Computational grids and remote sensing-based analysis of thermal environment of a geographic area

The paper describes a service for using on Computational Grids, that highlights the variations in the thermal environment that exist throughout a region due to different land cover types. The paper addresses a Supervised Classification algorithm and the computation of Normalized Difference Vegetation Index (NDVI), Land Surface Emissivity (LSE) and Land Surface Temperature (LST) based on satellite imagery for a certain geographic area. A Web-based client interface was also built. We consider the service will be greatly useful and convenient for those who are studying the ground thermal environment and urban heat island effects by using Landsat TM/ETM+ bands, and have typical workstations, with no special computing and storing resources for computationally intensive satellite image processing and no license for a commercial image processing tool.