AUTHOR=Salehi Hamid , Shamsoddini Ali , Mirlatifi Seyed Majid , Mirgol Behnam , Nazari Meisam 

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

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 9 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2021.795287

DOI=10.3389/fenvs.2021.795287

ISSN=2296-665X

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