Approximate analysis of binary topological relations between geographic regions with indeterminate boundaries

Abstract The development of formal models of spatial relations is a topic of great importance in spatial reasoning, geographic information systems (GIS) and computer vision, and has gained much attention from researchers across these research areas during the past two decades. In recent years significant achievements have been made on the development of models of spatial relations between spatial objects with precisely defined boundaries. However, these models cannot be directly applied to spatial objects with indeterminate boundaries which are found in many applications in geographic analysis and image understanding. This article develops a method for approximately analyzing binary topological relations between geographic regions with indeterminate boundaries based upon previous work on topological spatial relations and fuzzy sets. In addition, examples are given to demonstrate the method and related concepts. It is shown that the eight binary topological relations between regions in a two-dimensional space can be easily determined by the method.

[1]  Fangju Wang,et al.  Fuzzy Representation of Geographical Boundaries in GIS , 1996, Int. J. Geogr. Inf. Sci..

[2]  P. Burrough,et al.  Geographic Objects with Indeterminate Boundaries , 1996 .

[3]  Azriel Rosenfeld,et al.  Degree of adjacency or surroundedness , 1984, Pattern Recognit..

[4]  MAX J. EGENHOFER,et al.  Point Set Topological Relations , 1991, Int. J. Geogr. Inf. Sci..

[5]  Ronald F. Abler,et al.  The National Science Foundation National Center for Geographic Information and Analysis , 1987, Int. J. Geogr. Inf. Sci..

[6]  Eliseo Clementini,et al.  A Small Set of Formal Topological Relationships Suitable for End-User Interaction , 1993, SSD.

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

[8]  F. Benjamin Zhan,et al.  Topological relations between fuzzy regions , 1997, SAC '97.

[9]  Donna Peuquet,et al.  An algorithm to determine the directional relationship between arbitrarily-shaped polygons in the plane , 1987, Pattern Recognit..

[10]  A. Rosenfeld,et al.  Fuzzy rectangles , 1990, Pattern Recognit. Lett..

[11]  D. Unwin Geographical information systems and the problem of 'error and uncertainty' , 1995 .

[12]  N. Hazelton,et al.  Topological structures for 4-dimensional geographic information systems , 1992 .

[13]  Donna J. Peuquet,et al.  Representations of Geographic Space: Toward a Conceptual Synthesis , 1988 .

[14]  Max J. Egenhofer,et al.  Deriving the Composition of Binary Topological Relations , 1994, J. Vis. Lang. Comput..

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

[16]  Eliseo Clementini,et al.  Approximate topological relations , 1997, Int. J. Approx. Reason..

[17]  Marie-Christine Jaulent,et al.  A general approach to parameter evaluation in fuzzy digital pictures , 1987, Pattern Recognit. Lett..

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

[19]  Gudula Retz-Schmidt,et al.  Various Views on Spatial Prepositions , 1988, AI Mag..

[20]  Azriel Rosenfeld,et al.  Fuzzy Digital Topology , 1979, Inf. Control..

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

[22]  James M. Keller,et al.  Quantitative analysis of properties and spatial relations of fuzzy image regions , 1993, IEEE Trans. Fuzzy Syst..

[23]  David Altman,et al.  Fuzzy Set Theoretic Approaches for Handling Imprecision in Spatial Analysis , 1994, Int. J. Geogr. Inf. Sci..