A GIS-based borehole data management and 3D visualization system

The use of subsurface data for problem solving is limited in part by the freedom the user has in their choice of data structures. If a user is allowed to work with the data in a familiar way, they can spend more time performing analysis tasks and less time restructuring data, thus increasing productivity and reducing the risks associated with a series of data modification cycles. Borehole information system (BoreIS) is based upon this principle. Design was guided by interviews with geologists who were targeted as potential users of the software, and BoreIS was developed as an extension to ESRI's ArcScene three-dimensional (3D) GIS environment. BoreIS uses borehole or well data supplied by the user to develop a 3D GIS representation which can be queried, visualized, and analysed. By asking relevant questions about data stored in Excel spreadsheets, BoreIS can automate many high-level GIS functions so that an inexperienced GIS user can still use the system. By matching table elements to spatially and geologically significant terms through the interactive setup, users can work with the data more closely matched to the geological problem domain. This allows the novice user to use powerful GIS functions to discover spatial patterns in their data. BoreIS’ interactive manipulation of terms in complex queries, simple addition of contoured surfaces, and masking by lithology or formation helps geologists find spatial patterns in their data, beyond the limits of data tables and flat maps.     

A GEP-based spatial decision support system for multisite land use allocation

Multisite Land Use Allocation Problem (MLUA) refers to the problem of allocating more than one land use type in an area. MLUA problem is one of the truly NP Complete (combinatorial optimization) problems. To cope with this type of problems, intelligent techniques such as genetic algorithms, and simulated annealing, have been used. Research in the area of Spatial Decision Support Systems (SDSS) for resource allocation issues, a new scientific area of information system applications developed to support semi-structured or unstructured spatial decisions, has recently generated attention for integrating Artificial Intelligence (AI) techniques with Geographic Information Systems (GIS). In this paper we demonstrate how GIS can be integrated with Gene Expression Programming (GEP), a recently developed AI approach, for solving MLUA problems. The feasibility of the proposed approach in solving MLUA problems was checked using a fictive case study. The results indicated that the proposed approach gives good and satisfactory results.     

Fusion of point-based postal data with IKONOS imagery

Research in urban remote sensing has been recently reinvigorated by both the continuing fusion with GIS and the advent of high spatial resolution satellite sensor data. Both will be examined by this paper in terms of how GIS data at the point level can assist the identification and interpretation of urban land use patterns from classified land cover. Specifically, how spatial statistics can be used to summarise the two-dimensional patterns of point data representing residential and commercial buildings. In this paper point data refer to the location of postal addresses known as ADDRESS-POINT^TM and collected by the Ordnance Survey of Great Britain and COMPAS^TM in Northern Ireland. Groups of these postal points are characterised using standard nearest-neighbour and linear nearest-neighbour indices in terms of the spacing and arrangement of residential and commercial buildings. The indices then form the basis for the interpretation of urban pixels classified from IKONOS imagery at the 4 m spatial resolution. In addition, the paper will outline an agenda for constructing an automated pattern recognition system that would ultimately identify and characterise the physical arrangement of buildings in terms of density (compactness versus sparseness) and linearity. Preliminary results so far are most encouraging. Using ground truth from aerial photographs at 15 cm spatial resolution, classified IKONOS imagery representing two cities in the United Kingdom, Bristol and Belfast, have been investigated. In both, spatial patterns have demonstrated the ability to identify misclassified urban pixels and characterise a variety of building arrangements. Also, using the software e-Cognition, a spatial classification based on nearest neighbour contextual rules produced accuracies of 95.4% compared to 90.7% from a multispectral-only classification. Further, more extensive testing is continuing.     

Linking GIS and water resources management models: an object-oriented method

Many challenges are associated with the integration of geographic information systems (GISs) with models in specific applications. One of them is adapting models to the environment of GISs. Unique aspects of water resource management problems require a special approach to development of GIS data structures. Expanded development of GIS applications for handling water resources management analysis can be assisted by use of an object oriented approach. In this paper, we model a river basin water allocation problem as a collection of spatial and thematic objects. A conceptual GIS data model is formulated to integrate the physical and logical components of the modeling problem into an operational framework, based on which, extended GIS functions are developed to implement a tight linkage between the GIS and the water resources management model. Through the object-oriented approach, data, models and users interfaces are integrated in the GIS environment, creating great flexibility for modeling and analysis. The concept and methodology described in this paper is also applicable to connecting GIS with models in other fields that have a spatial dimension and hence to which GIS can provide a powerful additional component of the modeler’s tool kit.     

Visualizing Demographic Trajectories with Self-Organizing Maps

In recent years, the proliferation of multi-temporal census data products and the increased capabilities of geospatial analysis and visualization techniques have encouraged longitudinal analyses of socioeconomic census data. Traditional cartographic methods for illustrating socioeconomic change tend to rely either on comparison of multiple temporal snapshots or on explicit representation of the magnitude of change occurring between different time periods. This paper proposes to add another perspective to the visualization of temporal change, by linking multi-temporal observations to a geometric configuration that is not based on geographic space, but on a spatialized representation of n-dimensional attribute space. The presented methodology aims at providing a cognitively plausible representation of changes occurring inside census areas by representing their attribute space trajectories as line features traversing a two-dimensional display space. First, the self-organizing map (SOM) method is used to transform n-dimensional data such that the resulting two-dimensional configuration can be represented with standard GIS data structures. Then, individual census observations are mapped onto the neural network and linked as temporal vertices to represent attribute space trajectories as directed graphs. This method is demonstrated for a data set containing 254 counties and 32 demographic variables. Various transformations and visual results are presented and discussed in the paper, from the visualization of individual component planes and trajectory clusters to the mapping of different attributes onto temporal trajectories.     

The groundwater modeling tool for GRASS (GMTG): Open source groundwater flow modeling

Geographic Information Systems (GIS) are used to store, manipulate and visualize both spatial and non-spatial data. Because of their data manipulating capabilities, GIS have been linked to different simulation models in different research areas and are commonly used for both surface and ground water modeling. Unfortunately this has been done mainly with proprietary GIS which are expensive and which do not provide access to their source code thus making them hard to customize. In order to overcome these problems, a module was created in the Open Source Geographic Resources Analysis Support System (GRASS) GIS to integrate it with the finite difference groundwater flow model MODFLOW, to take full advantage of the GIS capabilities. The results obtained with this module, when compared to those obtained with an existing MODFLOW pre and post-processor show that it can be used to develop groundwater flow models using uniform grid spacing on the horizontal plane. This module provides a tool for groundwater flow modeling to those users who cannot afford the commercially available processors and/or to those who wish to develop their models within a GIS.     

基于SIG框架的上海城市空间信息应用服务系统的体系与实现

基于空间信息网格SIG框架的上海城市空间信息应用服务系统中城市空间特征、绿化、环保、水系、土地、道路网络等各类城市空间信息资源分布在网络的不同节点上；建立了集中的元数据库提供相关数据的描述信息；以分布在不同节点上的GIS Web Service提供空间数据处理服务。平台以门户网站的方式提供元数据检索，利用检索结果获取分布式的各类空间信息数据资源；提供空间数据处理网络应用程序，调用GIS Web Service，提供格式转换、坐标转换、地图综合、空间分析等空间数据处理功能；提供GIS Web Service的搜索和注册。此平台已经在上海公务网中实际运行。     

Mapping applications for low-cost remote sensing and geographic information systems

Abstract

Increasing attention is being given to the practicability of remote sensing and geographic information systems (GIS). Easily adaptable low-cost systems in these two rapidly advancing technologies have particular relevance for developing nations. Data from advanced satellite sensor sytems such as the SPOT High Resolution Visible (HRV) and the Landsat Thematic Mapper (TM) have proven to be useful in topographic as well as thematic mapping, particularly for map revision. Based on the specific application, mapping systems have ranged from simple visual image interpretation lo automated digital image analysis systems with sophisticated classification schemes. Examples of topographic and thematic mapping using low-cost systems will be presented.

GIS have extended the capability of low-cost digital systems that simply provided storage and map production capabilities, to systems providing spatial data analysis including the linkage of spatial data and spatially related attributes. Data capture is an essential but laborious and expensive component of the overall mapping system. Satellite remote sensing is an obvious source of data for mapping and map revision because of its repetitive wide-area coverage and low cost. The need for integration of remote sensing and GIS is thus inevitable and is rapidly emerging because of the complementary role played by these technologies in resource management. The importance and utility of this integrated approach to mapping will be documented using Canadian examples.     

拓扑关系形式化描述的基本问题与研究进展

拓扑关系是GIS中空间目标之间最基本也是最重要的关系之一,在GIS空间数据建模、空间查询、空间分析、空间推理、制图综合等过程中起着重要的作用。该文首先介绍了不同的空间数据模型中拓扑信息的表达模式,然后重点回顾和评述了拓扑关系的建模方法以及拓扑关系形式化模型,并探讨了目前研究中存在的问题和有待进一步研究的工作。     

Generating and updating multiplicatively weighted Voronoi diagrams for point,line and polygon features in GIS

A Voronoi diagram is an interdisciplinary concept that has been applied to many fields. In geographic information systems (GIS), existing capabilities for generating Voronoi diagrams normally focus on ordinary (not weighted) point (not linear or area) features. For better integration of Voronoi diagram models and GIS, a raster-based approach is developed, and implemented seamlessly as an ArcGIS extension using ArcObjects. In this paper, the methodology and implementation of the extension are described, and examples are provided for ordinary or weighted point, line, and polygon features. Advantages and limitations of the extensions are also discussed. The extension has the following features: (1) it works for point, line, and polygon vector features; (2) it can generate both ordinary and multiplicatively weighted Voronoi diagrams in vector format; (3) it can assign non-spatial attributes of input features to Voronoi cells through spatial joining; and (4) it can produce an ordinary or a weighted Euclidean distance raster dataset for spatial modeling applications. The results can be conveniently combined with other GIS datasets to support both vector-based spatial analysis and raster-based spatial modeling.     

Using a spatial decision support system for solving the vehicle routing problem

Recent technological advances in Operational Research and Information Technology have enabled the development of high quality spatial decision support systems (SDSS). They constitute a new scientific area of information systems applications developed to support semi-structured or unstructured decisions, paying much attention to the spatial dimension of data to be analyzed, such as the location and shape of, and relationships among, geographic features. This paper presents a SDSS to coordinate and disseminate tasks and related information for solving the vehicle routing problem (VRP) using a metaheuristic method termed: backtracking adaptive threshold accepting (BATA). Its architecture involves an integrated framework of geographical information system (GIS) and a relational database management system (RDBMS) equipped with interactive communication capabilities between peripheral software tools. The SDSS was developed for Windows 98 platforms, focusing on the detailed road network of Athens.     

GeoVR: a web-based tool for virtual reality presentation from 2D GIS data

A tool called GeoVR has been designed and developed under a client/server architecture to enable the interactive creation of a 3D scene and virtual reality modeling language (VRML) model from 2D spatial data by integrating Internet geographical information system (GIS) and HTML programming. The client front-end of this tool provides an HTML form to set properties for building 3D scenes, while the server back-end supported by off-the-shelf software: ArcView Internet Map Server and ArcView 3D Analyst through Avenue programming, processes the parameters and generates a 3D scene. This 3D scene is then transformed into a VRML model, which, together with its legend, is sent back to the VRML-enabled WWW browser for display and navigation. It is demonstrated that this tool, not only automates the conversion of the conventional 2D GIS data into VRML, but also adapts the current GIS 3D capabilities to the increasingly popular Web environment. The development of GeoVR offers new opportunities for geoscientists to build applications that benefit from virtual reality presentation based upon the existing GIS spatial databases.     

EKEMAS,an agent-based geo-simulation framework to support continual planning in the real-word

In this paper, we propose an agent-based geo-simulation framework EKEMAS to assist human planners when planning under strong spatial constraints in a real large-scale space. The approach consists in drawing a parallel between the real environment (for example, a forest in fire) and the simulated environment based on GIS data. This virtual environment uses software agents which are aware of the space and equipped with advanced spatial reasoning capabilities. In addition, we suggest some enhancements for the Continual Planning approach. Our aim is to demonstrate how EKEMAS, when coupled with a continual planning approach and agent’s spatial reasoning capabilities, can assist human planners overcoming obstacles related to real world constraints: dynamic, uncertain, and spatially constrained environment. We illustrate this idea on the forest firefighting problem and we use MAGS as a simulation platform and Prometheus as a fire simulator. Finally, and since plans in the studied case (wildfire fighting) are mainly paths, we also propose a new approach based on agent geo-simulation in order to solve particular Pathfinding problems.     

A patch‐based image classification by integrating hyperspectral data with GIS

Hyperspectral remote sensing data provide detailed spectral information and are widely used for pixel‐based image classification. However, without considering spatial correlation among neighbouring pixels, a generated thematic map may have a ‘salt‐and‐pepper’ appearance. With the development of the Geographic Information System (GIS), the spatial relationship between a pixel and its neighbours can be recorded readily and used together with remote sensing data. The objective of this study was to integrate hyperspectral data with the GIS for effective thematic mapping. To date, GIS data have been used mainly in field surveys or training field selection for remote sensing data interpretation. Here we propose a patch‐classification based on integration of the GIS with remote sensing data. The classification results obtained by using this method can be easily saved in a vector format as used for GIS files. Computational cost is decreased compared with a pixel‐by‐pixel classification. The issue of how to identify pure or mixed patches is addressed and a three‐level simple and effective checking method is developed. A case study is presented with a hyperspectral data set recorded by the Pushbroom Hyperspectral Imager (PHI) and related GIS data.     

Multiple representations for cartographic objects in a multi-scale tree—An intelligent graphical zoom

In Geographic Information Systems, a function to draw cartographic sketches quickly and in arbitrary scales is needed. This calls for cartographic generalization, a notoriously difficult problem. Efforts to achieve automatic cartographic generalization were successful for specific aspects, but no complete solution is known, nor are there any expected within the immediate future. In practical applications, a base map is stored and its scale is changed. Without major distortions, only changes to twice or half the original scale are feasible by simple numeric scale change. Everything beyond this requires adaptation of symbols, selection of objects, placements of labels, etc.

Extending ideas of hierarchies or pyramids, where representations of the same objects at different scales are stored, a multi-scale, hierarchial spatial model is proposed. Objects with increasing detail are stored in levels and can be used to compose a map at a particular scale. Applied to the particular problem of cartographic mapping, this results in a multi-scale cartographic tree. The same concept can be used equally well for other applications, which require rendering of objects at different levels of detail.

The structure of the multi-scale tree is explained. It is based on a trade-off between storage and computation, replacing all steps which are difficult to automate by essentially redundant storage. The dominant operation is ‘zoom,’ which moves towards a more detailed level, intelligently replacing the current graphical representation with the more detailed one, appropriate for the selected new scale. Methods to select objects for rendering are based on the principle of equal information density. Principles of possible implementations are presented.     

GIS环境下融合实时交通数据的交互系统

论述了如何在地理信息系统环境下集成实时交通数据,开发可交互系统。开发的目的主要有两点:1.充分利用数据库功能,增强当前交通监控系统能力;2.开发可视化智能分析工具,充分发挥当前交通监控系统的能力。文中分析了系统动态实时交通数据的数据库环境,讨论了交通数据实时融合、集中在GIS应用中的数据接口模块,并从时空两方面提供可视化和智能分析工具。为了便于分析,文章以北京交通管理局的地理信息系统开发为例。     

Space‐in‐Time and Time‐in‐Space Self‐Organizing Maps for Exploring Spatiotemporal Patterns

Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data cannot be analyzed by fully automatic methods but require the involvement of the human analyst's expertise. For a comprehensive analysis, the data need to be considered from two complementary perspectives: (1) as spatial distributions (situations) changing over time and (2) as profiles of local temporal variation distributed over space. In order to support the visual analysis of spatiotemporal data, we suggest a framework based on the “Self‐Organizing Map” (SOM) method combined with a set of interactive visual tools supporting both analytic perspectives. SOM can be considered as a combination of clustering and dimensionality reduction. In the first perspective, SOM is applied to the spatial situations at different time moments or intervals. In the other perspective, SOM is applied to the local temporal evolution profiles. The integrated visual analytics environment includes interactive coordinated displays enabling various transformations of spatiotemporal data and post‐processing of SOM results. The SOM matrix display offers an overview of the groupings of data objects and their two‐dimensional arrangement by similarity. This view is linked to a cartographic map display, a time series graph, and a periodic pattern view. The linkage of these views supports the analysis of SOM results in both the spatial and temporal contexts. The variable SOM grid coloring serves as an instrument for linking the SOM with the corresponding items in the other displays. The framework has been validated on a large dataset with real city traffic data, where expected spatiotemporal patterns have been successfully uncovered. We also describe the use of the framework for discovery of previously unknown patterns in 41‐years time series of 7 crime rate attributes in the states of the USA.     

Some challenges of integrating spatial and non-spatial datasets using a geographical information system

Geographical Information Systems or GIS are becoming useful tools in making strategic decisions in a variety of government and business activities in areas such as housing, healthcare, land use, natural resources, environmental monitoring, public health, transportation, retail, and routing. This usefulness emanates from the capability of GIS to present a large amount of data in a short period of time on a map, using a geographical coordinate system. In most cases, spatial datasets required for GIS mapping are already available free from many governmental agencies. GIS use more of computing technology than geographical concepts, however, the capabilities of GIS software did not reach the level of simplicity encountered in most software used on a daily basis. Most organizations perform GIS analysis on their data without getting involved with the mapping technology. A typical GIS analyst faces various challenges while incorporating non-spatial dataset to spatial dataset in order to present resulting dataset on a geographical map. In this paper, we present some data manipulation complexities that are encountered while using a GIS software to provide spatial twists to a large user dataset. We also provide ways to facilitate the data manipulation process through a practical example of asthma epidemiology. The solutions will be beneficial to many GIS users in varieties of industries.     

Five Steps to Construct a Model of Data Allocation for Distributed Database Systems

The allocation of data to nodes in a computer communications network is a critical issue in distributed database design, specially in wide area network where optimizing the distributed queries is the main objective. Numerous models of data allocation have been presented so far (Ceri and Pelagatti, 1986; Lee et al., 1994; Apers, 1988; Mahmood et al., 1994; Theel, 1994; Saha and Mukherjee, 1994; Walfson and Jajodia, 1995), but no optimal or universally accepted algorithm exists yet, and very few algorithms have been implemented to date (Rob and Cornonel, 1993). In this paper a method to construct a model of data allocation for distributed database system has been proposed. The adopted method for the construction of the data allocation model leads to an efficient model of its kind. The proposed model not only solves distributed database design problem, but also solves distributed database maintenance problem by covering initial allocation and post allocation of the data. The efficiency of proposed model has been proved by comparing proposed model with other relevant models.