Estimation of LST from multi-sensor thermal remote sensing data and evaluating the influence of sensor characteristics.

ABSTRACT Remote sensing science has proven fruitful for land surface temperature (LST) determination contrary to other techniques used especially for the rugged terrain like the Himalayan mountain system. In this study, an attempt has been made to estimate the land surface temperature in parts of Chenab basin, Jammu & Kashmir, by using Landsat-7 ETM+, TM, and Terra ASTER satellite data. The current study basically utilizes different surface temperature estimation techniques i.e. Reference Channel Method (RCM), Emissivity Normalization Method (ENM), Classification based and Stefan Boltzmann’s approach to inter-compare various temperature estimation techniques and to examine the influence of the difference in sensor characteristics on the estimated surface temperature on a glacier terrain. For the effect of spatial resolution variation in the determined (LST) values for ETM+ and TM was estimated and for radiometric resolution, effect comparison was carried between the ETM+ and ASTER-derived LST image. Furthermore, an effect of spatial resolution has been quantified and has been evaluated successfully due to the fact that two sensors used for the purpose did not differ much in their characteristics features