Fusion of MODIS and Landsat-8 Land Surface Temperature Images Using Spatio-Temporal Image Fusion Model

Achieving satellite images with high simultaneously spatial-temporal resolution has been one of the serious challenges faced by researchers in the field of remote sensing and its applications. In recent years, researchers have made serious efforts to solve the problem. In this study, producing Landsat like land surface temperature images with less than 16 day temporal resolution and over different land covers, using spatio-temporal image fusion algorithm (STI-FM) and MODIS Land surface temperature images, was investigated. The STI-FM technique consist of two main steps. First establishing a linear relationship between two consecutive MODIS LST images acquired at time 1 and time 2; then utilizing the above mentioned relationship as a function of a Landsat-8 LST image acquired at time 1 in order to predict a synthetic Landsat -8 LST image at time 2. The results showed strong linear relationship between the two consecutive MODIS images at times 1 and 2 (R2 in the range 0.85-0.95). The synthetic LST images were evaluated qualitatively and quantitatively and it was found that there is a high visual and strong agreements with the actual Landsat-8 LST images over different land covers. For example R2 and RMSE values were ranged 0.74-0.94 and 1.44-2.52, respectively.