Spatial interpolation using conservative fuzzy reasoning

Abstract

Spatial interpolation is an important feature of a Geographic Information System, which is the procedure used to estimate values at unknown locations within the area covered by existing observations. In this paper, we propose a conservative spatial interpolation technique that incorporates the advantages of local interpolation, Euclidean interpolation, and conservative fuzzy reasoning. The main objective of this paper is to formulate a computationally efficient spatial interpolation technique similar to the IDWA technique that can be used in real time application. The main feature of our spatial interpolation technique is inherited from the concept used in conservative fuzzy interpolation reasoning for interpolating fuzzy rules in sparse fuzzy rule bases. Illustration examples from a rainfall spatial interpolation problem are also used to illustrate the applicability of the proposed technique.