Abstract
Humans' representation about geographic phenomena in natural language is usually qualitative rather than quantitative. Qualitative spatial reasoning provides an approach which is considered to be closer to the representation. Commercial GIS software is being confronted with a challenge that the software should be equipped with artificial intelligent functions like qualitative spatial reasoning for users, especially for spatial decision-makers. This research proposes a framework of field-based fuzzy spatial reasoning through which qualitative description usually encountered in spatial reasoning process can be handled quantitatively. As preconditioning, field-based fuzzy representation structure for qualitative description is put forward, then the methods of constructing membership function are discussed. Standard operations of field-based fuzzy spatial reasoning model in the case of constraint satisfaction problem (CSP) are illustrated. An example explains the implication of the model in spatial decision-making process.
This chapter is improved from “Yaolong Zhao, Yumin Zhang, and Yuji Murayama (2005), Fieldbased fuzzy spatial reasoning model for geographical information systems: Case of constraint satisfaction problem, Theory and Applications of GIS, 13, 21–31”, with permission from GIS Association, Japan.
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Acknowledgements
National Natural Science Foundation of China, No. 40901090, 70863014; Foundation of Japan Society for the Promotion of Science (JSPS), No. 19.07003; Talents Introduced into Universities Foundation of Guangdong Province of China, No. 2009–26.
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Zhao, Y., Zhang, Y., Murayama, Y. (2011). Field-Based Fuzzy Spatial Reasoning Model for Constraint Satisfaction Problem. In: Murayama, Y., Thapa, R. (eds) Spatial Analysis and Modeling in Geographical Transformation Process. GeoJournal Library, vol 100. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0671-2_2
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