Sskm: a Tool to Improve Spatial Decision Support Ability of Gis
نویسندگان
چکیده
Spatial decision support is an important research area of spatial information science and should be an integrated function offered by GIS (Geographical Information System) software. It has been proved that many spatial problems are semior ill-structured and cannot be solved by traditional GIS that has no domain knowledge support. It is highly desired to include the theory of knowledge management with the intention of improving GIS spatial decision support ability. Integrating spatial information management and human or domain knowledge is an essential way. This paper proposes the concept, principle and method of Structured Spatial Knowledge Management, or SSKM, an effective domain knowledge management method Compared with non-spatial knowledge, spatial knowledge, as its name indicates, is defined here as a kind of geo-referenced knowledge that is location-specifically applicable. Centered on structured knowledge representation (or SKR), SSKM offers a comprehensive platform capable of expressing a clear and uniform spatial knowledge views so both knowledge access, knowledge utilization and knowledge-based spatial reasoning become easier than represented in other ways. In this way semior ill-structured spatial problems solving based on existing spatial/nonspatial knowledge and general spatial analysis functions usually identical to GIS can be collaborated seamlessly to generate understandable spatial decision results. As the center of SSKM, SKR is a hybrid knowledge representation strategy that combines object-oriented and rule-base knowledge representation, while domain analysis is the first step to extract conceptual and logical knowledge framework so SKR representation can then be implemented. An integrated unit of knowledge-based spatial reasoning and GIS named GIS distributed intelligent agent, or GIS-DIA, is proposed as an embodiment of this research. GIS-DIA aggregates both data, knowledge and general GIS functions, and thus offers both knowledge support and GIS function to complete certain georeferenced problems. Related GIS-DIAs usually collaborate together to solve semior ill-enhance problem. In the end a case study in agriculture decision-making is given. After domain analysis of possible decision classification and required knowledge, GIS-DIAs are designed and developed that are able to identify proposed problems and give a corresponding decision result to each problem. * Corresponding Author
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