Fuzzy Set Theoretic Approaches for Handling Imprecision in Spatial Analysis

Abstract This paper presents methodologies for modelling imprecision in the definition, analysis and synthesis of two-dimensional features. The imprecision may arise through incomplete information, the presence of varying concentrations of attributes, or the use of qualitative descriptions of spatial features or their relationships. The work is intended to have applications in geographical information systems (GIS), but is equally applicable to other types of spatial information systems or spatial database applications. Fuzzy sets are used as a representational and reasoning device. The paper contains definitions of an imprecisely defined spatial feature or fuzzy region; definitions of distance and directional metrics between two such regions; a methodology for analysis of the spatial relationship between two regions; and a methodology for synthesis of new regions that are subject to the presence of imprecise spatial constraints.

[1]  D. Lozano-García,et al.  Accuracy assessment of map coordinate retrieval , 1991 .

[2]  Donna J. Peuquet,et al.  A Conceptual Framework and Comparison of Spatial Data Models , 1984 .

[3]  Ian Graham,et al.  Expert Systems: Knowledge, Uncertainty and Decision , 1988 .

[4]  Shyi-Mig Chen,et al.  A new approach to handling fuzzy decision-making problems , 1988, [1988] Proceedings. The Eighteenth International Symposium on Multiple-Valued Logic.

[5]  Sumith Pathirana Detection of linear and sub-pixel phenomena using the fuzzy membership approach , 1992 .

[6]  Madan M. Gupta,et al.  Fuzzy mathematical models in engineering and management science , 1988 .

[7]  Vincent B. Robinson Interactive machine acquisition of a fuzzy spatial relation , 1990 .

[8]  H. Zimmermann Fuzzy sets, decision making, and expert systems , 1987 .

[9]  Jin-Fu Chang,et al.  Knowledge Representation Using Fuzzy Petri Nets , 1990, IEEE Trans. Knowl. Data Eng..

[10]  Soumitra Dutta,et al.  Approximate spatial reasoning: Integrating qualitative and quantitative constraints , 1991, Int. J. Approx. Reason..

[11]  Yee Leung,et al.  A Linguistically-Based Regional Classification System , 1985 .

[12]  Kwong-Sak Leung,et al.  Fuzzy concepts in expert systems , 1988, Computer.

[13]  Brian Everitt,et al.  Cluster analysis , 1974 .

[14]  A. Kaufmann,et al.  Introduction to fuzzy arithmetic : theory and applications , 1986 .

[15]  V. Robinson Some implications of fuzzy set theory applied to geographic databases , 1988 .

[16]  J. Bezdek,et al.  FCM: The fuzzy c-means clustering algorithm , 1984 .

[17]  R. Dunn,et al.  Positional accuracy and measurement error in digital databases of land use: an empirical study , 1990, Int. J. Geogr. Inf. Sci..

[18]  Caroline M. Eastman,et al.  Review: Introduction to fuzzy arithmetic: Theory and applications : Arnold Kaufmann and Madan M. Gupta, Van Nostrand Reinhold, New York, 1985 , 1987, Int. J. Approx. Reason..

[19]  Peter Fisher,et al.  An investigation of the meaning of near and close on a university campus , 1991 .

[20]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .

[21]  Jin-Fu Chang,et al.  An inexact reasoning technique based on extended fuzzy productions rules , 1991 .

[22]  Peter A. Burrough,et al.  Fuzzy mathematical methods for soil survey and land evaluation , 1989 .

[23]  Gary J. Hunter,et al.  Understanding error in spatial databases , 1992 .

[24]  Rudolf Kruse,et al.  Uncertainty and Vagueness in Knowledge Based Systems , 1991, Artificial Intelligence.

[25]  James C. Bezdek,et al.  Efficient Implementation of the Fuzzy c-Means Clustering Algorithms , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Yee Leung,et al.  Spatial Analysis and Planning under Imprecision , 1988 .

[27]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[28]  Fangju Wang,et al.  Fuzzy supervised classification of remote sensing images , 1990 .

[29]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[30]  Paul V. Bolstad,et al.  Positional uncertainty in manually digitized map data , 1990, Int. J. Geogr. Inf. Sci..

[31]  Gerard B. M. Heuvelink,et al.  Propagation of errors in spatial modelling with GIS , 1989, Int. J. Geogr. Inf. Sci..

[32]  A. Kandel Fuzzy Mathematical Techniques With Applications , 1986 .

[33]  Fangju Wang,et al.  Fuzzy information representation and processing in conventional GIS software: database design and application , 1990, Int. J. Geogr. Inf. Sci..

[34]  Ronald R. Yager,et al.  Approximate reasoning as a basis for rule-based expert systems , 1984, IEEE Transactions on Systems, Man, and Cybernetics.

[35]  Rudolf Kruse,et al.  Uncertainty and vagueness in knowledge based systems: numerical methods , 1991, Artificial intelligence.

[36]  Carl G. Looney,et al.  Fuzzy Petri nets for rule-based decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[37]  Weldon A. Lodwick,et al.  Attribute error and sensitivity analysis of map operations in geographical informations systems: suitability analysis , 1990, Int. J. Geogr. Inf. Sci..

[38]  Peter F. Fisher,et al.  The evaluation of fuzzy membership of land cover classes in the suburban zone , 1990 .