ریز مقیاس کردن زمانی و مکانی تبخیر-تعرق واقعی تصاویر لندست و مودیس

Remote sensing is a suitable method for estimating of actual evapotranspiration (AET) especially in large scales. As the estimation of AET with both high temporal and spatial resolution is impossible for most sensors such as MODIS and Landsat, it is necessary that the AET maps derived from a sensor were downscaled to another sensor using downscaling methods. The objectives of this study were to use of different scaling factors simultaneously for input parameters of SEBAL included surface albedo, normalized difference vegetation index (NDVI) and land surface temperature (LST) for spatial downscaling of AET maps derived based-MODIS (۱۰۰۰ m) images to Landsat images (۳۰ m) and also temporal downscaling of AET maps derived based Landsat (۱۶ day) images to MODIS (daily) images using input/output regression and input/output subtraction methods in a part of Mashhad plain. The results showed that the zero band emissivity of Landsat and LST of MODIS images had the best performance in spatial downscaling of AET maps. NDVI and LST of Landsat images as a scaling factor had not a good performance in spatial downscaling of AET maps in summer and spring, respectively. Considering the results of this study, it can be concluded that the zero band emissivity of Landsat and LST of MODIS images as a scaling factor for spatial downscaling of AET maps and input regression method for temporal downscaling of AET maps are suitable in Mashhad plain.  

Keywords:

تبخیر-تعرق واقعی , ریز مقیاس کردن مکانی , فاکتور مقیاس , لندست , مودیس