Change detection assessment using fuzzy sets and remotely sensed data: an application of topographic map revision

This paper explores a methodology for computing the amount of changes that have occurred within an area by using remotely sensed technologies and fuzzy modelling. The discussion concentrates on the formulation of a standard procedure that, using the concept of fuzzy sets and fuzzy logic, can define the likelihood of changes detected from remotely sensed data. Furthermore, an example of how fuzzy visualisation of areas undergoing changes can be incorporated into a decision support system for prioritisation of areas requiring topographic map revision and updating is presented. By adapting the membership function of the fuzzy model to fit the shape of the histogram characterising the change image (derived from any of the common pre-classification methods of change detection), areas can be identified according to their likelihood of having undergone change during the period of observation. (C) 1999 Elsevier Science B.V. All rights reserved.