel spatial database management systems under the environment of PC cluster at present, and thus its spatial partitioning strategy of data needs solving first. Hilbert spatial ordering code based on Hilbert space-filling curve is an excellent linear mapping method, and gets wider and wider applications in processing spatial data. After studying Hilbert curve, this paper proposes a new and efficient algorithm for the generation of Hilbert code, and it has overcome drawbacks of the traditional algorithm. Then Hilbert code is applied to spatial partitioning with the method of cluster analysis, and a concrete method is given, which fully considers characteristics of spatial data, such as the aggregation of spatial data, reduces the time of disks accesses, and achieves better performance by experiments than the compulsory partitioning of ORACLE Spatial based on X coordinate values and (or) Y coordinate values in subsequent parallel processing of spatial data.

As a process to find proper positions for annotations, annotation placing has been regarded as a difficult problem in automatic map making. Following accepted cartographic conventions, the objective of a good label placement is to display the geographic position of features with their corresponding text in a clear and harmonious fashion, and having no overlap most important. In this paper, we think that annotation can have two categories by shape. The first is named point locating annotation; the second is named line locating annotation. Both of them can be seen from a combinatorial optimization point of view. Our research first evaluates the heuristic Tabu Search (TS), and then applies this method to cartographic label placement. Lastly, based on an experiment made on 1/250000 topographic data of China, TS has proven to be an efficient choice, with the best performance in quality. And results show that labels of cartographic features almost have no overlap.

GIS is an application-driven and technology-guided specialty and it has become an important part of informational technology industry. The purpose of GIS talent education is to provide the talented person (theory-oriented and technique-oriented) for the digital society. So it is obviously market-driven. The multi-level, diversification and socialization of GIS application need multi-objective, multi-gradient and large-scale GIS talent education. The college is the dominating education department in China. So the college education modes have a strong impact on the quality of GIS talents. The curriculum design embodies intrinsic request of education goals and modes. So it should be flexible, diverse and multi-level in order to achieve the established goals. In this paper, we analyze the present situation of GIS education both home and abroad, find out the problems and their corresponding reasons of China GIS education, then put forward three goals of domestic GIS education and five education modes ("3+5" education modes). At last, we argue the basic frame of the curriculum design.

The field of research in the generalization assessment has been less studied than the generalization process itself, and it is very important to keep topological relation consistency for meeting generalization quality. This paper proposes a methodology to assess the quality of generalized map from topological relations consistency. Taking roads (including railway) and residential areas for examples, from the viewpoint of the spatial cognition, some issues about topological consistency in different map scales are analyzed. The statistic information about the inconsistent topological relations can be obtained by comparing the two matrices: one is the matrix for the topological relations in the generalized map; the other is the theoretical matrix for the topological relations that should be maintained after generalization. Based on the fuzzy set theory and the classification of map object types, the consistency evaluation model of topological relations is established. The paper proves the feasibility of the method through the example about how to evaluate the local topological relations between simple roads and residential area finally.

Spatial conflict resolution is an important part of cartographic generalization, and it can deal with the problems of having too much information competing for too little space, while feature displacement is a primary operator of map generalization, which aims at resolving the spatial conflicts between neighbor objects especially road features. Considering the road object, this paper explains an idea of displacement based on structural mechanics. In view of spatial conflict problem after road symbolization, it is the buffer zones that are used to detect conflicts, then we focus on each conflicting region, with the finite element method, taking every triangular element for analysis, listing stiffness matrix, gathering system equations and calculating with iteration strategy, and we give the solution to road symbol conflicts. Being like this until all the conflicts in conflicting regions are solved, then we take the whole map into consideration again, conflicts are detected by reusing the buffer zones and solved by displacement operator, so as to all of them are handled.

The majority of geography features has temporal attribute as well as spatial and other attributes and usually changes with time while the most of current GIS platforms are lack of the ability of dealing with space-time data. Dynamic display model advanced in this paper is the display manner which takes time as variable and visualizes the dynamic situation of geography features following time. The shape and position of geography features in the interim could be interpolated according to the given features. The features mentioned in this paper are 2-D polygonal shapes which are used to express area features in GIS. The combination of dynamic display model and GIS enhances the expression and analysis ability of GIS and provides the new approach to geographical research on temporal dimension.

Over the past decades, wavelet transformations are widely applied to seismic data processing, image processing, sound processing, and so on. In contrast, less attention is paid to wavelet-based simplification of geometrical elements, e.g., iso-contour simplification. This paper is intended to explore wavelet-based line simplification for the purpose of map generalization. Iso-contour simplification is taken into account. After making wavelet transformations of the iso-contour, the wavelet coefficients at certain level are tailored with a threshold. Innovatively, the threshold is evaluated by the extended radical law of Topfer and Pillewizer. Furthermore, the threshold is evaluated differently with the three-level importance of an iso-contour. The multilevel wavelet transformations of the iso-contour are performed, and the wavelet coefficients are thresholded at each level. Through a reverse transformation of tailored wavelet coefficients, a simplified iso-contour is obtained. Without the consideration of relationships between iso-contours, the generalized iso-contour map is a set of simplified iso-contours. The experiment of iso-contour generalization has shown the feasibility of wavelet-based line simplification by tailoring wavelet coefficients with a map scale-derived threshold.

Movement in a spatial system is produced and determined by the structure of the complex space itself, rather than special attractors within the whole spatial system. Based on this theory of space syntax, tourists' convergence and dispersal in the Palace Museum should be originated by the distribution of the internal constructions form. This article presents an application of the space syntax approach to the Palace Museum. After analyzing its internal spatial configuration, as a conclusion, the paper provides some rational advices so as to facilitate tourists as well as protect our invaluable cultural heritage.

Rendering complex building scene like ancient architecture heritage is always a difficult work since there is very high occlusion ratio. According to the architectural structure and the data organization strategy of 3D ChiLin models, a new occlusion culling algorithm is proposed, which is based on the normal line grouping of the models concerned with the building features. By integrating with other accelerate methods such as frustum culling, detail culling, LOD and classifying rendering, this algorithm can improve the rendering speed efficiently.

Spatial relationship is an important research area in GIS. The orientation information about the urban environment is directly available to human beings through perception and is crucial for establishing their spatial location and for way-finding. People perceive the layout of entities in space, categorize them as spatial relationships, and describe them as spatial expression in language. The orientation expression in different language is different. This paper will discuss the road network in Beijing and its characteristic. We analyze the post-position in Chinese, we know that people like to use 'outside' and 'inside' in the sentence "N is + ring road + postposition" by first experiment. We will illustrate the fuzzy range by 'outside or inside' in the ring-road by the second experiment. In the last part, we conclude the paper and our further research.

Hydrography and cartography is an important part of Geoinformatics, and it is the basic technology of ocean resource exploitation and utilization. In this paper some new techniques development situation of hydrography and cartography in China is introduced. The unification of marine and land datum, precision rectification of the marine remote sensing images, satellite altimetry and remote depth, the ocean delimitation, virtual reality and pattern recognition etc. are discussed as principal research contents. The situation and multi-expressing of marine surveying information processing are expounded at last.

Traditional GIS has many flaws in managing distributed, large-scale, heterogeneous spatial data. Nowadays, more and more countries build their own spatial data grid to provide abundant data services. But data grid system is a complicated one and involved in lots of entities which are different in many ways, including type, performance, runtime environment, etc. It is necessary to divide the whole system into different layers, which has great importance to simplify the system complexity, improving system stability and establish an efficient, extensible, self-adaptive and self-organizing system. Here, after carefully analyzing various system entities, the article describe the idea that entities are divided into three kinds service-type entities, management-type entities and draw-type entities that is the basis of clear level classification of the spatial data grid and establishment of a mixed three-tier architecture based on grid computing and P2P technologies.

By analyzing the specific requirement and practical procedure in digital cartography field, in this paper we put forward an improved algorithm for buffer zone analysis and propose a method of applying the buffer zone analysis algorithm to the process of conflict detecting and solving between spatial features. The principle of this method has been elaborated and examples of its practical application in the cartographic system based on national basic geographic data at the scale of 1: 250,000 have been presented. It is approved that this method is effective.

Least squares method is one of the effective and widely used data process tool in statistical based data analysis. Automated map generalization is an intelligent process in nature, which involves mining the knowledge from the original data sets to form the generalized features that are the abstracted representation of the original features in multiple and different scale levels. In this paper, we present an integrated methodology for the automated generalization of settlement areas based on least squares adjustment. Taking the original data sets of the features as observational values, the parameters representing the generalized features are computed according to the least squares adjustment model. The four-level hierarchical model for settlement area generalization is first proposed. The rules and constraints conditions in settlement area generalization are then described, and the least squares adjustment model is derived in settlement areas generalization. The results of practical tests demonstrate that the validity and feasibility of the proposed model for the simplification of settlement areas in geographic information system.

Evaluation of spatial data quality is an important problem in Geographical Information System (GIS) applications and research. Many evaluation criterions of spatial data are involved in the evaluating process, The criterions for judging the quality of spatial data comes from the evaluation process, using such information as positional accuracy, attribute accuracy, logical consistency, temporal accuracy and so on. How to evaluate the quality of spatial data based on these indexes is a problem we are always confronted within GIS applications. In this paper, we construct a model for determining spatial data quality using attribute recognition principles and methods in Attribute Mathematics, which were founded by Cheng Qiansheng. This model overcomes the defects of current evaluation models, and leads to reasonable and reliable results on spatial data quality in GIS as proved by the results of our tests.

With the advent of Earth Observation Program, the speed of data accumulation and update is getting faster than ever. However, the gain of the knowledge from the data has not been progressed as what is expected while the data volume is getting immensely huge. Knowledge discovery from database (KDD) is a feasible method to solve this contradictive problem of "the lack of knowledge while data getting explosive". In addition, the uncertainty in the Remote Sensing Science is worth of being investigated as well due to the fact that the remotely sensed data may be collected under various circumstances, which resulted in multi-sourced information. The process of acquiring the data is another factor impacting the data quality, because the transmission of the signal is affected by all kinds of uncertain factors. Thus, uncertainty is an inherent property of the Remotely Sensed data(Michel Crosetto, 2001). As a graphical model for the probabilistic relationships among a set of variables, the Bayesian network has become a popular representation for encoding uncertain expert knowledge in KDD domains over the last decade(Datcu and Seidel, 1999; Marcot et al., 2001; Murphy, 1998). The Bayesian method integrates a prior knowledge about the objects under study and the information provided by new data set, followed by encoding the multi-knowledge into conditional probability network model. Thus, Bayesian network in conjunction with Bayesian statistical techniques facilitates the combination of domain knowledge with the relevant data. Theoretically, the updated information is weighted by the prior knowledge together with the information induced by the new data, and the uncertain knowledge has been considered as the probabilistic causal relationship among parameters(Chan and Darwiche, 2005). This paper investigates the causal relationship between Bidirectional Reflectance Distribution Function(BRDF) and some other earth surface status parameters, such as the type of land objects, the temporal factors of vegetation growing(e.g. phenology period) and the planting structural parameters(e.g. Leaf Area Index(LAI), Leaf Angel Distribution(LAD))(Li et al., 2001; Marie Weiss, 2000). By learning the Bayesian network parameter from the database, the associated knowledge on the reflectance on characteristic band of BRDF and the earth surface parameter are established. This type of knowledge can be used as the constrained factor named soft-bound in land surface parameters inversion algorithm. As illustrated, using KDD technique under Bayesian network to discover the uncertain knowledge from Remotely Sensed database can help accumulate the prior knowledge and support the application of vegetation parameters inversion.

A new field of technology, GIS has emerged with the development of computer technology and is now in a state of drastic evolution and development. This research discusses the present situation of the overall GIS field, the development of GIS, and features of the present development of GIS technology. It also investigates and analyzes relevant issues, such as the uncertainty in topological relations which is caused by the inaccuracy of, and uncertainty in, GIS spatial data, spatial reasoning, spatial searching, spatial-searching language, the theoretical development of topological relations, the trend of GIS development, and the problems in the development of GIS in the 21^st century.

Schema Matching is one of key steps in GIS client database updating. In order to find semantically similar elements between schemas of master database and client database, an approach based on instance statistical similarity is presented. Different instance comparing technologies, such as correlation analysis, edit distance calculation, are used to determine the similarity of schema elements. Unlike other schema matching methods that only focus on attribute-level matching, our method adopts a hierarchical strategy to determine mapping relationship form two-level schema elements including feature classes and attributes. Experimental result is also presented to demonstrate the viability of this approach.

There are much uncertainty in the process of image segmentation, The paper firstly researched the sources of uncertainty of image segmentation; and then analyzed the method of image segmentation based on K means cluster, and the method based on fuzzy K means cluster; and then, the paper researched the theory of cloud model, which considers the fuzziness, random and the their association of uncertainty. The paper put forward a new method of image segmentation based on cloud model. Lastly, the experiments proved the method of image segmentation based on cloud model is better than the method based on fuzzy K means cluster and the method based on K means.

Coastal zone geographic information is coastal zone spatial data including remote sensing images, digitized maps or charts and various surveying and statistical data. With the development of Digital Earth, coastal zone geographic information is changing from plane, static and isolated to three dimensional, dynamic and associated. However, there is no comprehensive, compositive and dynamic study on processing of coastal zone spatial data. Mathematics base is the basic study on multi-expressing of coastal zone geographic information, which includes coordinates system and projection system. The influence of geodesy surveying datum system is expressed through the plane coordinates system and vertical datum system. According to digital maps, remote sensing images and three dimensions terrain sight, there are three typical projections: static map projection, dynamic space projection and three dimensions perspective projection. The mathematics base can be unified to ellipsoidal geographic coordinates. Coastal zone geographic information multi-expressing system (CZIMS) is explored in VC++ programming language, and the integrated structure of CZIMS is discussed. The key technologies including coastal zone vector map display, remote sensing images processing and three dimensional terrain building are studied. The system is developed to provide real-time, dynamic information and multianalysis for coastal zone monitoring and management.

Land use drivers that best describe land use patterns quantitatively are often selected through regression analysis. A problem using conventional statistical methods in spatial land use analysis is that these methods assume the data to be statistically independent while spatial land use data have the tendency to be dependent, known as spatial autocorrelation. Two different scales of study area, Fujian Province and Longhai county are selected. In this paper, Moran's I is used to describe spatial autocorrelation of dependent and independent variables and spatial autoregressive models which incorporate both regression and spatial autocorrelation are constructed. 5 main land use types in Fujian Province, 9 main land use types in Longhai county and all candidate land use driving factors show positive spatial autocorrelation. The occurrence of spatial autocorrelation is highly dependent on the aggregation level. Results also show that spatial autoregressive models yield residuals without spatial autocorrelation and have a better goodness-of-fit. The spatial autoregressive model is statistically sound in the presence of spatially dependent data in contrast with the standard linear model.

Digital map conflation is a methodology to reconcile discrepancies between two datasets to get a new and consistent dataset. The new dataset may have high positional accuracy or rich attributes. Conflating urban maps needs to reconcile coordinate discrepancies and simultaneously preserve some characteristics of features. This should depend on various departments' requirements. This paper introduces an least square adjustment approach for map conflation. It regards those demands as different observations and applies parameter adjustment method to solve the equation system. This method is tested on some maps and compared with other popular methods. The test results show that this approach can bring about good result on positioning features and has an excellent ability to maintain characteristics of features.

In the domain of GIS, large amounts of geographic data are increasingly shared, interchanged and analyzed in many different applications. Mobile GIS technologies bring lots of advantages for field survey and the datasets acquired by field based data collection in Mobile GIS are often employed for many purposes. Therefore, to ensure the quality of the collected datasets and tell the data users information about how reliable the datasets are, more concerns have to be contributed to spatial data quality issues. This paper will describe the open architecture of field based Mobile GIS and show the importance of spatial data quality issues. Then it explains how the spatial data quality concerns are considered for Mobile GIS aligning with international standards in geoinformatics, like ISO and OGC standards. Geographic data modeling with emphasis of spatial integrity constraints will be introduced here. In order that field users can simultaneously receive the warning of errors when they are entering the data in the field and correct them through seeing the reality, the data quality assurance work should be seamlessly integrated into the Mobile GIS. Therewith, the method of applying the spatial integrity constraints into the data collection work will also be explained.

Integrated analysis of Heterogeneous spatial data sets is becoming an increasing focused and important issue in geographical information sciences at present. More and more interdisciplinary projects need the integrated analysis of heterogeneous spatial data sets from multi-sources with different quality. Especially with the development of remote sensing technology, how to make full use of the huge spatial data and how to integrate them with available history data and statistical data attract more and more attention. In this paper, the heterogeneous data integration of vector data and imagery is discussed, and a new method using fuzzy reasoning in GIS is put forwards to integrate the former vector land use data and present remote sensing imagery. One example experiment for Changling County in Northeast China with the above-mentioned method is described in detail. In the example, the real change information of earth surface is extracted exactly because the uncertainty imported by other factors is removed.

People usually use qualitative terms to express spatial relations, while current geographic information systems (GIS) all use quantitative approaches to store spatial information. The abilities of current GIS to represent and query spatial information about geographic space are limited. In order to incorporate the concepts and methods people use to infer information about geographic space into GIS, research on the formal model of common sense geography becomes increasingly important. Previous research on the formalizations of natural-language descriptions of spatial relations are all based on crisp classification algorithms. But the human languages about spatial relations are ambiguous. There is no clear boundary between "yes" or "no" if a spatial relation predicate can express the spatial relations between objects. So the results of crisp classification algorithms can not formalize natural-language terms well. This paper uses a fuzzy decision tree method to formalize the spatial relations between two linear objects. Topologic and metric indices are used as variables, and the results of a human-subject test are used as training data. The formalization result of the fuzzy decision tree is compared with the result of a crisp decision tree.

By extending the traditional land suitability evaluation from natural conditions evaluation to land eco-economic comprehensive suitability evaluation, the evaluation factor system is created from three levels, which are regional level, unit level and inter-unit level. Meanwhile the quantitative criterion and methods are developed from four classes: positive factor, negative factor, moderate factor and qualitative factor. Based on these, the land eco-economic suitability evaluation model is proposed on the basis of fuzzy close-degree analysis. In the end, Huangpi district of Wuhan city is taken as an example to have a case study. The result shows that the model is reasonable and applicable.

A new map projection according to the normal of ellipsoidal surface is proposed in this paper. In this projection mode, the ellipsoidal surface can be approximated mathematically by a series of continuous secant facets which are all isosceles trapezoids. Every projection plane is just a secant facet projected by two geodetic parallels and two meridians in each coordinate grid, latitude and longitude intervals of which can be determined by the map scale. The projection formulas which can be applied to transform geodetic coordinates of any point on the ellipsoid into rectangular coordinates on the plane are deduced, and the method and formulas of joining four map sheets are also given. The results of the experiment on 1:50000 map sheets indicate that all kinds of projection distortions are very small in each map; the slits between two map sheets are so small that they can be ignored; and coordinates of different map sheets after joining can be used as the spatial measurement.

Despite developments in error analysis for discrete objects and interval/ratio fields, there exist conceptual problems with the case of nominal fields. This paper seeks to consolidate a conceptual framework based on the discriminant space for categorical mapping and error modeling. The discriminant space is defined upon the essential properties and processes underlying occurrences of spatial classes, and lends itself to geostatistical analysis and modeling. The discriminant space furnishes consistency in categorical mapping by imposing class-conditional mean structures that are associated with discriminant or "environmental" variables in various statistical models, and facilitates physically interpretable and scale-dependent error modeling. Further research will focus on models and methods based on multi-dimensional discriminant space and at multiple scales.

As a neural approach, fuzzy ARTMAP has the capability to resolve the stability-plasticity dilemma, i.e., incorporate novel information but preserve significant past learning. In this paper, we propose two non-parametric algorithms for the fuzzy ARTMAP to provide soft classification outputs. These algorithms, which are triggering-frequency-based and are called ART Commitment (ART-C) and ART Typicality (ART-T), expressing in the first case the degree of commitment the classifier has for each class for a specific pixel and in the second case, how typical that pixel's reflectances are of the ones upon which the classifier was trained for each class. To evaluate the two proposed algorithms, soft classifications of a SPOT HRV image were undertaken. A Bayesian posterior probability soft classifier, Mahalanobis typicality soft classifier, SOM Commitment and SOM Typicality measures were also used as a comparison. Principal Components Analysis (PCA) was used to explore the relationship between these measures. Results indicate that similarities exist among the ART-C, SOM-C and a parametric Bayesian posterior probability classifier, and among ART-T, SOM-T and a Mahalanobis typicality classifier. Additionally, ART models distinguish themselves from all other four models due to its special properties.

The inherently spatial uncertainty of many geographic objects has been the target of several, though still limited number of, studies. Two types of uncertainties, namely fuzziness and randomness, have been formally characterized within the framework of fuzzy set and probability theories, respectively. However, the scale issue has not been explicitly considered in modelling vagueness, whilst it is true that the degree of uncertainty of many objects is in relation to the scale of its representation. Furthermore, though fuzzy data types have been there for some years, a computational framework for handling fuzzy spatial objects is still lacking. In this article a previously introduced neural representation of polygon layers has been generalized to represent not only polygons but also points, lines, and complex combinations of these in the hard (crisp) and fuzzy domains. Two types of neural units, combined with two types of activation function, were identified as the processing core of the model, where the activation function can be either hard or fuzzy. In the hard case, we show how it is possible to differentiate among interior, exterior and boundary of a polygon by using a tri-valued activation function instead of the binary function originally used. The generalization to fuzzy domains can be implemented in computers, allows hierarchical constructions of complex objects from basic ones and allows us to build upon traditional spatial databases (with crisp boundaries). It is shown how the degree of fuzziness may be related to the scale of the representation under the premise that a decrement in the degree of fuzziness may lead to new details becoming apparent in the boundary. Indications on how to perform a complex overlay of fuzzy maps are also provided.

The interface of fluids can develop corners and discontinuities while it advances. The Level-set method is one of the most popular methods used for the problem of tracking a propagating interface. The Fast marching method (FMM) is an effective method for monotonically propagating fronts. In this paper we present an o(n) improved level-set algorithm. This new method is based on the narrow band approach as in the FMM. However, it uses a multi-point correction strategy to advance a group of grid points at a time, rather than sorting the solution in the narrow band, to march forward to a single grid point, and then update the rid points one by one. The numerical results by two and three dimensions, shows the validity of the new method. This method has been applied to the tracking of an interface in a dynamic virtual environment.

The object-oriented GIS data model enables the specification of applications not only to be a more accurate representation but also to incorporate "intelligent" objects into an analytical framework through their associated behaviors and methods. In this paper, a specific logical data model incorporating the decision-making support techniques is designed in the object-oriented approach, in order to restructure the NEG basic models for this research case to support the empirical explorations of self-organizing urban systems of Eastern China; furthermore, this logical model is directly mapped into the ArcGIS geodatabase data model within the framework of relational database technology. A prototype GIS software system for simulating urban hierarchy of study case in the environment of object-oriented GIS is proposed.

In this paper, we proposed a method based on GA to solve the path-optimization problem. Unlike the traditional methods, it considers many other factors besides the road length including the task assignment and its balance, which are beyond the capability of path analysis and make this problem a Combinatorial Optimization problem. It can't be solved by a traditional graph-based algorithm. This paper proposes a new algorithm that integrates the Graph Algorithm and Genetic Algorithm together to solve this problem. The traditional Graph-Algorithm is responsible for preprocessing data and GA is responsible for the global optimization. The goal is to find the best combination of paths to meet the requirement of time, cost and the reasonable task assignment. The prototype of this problem is named the TSP (Traveling Salesman Problem) problem and known as NP-Hard Problem. However, we demonstrate how these problems are resolved by the GA without complicated programming, the result proves it's effective. The technique presented in this paper is helpful to those GIS developer working on an intelligent system to provide more effective decision-making.

The selection of base vectors is important to linear expression of hyperspectral imagery. There exists several techniques for determination of representative vectors, but the selected results of them cannot act as good base vectors in usual. In this paper, a base vector selection method is constructed based on iterative weighted eigenvector fitting (IWEF). Beginning with an initial combination of vectors, the method tries to substitute each vector for each selected vector to reduce the fitting error. This procedure is iterated until no more valid replacements are done. In order to further reduce its computational cost, principal component analysis and kernel trick are used in data preprocessing. Experiments on synthetic data and on truth hyperspectral data prove the efficiency of the proposed method.

The biodiversity conservation and management of the salt marsh vegetation relies on processing their spatial information. Nowadays, more attentions are focused on their classification surveying and describing qualitatively dynamics based on RS images interpreted, rather than on simulating and predicting their dynamics quantitatively, which is of greater importance for managing and planning the salt marsh vegetation. In this paper, our notion is to make a dynamic model on large-scale and to provide a virtual laboratory in which researchers can run it according requirements. Firstly, the characteristic of the cellular automata was analyzed and a conclusion indicated that it was necessary for a CA model to be extended geographically under varying conditions of space-time circumstance in order to make results matched the facts accurately. Based on the conventional cellular automata model, the author introduced several new conditions to optimize it for simulating the vegetation objectively, such as elevation, growth speed, invading ability, variation and inheriting and so on. Hence the CA cells and remote sensing image pixels, cell neighbors and pixel neighbors, cell rules and nature of the plants were unified respectively. Taking JiuDuanSha as the test site, where holds mainly Phragmites australis (P.australis) community, Scirpus mariqueter (S.mariqueter) community and Spartina alterniflora (S.alterniflora) community. The paper explored the process of making simulation and predictions about these salt marsh vegetable changing with the conditions optimized CA (COCA) model, and examined the links among data, statistical models, and ecological predictions. This study exploited the potential of applying Conditioned Optimized CA model technique to solve this problem.

A distributed hydrological model incorporating the catchment's spatial information including topography, land cover and soil, was developed in this paper. The proposed model splits the concerned catchment into a series of sub-catchments linked with stream networks derived from digital elevation model. A revised TOPMODEL, which includes a forest canopy sub-module to descript the temporal and spatial heterogeneity of forest cover, was used to simulate runoff processes of each sub-catchment. The model was implemented to fully integrate with Arc/Info and input parameters derived from remote sensing images could be generated effectively through the geographic information system. The model was applied to a case study in the QingJiang river basin, which is one of the largest catchments in the middle reach of the Yangtze River. The voids-filled SRTM DEM was used to derive stream networks and topographic information including area, topographic index distribution of each sub-catchment. Land cover and LAI products of MODIS incorporated with the FAO global soil map were used to derive other relative model parameters. The model was calibrated and validated with observed hydrological datasets and the result indicates that the model can simulate reasonably well the runoff hydrograph and a distributed hydrological modeling system integrated with GIS and remote sensing has a great potential for both research and application.

In this paper, a comprehensive study for the evaluation and simulation of regional carrying capacity has been presented. After constructing the modified operational framework for regional carrying capacity evaluation and the indictor system, the Bohai-Rim region in northern China is taken as an example to implement the theoretical system: (1) Database is constructed and the data preprocesses have been performed based on GIS; (2) the assimilative capacity, supportive capacity and loading have been evaluated by using principal components analysis (PCA) and ecological footprint method; (3) then, the carrying states of 1996~2003 have been evaluated by statistical analysis; (4) future carrying states of 2004~2020 are forecasted by using ANN-based CA model.

Recently, the study and application of GIS, RS and GPS and their integration have developed very quickly in China. Strong employment market demand for RS professional employees is expected and RS education or training becomes urgent. However, when the students graduate, a large amount of them will find it is difficult to gain a proper job in this field. How to change the situations is critical for sustainable development of RS education and training in China today? The problem might be improved by emphasizing employability and practice in RS education. This article has four parts. First section is introduction of current existing condition. In section II, the research will analyze problems of RS education and training in China. There are three main problems as follows. Many students are lack of employability, and their practicing training is insufficient. Students and Staff are less mobile and vocation qualification system is imperfect. Long-Term Interaction is lacking among universities, enterprises, and different areas or countries. Solutions are discussed in section III. It emphasizes promoting employability and international competition by occupation qualification system of RS. And RS education and training should be guided by employment opportunities and promoted by employment market demands. It should increase diverse laboratories and field exercise bases for practice. Finally, strengthening Long-Term Interaction of RS education conclusions should be made. The most important is to carry on the quality education centering on social sustainable development, and to emphasize employability and practice in RS education and training in China today.

Visibility analysis is an important aspect in terrain analysis. Terrain visibility calculation is a time-consuming process, and visibility algorithms are dedicated to reduce the algorithm complexity to enhance calculation speed. We use digital elevation model to represent terrain. This equal-distance discrete data structure can be processed by geometric algorithm. The paper judges line of sight (LOS) visibility through geometric vector cross product, then delivers an incremental method to calculate terrain visibility with comparison of elevation difference using increments base on grid size. We analyze the algorithm performance in two aspects: horizontal and vertical comparisons. Through vertical analysis, the run-time of the algorithms has been measured for different terrain configurations and different heights of the viewpoint in terrain region. The method is more simple, lower complexity and easier to realize. We give out many computational results of viewshed with different location, and analyze the their distribution characteristics. We conclude that this method have high efficiency in undulant terrain with long line of sight or deep valleys. Also we compare this method with ARCGIS viewshed function horizontally through many tests and find that incremental method is faster and finer than ARCGIS model.

Hydrological model is very significant for the runoff simulation and flood prediction. Compared with lump hydrological model, distributed hydrological model has more specific physical mechanisms which consider the spatial non-uniformity of hydrological parameters in the river basin. Because of its complex space-related parameters, DHM is not easy to be constructed in conventional ways. The method and technology to realize DHM in practice have become the major bottleneck that has been restricting DHM construction. This paper proposes a new method for the construction of DHM based on GIS and RS. According to the method, GIS is not only adopted to extract the subcatchment and drainage system in river basin from DEM, but also applied to divide the hydrological subunits and to manage the space-related parameters. Multi-source remotely sensed images are utilized to acquire the parameters of all hydrological subunits distributed in the river basin. Based on the integrated application of GIS and RS, hydrological spatial information grid which serves as the platform of DHM construction is proposed. It is concluded that the integrated application of GIS and RS provides a new modern method for the realization of DHM, and makes it possible to construct a hydrological model in practice with the real meaning of "distributed in the whole scale of river basin".

This paper presents a model integrating GIS, cellular automata (CA) and genetic algorithm (GA) in urban spatial optimization. The model involves three objectives of the maximization of land-use efficiency, the maximization of urban spatial harmony and appropriate proportion of each land-use type. CA submodel is designed with standard Moore neighbor and three transition rules to maximize the land-use efficiency and urban spatial harmony, according to the land-use suitability and spatial harmony index. GA submodel is designed with four constraints and seven steps for the maximization of urban spatial harmony and appropriate proportion of each land-use type, including encoding, initializing, calculating fitness, selection, crossover, mutation and elitism. GIS is used to prepare for the input data sets for the model and perform spatial analysis on the results, while CA and GA are integrated to optimize urban spatial structure, programmed with Matlab 7 and coupled with GIS loosely. Lanzhou, a typical valley-basin city with fast urban development, is chosen as the case study. At the end, a detail analysis and evaluation of the spatial optimization with the model are made, and it proves to be a powerful tool in optimizing urban spatial structure and make supplement for urban planning and policy-makers.

Precipitation is a function of many topographical features as well as geographical locations. The correlations between precipitation and topographical and geographical features can be used to improve estimation of precipitation distribution. In this paper, we built seasonal precipitation model based on GIS techniques in Zhejiang Province in southeastern China. Terrain variables derived from the 1 km resolution DEM are used as predictors of the seasonal precipitation, using a regression-based approach. Variables used for model development include: longitude, latitude, elevation, and distance from the nearest coast, direction to the nearest coast, slope, aspect, and the ratio of land to sea within given radii. Seasonal precipitation data, for the observation period 1971 to 2000, were assembled from 59 meteorological stations. Precipitation data from 52 meteorological stations were used to initialize the regression model. The data from the other 7 stations were retained for model validation. Seasonal precipitation surfaces were constructed using the regression equations, and refined by kriging the residuals from the regression model and subtracting the result from the predicted surface. Latitude, elevation and distance from the sea are found to be the most effective predictors of local seasonal precipitation. Validation determined that regression plus kriging predicts mean seasonal precipitation with a coefficient of determination (R²), between the estimated and observed values, of 0.546 (winter) and 0.895 (spring). A simple regression model without kriging yields less accurate results in all seasons.

DEM data availability and GIS-assisted processing of the data have extended the usage of DEM to a great extent. Taking 5 m grid resolution DEMs of 48 test areas in the Loess Plateau in north Shaanxi as test data, this paper introduces the definition, calculation, extraction and stable threshold area of terrain driving force (T_d) for soil erosion. Then, spatial distribution of T_d is investigated with a method of geostatistics analysis. Results show that spatial distribution of T_d is correlatable with spatial distribution of the soil erosion intensity and T_d can be taken as a regional terrain factor of regional soil erosion in the Loess Plateau. But T_d is not exact enough in evaluation processing of regional soil erosion, an integrated analysis combining the climate, vegetation cover, soil and water conservation management is demanded. Then, some problems existing in the research of regional soil erosion are analyzed and a preliminary model of regional soil erosion contained T_d is proposed. Subsequent research is focused on data collection and integration of regional soil erosion and its applicability in the Loess Plateau.

Geographically weighted regression (GWR) is a simple but powerful method for exploring spatial relationship non-stationary. In GWR, all coefficients vary over space, and the parameter estimates are made using an approach in which the contribution of a sample to the analysis is weighted based on its spatial proximity to the specific location under consideration. Data from observations close to the location under consideration are weighted more than data from observations far away. And parameter estimates are local rather than global parameters at each point on study region. But in some situations not every coefficient in a model varies geographically, so mixed geographically weighted regression, in which some coefficients are termed global while the remaining coefficients are termed local, should be considered. Undoubtedly, ordinary algorithm of parameter estimation of GWR is not directly used in mixed GWR. In this paper, based on some work with GWR technique, an iterative algorithm is developed to estimate global coefficients and local coefficients in GWR, and this method is further tested by using average sold prices of house blocks in Shanghai, China. The experiment proves that mixed GWR is more appropriate and stable for the local coefficients estimates than GWR, although it requires a greater computational effort.

Landforms can be described and identified by parameterization of digital elevation model (DEM). This paper discusses the large-scale geomorphological characteristics of China based on numerical analysis of terrain parameters and develop a methodology for characterizing landforms from DEMs. The methodology is implemented as a two-step process. First, terrain variables are derived from a 1-km DEM in a given statistical unit including local relief, the earth's surface incision, elevation variance coefficient, roughness, mean slope and mean elevation. Second, every parameter regarded as a single-band image is combined into a multi-band image. Then ISODATA unsupervised classification and the Bayesian technique of Maximum Likelihood supervised classification are applied for landform classification. The resulting landforms are evaluated by the means of Stratified Sampling with respect to an existing map and the overall classification accuracy reaches to rather high value. It's shown that the derived parameters carry sufficient physiographic information and can be used for landform classification. Since the classification method integrates manifold terrain indexes, conquers the limitation of the subjective cognition, as well as a low cost, apparently it could represent an applied foreground in the classification of macroscopic relief forms. Furthermore, it exhibits significance in consummating the theory and the methodology of DEMs on digital terrain analysis.

The research probes into the temporal-spatial process of drainage development of Loess Plateau on the basis of a carefully designed experiment. In the experiment, the development of a simulated loess watershed is tested under the condition of lab-simulated rainfall. A close-range photogrammetry survey is employed to establish a series of high precision and resolution DEM (Digit Elevation Model) of the simulated loess surface. Based on the established DEM, the erosion loss, the slope distribution, the topographic index , the gully-brink, and the drainage networks are all derived and discussed through comparison analysis and experimental validation. All the efforts aim at revealing the process and mechanism of erosion and drainage development of loess surface .This study demonstrates: 1) the stimulation result can effectively reflect the truth if those experimental conditions, i.e. loess soil structure, simulated rainfall, are adjusted in accord with true situation; 2) the remarkable character of the erosion and drainage up-growth of loess surface include the drainage traced to the source, the increased of the drainage's density, the enlarged of gully, the durative variety of multiple terrain factor's mean value and its distribution, such as slope and topographic index; 3) The slope spectrum is the more felicitous terrain factor for depicting the erosion and drainage development of loess surface, including the rule of erosion and evolution process. It is the new way and mean for studying the loess physiognomy.

Forecasting has become an essential part of modern thought, but the practical limitations still are manifold. We addressed future rates of change by comparing models that take into account time, and models that focus more on space. Cox regression confirmed that linear change can be safely assumed in the short-term. Spatially explicit Poisson regression, provided a ceiling value for the number of deforestation spots. With several observed and estimated rates, it was decided to forecast using the more robust assumptions. A Markov-chain cellular automaton thus projected 5-year deforestation in the Amazonian Arc of Deforestation, showing that even a stable rate of change would largely deplete the forest area. More generally, resolution and implementation of the existing models could explain many of the modelling difficulties still affecting forecasting.

Geographical Information Systems (GIS) has become powerful tools for the management of multivariate information. GIS serves as a tool to supplement the shortage of existing geophysical analysis methods. The increased attentions to the research of deep geological structure are creating awareness of the potential of GIS technology for geophysical data analysis and data integration. It is an important approach that GIS is combined with geophysics for the resolving of various difficult problem of deep geological structure interpretations. Taking the data of Guangxi, China as an example, This paper presents the approach of geophysical data integration and the process of spatial overlay analysis based on GIS. The study has indicated there are the close relationships between the subsurface structure of study area and the geophysical properties such as gravity anomaly, aeromagnetic anomaly and seism. The weighted overlay analysis of different geophysical surveys provides new insights into the structures of the crustal underground. The Digital Elevation Model (DEM) analysis of geophysical data shows the existence of northeast structure and northwest structure more distinctly. The magnetotelluric resistivity 3D model created by 3D modeling tool of MAPGIS opens out the characters of subsurface geological structure decided by magnetotelluric data more visually.

Spatial association rule is one of the upmost knowledge rules in the result of spatial data mining. It emphasizes particularly on confirming the relation of data in different fields. It tries to find out the dependence of data in multi-fields. As we know, in GIS the spatial database is often separated into several layers or tables according the type of the spatial object such as road layer, building layer, plant layer etc. In the relational database we often separate it into several tables which be associated by the primary key and foreign key according the normal form theory. Consequently, the spatial data is stored in different layers and tables. It is necessary and meaning to mining the knowledge and rules in multi-layer and multi-tables. And, It is inevitable to mining spatial association rules in multi-layer in some application. There is a problem in it, that is the number of the rules are magnitude. So, we point a new way by using the cell pattern of the rules which the user interested to reduce and simplify the operation. In this paper the concept of multi-layer spatial association rule is put forward. Then an algorithm of mining multi-layer spatial association rule is presented which based on cell pattern and spatial concept relation. It was called AP-MLSAM in the paper. Last, an example in GIS is given. In AP-MLSAM, First, it confirms the patterns and rules that the user is interested in. Second it counts the large itemsets according with the cell pattern in each data layer. Last, the spatial association rules are gained by the itemsets which be counted in the second step. From the experiment, it proved that AP-MLSAM is effective. It improved the efficiency by reducing the time of finding the large itemsets. It is a significance research field for mining multi-layer spatial association rules. There are many applications based on multi-layer spatial association analyse. For example: traffic flux analyse in city, weather pattern analyse, trend analyse for climate and plant. All these applications request mining the association rules in the mass data. It is necessary to improve the efficiency of the algorithm. And this paper offers a new way to mine multi-layer spatial association rule based on concept relation using cell pattern.

In this study, hillslope erosion risk has been estimated for all eastern New South Wales (NSW) catchments, Australia using Revised Universal Soil Loss Equation (RUSLE) in a geographic information system (GIS) environment. Rainfall-runoff erosivity (R) factor was interpolated from NSW rainfall-erosivity contour (isoerodent) data. Soil erodibility (K) factor was based on the soil regolith stability and sediment yield classification. The classification was derived from soil landscape and related soil map data. The slope length and steepness (LS) factor was derived from high resolution digital elevation model (DEM). A fully-automated program using Arc Macro Language (AML) produced RUSLE-based LS factor grids for all coastal catchments. The outputs are comparable to the range of LS values summarised in the literature. Cover and management (C) factor and conservation support-practices (P) factor were set to one. They are intended to be allocated according to land use, ground cover and erosion control provisions for particular land management actions. The resulting erosion risk map, with pixel size of 25-m, provides unprecedented resolution of relative expected sheet and rill erosion across all NSW costal catchments and can be adapted for a range of erosion control purposes such as bushfire hazard reduction and comprehensive costal assessment.

Surrogate travel (or sometimes referred to as movie maps) is the term given to the use of interactive multimedia products that allow users to 'travel' through environments. They are built with a variety of multimedia products, but they have in common the goal to provide tools that allow buildings, towns, cities and natural environments to be appreciated and understood without actually 'being there'. This paper provides a brief background to surrogate travel and it gives, by way of background, a brief description of two key surrogate travel cartographically-related products - the Aspen Movie Map and the Domesday project. It also provides brief details of surrogate travel products developed by the author as proof-of-concept prototypes. Finally, the paper provides information about further developments of surrogate travel by the author.

This paper introduces an approach to the risk evaluation of underground gas pipe by making use of the spatial data and corresponding attribute data in the CIS. By using risk evaluation model for gas pipe, the risk is analyzed for the collected spatial data and attributes data from gas pipe, which gets safety levels of the urban gas pipes and displays the result on the electronic map. The result of risk evaluation will be used for making decision on the maintenance and updating of gas pipes.