Fuzzy Bayesian Semantic Kriging

The spatial semantic kriging (SemK) based interpolation approach is an attempt to amalgamate semantic knowledge into the prediction process. It considers land-use/land-cover (LULC) information for the land–atmospheric interaction modeling to achieve better prediction outcome. However, the correlation study between every pair of LULC classes in SemK is a-priori, which is not a pragmatic approach. In this a-priori process, the influences of other nearby LULC classes is ignored in the interpolation process. This chapter establishes a modification of spatial SemK by extending this process with an a-posterior probability-based correlation analysis among different LULC classes. The fuzzy Bayesian network principle is utilized here to carry out the probabilistic analysis. The empirical evaluations with real land surface temperature data shows the need for probability-based correlation analysis in SemK by achieving more prediction accuracy.