Land surface temperature - Based spatial interpolation using a modified Inverse Distance Weighting method

Abstract

The aim of this study is to design a spatial interpolation system integrating long years' monthly average (LYMA) land surface temperature (LST) and air temperature (Ta) data from meteorological stations. A new modified Inverse Distance Weighting (M-IDW) method is proposed for this purpose along with a sustainable geographical information system (GIS). An application is presented for Eastern Thrace, which is located in Southeast Europe. The results show that if sufficient amount of image and cloudless pixels are assembled in the LST computation, the natural structure and characteristic were reflected better using the proposed system as compared to the standard IDW. The proposed method seems to yield more accurate results than standard IDW particularly in spring, summer and autumn.