Evapotranspiration and Vegetation Cover Classifications Maps Based on Cloud Computing at the Arab Countries Scale

作者：Mohammed A. El-Shirbeny, Çhandrashekhar Biradar, Kamel Amer, Supria Paul · 发表于：Earth Systems and Environment · 年份：2022 · DOI：10.1007/s41748-022-00320-2 · 被引用次数：25 · 研究领域：Plant Water Relations and Carbon Dynamics、Climate variability and models、Urban Heat Island Mitigation

Abstract According to the most recent Köppen–Geiger classification, Arab countries are divided into seven climate classes. Ground data availability is limited in developing countries, and ground meteorological data are scarce and concentrated in a few locations, rather than station maintenance capability being adequate for the responsibilities. The current study uses remote sensing and meteorological data to create regional classification maps of reference evapotranspiration (ETo), potential crop evapotranspiration, and vegetation cover in Arab countries from 2005 to 2020. The Stand-alone Remote Sensing Approach to Estimate Reference Evapotranspiration (SARE) was used to estimate ETo using satellite data from 2005 to 2020. The Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) were extracted from MODIS satellite data and used in the SARE model, in addition to elevation (E), Julian day (J), and Latitude (Lat). To validate the SARE model results, the FAO-Penman–Monteith model was applied to 35 ground meteorological stations distributed across Arab countries to cover all climate classes based on the most recent Köppen–Geiger climate classification. Google Earth Engine was used to create the classification. The statistical indices produced acceptable results, with average RMSE values ranging from 6.9 to 17.3 (mm/month), while correlation coefficient ( r ) and index of agreement ( d ) values are more significant than 0.9. To be included in the ETc cal...