Spatial and Temporal Resolution Improvement of Actual Evapotranspiration Maps Using Landsat and MODIS Data Fusion

Producing daily actual evapotranspiration (ET a ) maps with high spatial resolution has always been challenge for remote sensing research. This study assessed the feasibility of producing ET (30 m) sugarcane farmlands Amir Kabir Sugarcane Agro-industry (Khuzestan, Iran) using three different scenarios. In first scenario, reflectance bands Landsat 8 were predicted from moderate imaging spectroradiometer (MODIS) imagery and temporal adaptive fusion model (STARFM) algorithm. Also, thermal by spatiotemporal data algorithm temperature mapping (SADFAT). Then, amounts calculated employing such surface energy balance land (SEBAL). second input needed SEBAL downscaled MODIS images methods. SEBAL, 30 m calculated. third acquired to scale 8. scenarios, downscaling was carried out ratio, regression, neural networks methods two approaches. approach, image on day 1 relationship between other days used. simulated previous consecutive Comparing derived 8, scenario had best result an RMSE (root mean square error) 0.68 mm ?1 . The method used in approach worst 2.25 , which however better than 3.19 developed this offers efficient inexpensive way produce resolution. Furthermore, we suggest that STARFM SADFAT algorithms have acceptable accuracies simulation homogeneous areas.