Spatial Uncertainty

Uncertainty analysis is the part of risk analysis that focuses on the uncertainties in the data characteristics. Important components of uncertainty analysis include qualitative analysis that identifies the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process, and communication of the uncertainty. (Funtowwicz and Ravetz 1990, Petersen 2000, Regan et a1.2002, Katz 2002). Spatial connectivity includes neighbourhood structure between regions, where investigation of that structure includes modelling of the spatial homogeneity. The last could be illustrated by using spatial modelling techniques (like spatial autocorrelation, partition functions, and multilevel models). Spatial investigation involves stochastic modelling especially in cases where the incomplete data involves hide information’s. In this work a spatial analysis methodology was introduced and procedures to solve the problem with spatial variability are described.