Comparison of Crisp, Fuzzy and Possibilistic Threshold in Spatial Queries

Decision making is one of the most important application areas of geoinformatics. Such support is mainly oriented on the identification of locations that fulfil certain criterion. The contribution presents the suitability of various approaches of spatial query using different types of Fuzzy thresolds. Presented methods are based on the classical logic (Crisp queries), Fuzzy logic (Fuzzy queries) and Possibility theory (Possibilistic Queries). All presented approaches are applied in the case study. Use these findings may contribute to the better understanding of the nature of the methods used and can help to obtain more accurate results, which have a determining influence on subsequent decision-making process.

[1]  Frank Witlox,et al.  Spatial Decision-Making Using Fuzzy Decision Tables: Theory, Application and Limitations , 2005 .

[2]  Donald H. Kraft,et al.  Fuzzy sets in database and information systems: Status and opportunities , 2005, Fuzzy Sets Syst..

[3]  Sungsoon Hwang,et al.  Modeling Localities with Fuzzy Sets and GIS , 2005 .

[4]  R. Hickey,et al.  The effect of slope algorithms on slope estimates within a GIS , 1998 .

[5]  Peter Fisher,et al.  Sorites paradox and vague geographies , 2000, Fuzzy Sets Syst..

[6]  Jiri Dvorský,et al.  P systems: State of the Art with Respect to Representation of Geographical Space , 2012, DATESO.

[7]  M. Goodchild,et al.  Geographic Information Systems and Science (second edition) , 2001 .

[8]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[9]  L. Zadeh Fuzzy sets as a basis for a theory of possibility , 1999 .

[10]  Weldon A. Lodwick,et al.  Modelling the Fuzzy Spatial Extent of Geographical Entities , 2005 .

[11]  P. Burrough,et al.  Principles of geographical information systems , 1998 .

[12]  Berthold K. P. Horn,et al.  Hill shading and the reflectance map , 1981, Proceedings of the IEEE.

[13]  Michael Hanss,et al.  Applied Fuzzy Arithmetic: An Introduction with Engineering Applications , 2004 .

[14]  Alfred Stein,et al.  Thirty Years of Research on Spatial Data Quality: Achievements, Failures, and Opportunities , 2010, Trans. GIS.

[15]  Didier Dubois,et al.  Possibility Theory - An Approach to Computerized Processing of Uncertainty , 1988 .

[16]  Didier Dubois,et al.  The role of fuzzy sets in decision sciences: Old techniques and new directions , 2011, Fuzzy Sets Syst..

[17]  Lotfi A. Zadeh,et al.  Is there a need for fuzzy logic? , 2008, NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society.

[18]  Frederick E. Petry,et al.  Fuzzy Modeling with Spatial Information for Geographic Problems , 2008 .

[19]  M. Goodchild,et al.  Geographical information systems. 2nd. , 1999 .

[20]  Didier Dubois,et al.  Ranking fuzzy numbers in the setting of possibility theory , 1983, Inf. Sci..