Fuzzy Spatial Data Modeling for Integration of Heterogeneous Geospatial Information

Geospatial data has become an integral part of many decision making processes specially related to socio-economic development. The geospatial information are often stored, maintained and processed by various diverse organizations in proprietary GIS systems. With increasing use in Internet and web services on line data sharing and accession has increased. Thus the major bottlenecks of integrating these diverse datasets lie in the understanding of individual data structures or models, inter-relationships among the data and the accessibility of the repositories over web. In order to integrate these data, the structure of these diverse datasets are to be standardized. In addition, Uncertainty and fuzziness are inherent to the properties of spatial data. However, the current standards proposed for geospatial data modeling technique are not able to represent the fuzzy data. Thus most of the geospatial organization uses crisp data model to share and integrate the diverse datasets. However, when spatial phenomena is generalized in crisp form, then lot of quantitative informations are lost. This work presents fuzzy spatial data modeling technique, by incorporating fuzzy set theory concepts and fuzzy logic in UML class diagram. Integration of diverse, imprecise information based on the fuzzy spatial data model has also been shown using some spatial data sets.