Maria Cobb

Fuzzy Modeling with Spatial Information for Geographic Problems

Reasoning About Regions, Relations, and Fields.- Fuzzy Reasoning about Geographic Regions.- Combined Extraction of Directional and Topological Relationship Information from 2D Concave Objects.- Field Based Methods for the Modeling of Fuzzy Spatial Data.- Modeling Localities with Fuzzy Sets and GIS.- Fuzzy Classification.- Mining Weather Data Using Fuzzy Cluster Analysis.- Modelling the Fuzzy Spatial Extent of Geographical Entities.- Multi-Dimensional Interpolations with Fuzzy Sets.- Talking Space - A Social & Fuzzy Logical GIS Perspective On Modelling Spatial Dynamics.- A Valuation of the Reliability of a GIS Based on the Fuzzy Logic in a Concrete Case Study.- Fuzzy Representations of Landscape Features.- Fuzziness and Ambiguity in Multi-Scale Analysis of Landscape Morphometry.- Fuzzy Representation of Special Terrain Features Using a Similarity-based Approach.- Decision Making with GIS and Fuzzy Sets.- Spatial Decision-Making Using Fuzzy Decision Tables: Theory, Application and Limitations.- Spatial Decision Making Using Fuzzy GIS.- Spatially Explicit Individual-Based Ecological Modeling with Mobile Fuzzy Agents.

Fuzzy Set Approaches to Spatial Data Mining of Association Rules

This paper presents an approach to the discovery of association rules for fuzzy spa- tial data. Association rules provide information of value in assessing significant correlations that can be found in large databases. Here we are interested in correlations of spatially related data such as soil types, directional or geometric relationships, etc. We have combined and extended techniques developed in both spatial and fuzzy data mining in order to deal with the uncertainty found in typical spatial data.

An OO database migrates to the Web

The authors faced the dual challenge of first converting a relational database to the OO paradigm, then migrating it to the Web. They describe the procedures and technologies they used. The basic architecture of the resulting system is presented. The project goal was to create a Java based mapping client that would provide display and query capabilities for a set of geographic objects (features) that would be retrieved from the Smalltalk mapping prototype acting as a server. We planned to base communication on the Corba specification. We also planned to keep the remote fetching of objects completely transparent to the end user, who would be able to manipulate the features as if they were local.

Fuzzy spatial relationships and mobile agent technology in geospatial information systems

This chapter discusses an integrated work in the definition and implementation of sets of fuzzy spatial relationships concerning topology and direction. We present our basic approach to defining these relationships as an extension to previous work in temporal relations. We also discuss several extensions to this approach that include refinements and alternate definitions. Two implementations are also described, one in a C++, Oracle database environment and another utilizing the expert system shell Fuzzy Clips. Finally we discuss the integration of this querying approach in an agent-based framework. Agent technology has become a leading implementation paradigm for distributed and complex systems, and has recently garnered much interest from researchers in the area of spatial databases. Agents offer many advantages with respect to intelligence abilities and mobility that can provide solutions for issues related to uncertainty in spatial data, such as those of spatial relationships.

Fuzzy spatial relationship refinements based on minimum bounding rectangle variations

Abstract Many spatial data modeling strategies rely upon approximate representations of spatial objects both for computational efficiency issued as well as the simplification of logical modeling strategies. The most widely used approximation is the minimum bounding rectangle (MBR). While the use of MBRs in spatial data modeling is extensive due to their efficiency for storage and relationship calculation, their use as a solitary means of identifying, for example, topological relationships between objects is problematic due to the inconsistency of mappings between relationships of MBRs and corresponding relationships of the objects they represent. In this paper we examine several extensions to the MBR model that reduce the discrepancies between binary spatial relationships of the MBRs and those of the contained objects. For each scheme, we consider the implications to the determination of fuzzy spatial relationships and the impact on computational issues.

Design of system for managing fuzzy relationships for integration of spatial data in querying

Abstract In this paper we present the design of two essential components for the spatial querying system we have been developing. The overall system architecture utilizes multiple levels of agents to process external sources of spatial data. Upon a user query, agents are spawned to mine various web sources, integrate the spatial data and return the correctly formulated query result to the user. Here we specifically describe a rule-based component for processing spatial relationships that is used both for the active agents and at the user interface to provide a dynamic query response. We also describe the database that is being used to maintain the spatial relationships uncovered in the query. The design and implementation of the two major components, the expert system using the expert system shell Fuzzy clips and the database in a C++, Oracle database environment, are described in some detail.

Performance evaluation of SDIAGENT, a multi-agent system for distributed fuzzy geospatial data conflation

A rapid growth of available geospatial data requires development of systems capable of autonomous data retrieval, integration and validation. Mobile agents may provide the suitable framework for developing such systems since this technology, in a natural way, can deal with the distributed heterogeneous nature of such data. In this paper, we evaluate SDIAGENT our, recently introduced, multi-agent architecture for geospatial data integration and conflation, and compare its model performance with that of client/server and single-agent approaches. Experimental results for several realistic scenarios, under varying conditions, are presented for these three system architectures. We analyze the performance alteration for various numbers of participating nodes, varying amount of database accesses, processing loads, and network loads.

Preliminary performance evaluation of an agent-based geospatial data conflation system

A rapid growth of available geospatial data requires development of systems capable of autonomous data retrieval, integration and validation. Mobile agent technology may provide a suitable framework for developing such systems since this technology can deal, in a natural way, with the distributed heterogeneous nature of the data. We evaluate our novel multi-agent architecture for geospatial data integration and compare its performance with a client/server and a single-agent architecture. We analyze the performance alteration for various numbers of participating nodes, amount of database accesses, processing loads, and network loads.

Querying Multiple Data Sources via an Object-Oriented Spatial Query Interface and Framework

Abstract A spatial query interface has been designed and implemented in the object-oriented paradigm for heterogeneous data sets. The object-oriented approach presented is shown to be highly suitable for querying typical multiple heterogeneous sources of spatial data. The spatial query model takes into consideration two common components of spatial data: spatial location and attributes. Spatial location allows users to specify an area or a region of interest, also known as a spatial range query. Also, the spatial query allows users to query spatial orientation and relationships (geometric and topological relationships) among other spatial data within the selected area or region. Queries on the properties and values of attributes provide more detailed non-spatial characteristics of spatial data. A query model specific to spatial data involves exploitation of both spatial and attribute components. This paper presents a conceptual spatial query model of heterogeneous data sets based on the object-oriented data model used in the geospatial information distribution system (GIDS).

Uncertainty in Distributed and Interoperable Spatial Information Systems

Many facets of spatial data representation inherently involve issues of accuracy and uncertainty. This problem is greatly magnified when considering the integration of spatial data from different sources, such as in a distributed or interoperable environment. The general concept, of schema merging Involves the resolution of incompatibilities as in a distributed environment. These may be either structural or semantic in nature. Structural incompatibilities involve those, for example, in which attributes for representing the same values arc tie-fined differently. Semantic incompatibilities, however, represent those cases in which similarly defined attributes have different meanings or values For example, an attribute of WIDTH for a road in one database may include the widih of associated accca lanes, while in anoiltei database it may be only the main drive able portion of the road. Such semantic issues are much more difficult to resolve, as they require a fleeper understanding oi ute data. We will survey tnc issues as diwussed above for spatial data in such environments and describe several approaches lor different aspects of the data using furry set techniques lo deal with the incompatibilities.