Fuzzy Objects: Their Changes and Uncertainties

Although most geographical entities represented as objects in a GIS have crisp boundaries, in reality they have indeterminate boundaries and fuzzy spatial extent. This is due to the fact that they are distributed continuously in space and time. Furthermore, measurement procedures generally produce data with a limited accuracy, which lead to the uncertain description of geographical entities. Because of these facts, uncertainties exist in the crisp object description of geographical entities. When temporal information is applied to analyze their change, these uncertainties will influence the final results of mapping. Therefore, the effects of the uncertainties on monitoring geographical entities should be studied, in order to provide accurate information to decision makers. This paper discusses the indeterminate nature of geographic entities and its effect on change detection when they are monitored through time. The concepts of fuzzy objects and fuzzy change detection are applied to describe heterogeneous objects or objects with indeterminate boundaries, several measures for fuzzy change detection are presented to evaluate the change processes of the objects. A practical example of the dynamics of sediments along the Dutch coast is elaborated to demonstrate the approach and the concepts proposed.

[1]  Suzana Dragicevic,et al.  A fuzzy set approach for modelling time in GIS , 2000, Int. J. Geogr. Inf. Sci..

[2]  Achille C. Varzi,et al.  Fiat and Bona Fide Boundaries , 2000 .

[3]  Helen Couclelis,et al.  What Maps Mean to People: Denotation, Connotation, and Geographic Visualization in Land-Use Debates , 1997, COSIT.

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

[5]  Sucharita Gopal,et al.  Fuzzy set theory and thematic maps: accuracy assessment and area estimation , 2000, Int. J. Geogr. Inf. Sci..

[6]  Martien Molenaar,et al.  Identification of Fuzzy Objects from Field Obseravtion Data , 1997, COSIT.

[7]  T. M. Lillesand,et al.  Remote Sensing and Image Interpretation , 1980 .

[8]  Eleanor Rosch,et al.  Principles of Categorization , 1978 .

[9]  Barry Smith,et al.  Fiat and Bona Fide Boundaries: Towards on Ontology of Spatially Extended Objects , 1997, COSIT.

[10]  G. Edwards,et al.  Modeling uncertainty in photointerpreted boundaries , 1996 .

[11]  Daniel G. Brown,et al.  Classification and Boundary Vagueness in Mapping Presettlement Forest Types , 1998, Int. J. Geogr. Inf. Sci..

[12]  F. Canters,et al.  Evaluating the uncertainty of area estimates derived from fuzzy land-cover classification , 1997 .

[13]  M. Molenaar,et al.  Objects with fuzzy spatial extent , 1999 .

[14]  Ola Ahlqvist,et al.  Rough classification and accuracy assessment , 2000, Int. J. Geogr. Inf. Sci..

[15]  G. M. Foody The Continuum of Classification Fuzziness in Thematic Mapping , 1999 .