Apatial Fuzzy Classification in GIS

Spatial objects that ara represented in a conventional GIS are generally considered to be crisp and represented by determonatc boundaries.When objects change gradually and continuously over space, there are no crisp boundaries to differentiate them. The fuzzy objects, which have indeterminate spatial extent and boundaries, and must be presented accordingly in GIS.crisp boundaries specially in spatial objects (e.g.coastal zones) leads to crisp categorizing (categories with sharp boundaries ) and exploring patterns is effected by crisp categorization. Using fuzzy operations make resulting patterns more close to real world and mimic it better. Therefore using fuzzy concepts for data mining and exploring volumeness data warehouse is appropriate.

Keywords:

Geospatial information Systeme (GIS) , Geispatial Classification , Fuzzy logic , Data Mining