Fusion of Visible and Thermal Infrared Remote Sensing Data Based on GA-SOFM Neural Network

An approach which can take advantage of high spatial resolution feature of visible data and high temporal resolution feature of thermal infrared data,is adapted by a nonlinear fusion method based on GA-SOFM-ANN to map the relation between retrieved land surface parameters from visible data and temperature.According to this method,a result of fusing both visible data with spatial resolution feature and thermal infrared data with temporal feature is finished.A case of testing method is showed,utilizing the ASTER data.The conclusions show that it is a new approach to quickly estimate and acquire high resolution land surface temperature.