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Remote Sensing of Watershed

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Palabras clave – provistas por la editorial

multi-source remote sensing; aquaculture mapping; texture feature; Google Earth Engine; Pearl River Basin; land surface temperature; VIC model; wavelet analysis; multiscale analysis; LUCC; MODIS NDVI; vegetation cover; trend analysis; Sen + Mann-Kendall; topography; GWR; Qinghai-Tibet Plateau; maize yield; evapotranspiration; plastic film mulching; G-AquaCrop model; Heihe River basin; paddy rice; SEBAL; interannual variation; spatial distribution; Ganfu Plain irrigation system; vegetation browning; warming hiatus; vapor pressure deficit; spring; autumn; Xinjiang; Qijia culture (QJC); spatial diffusion patterns; cultural hearth; circle structure; dryland; SIF; EVI; TROPOMI; extreme drought; phenology; NATT; China; drought; SPEI; VPD; vegetation; GPP; water level recognition; hydrological monitoring; deep learning; computer vision; alpine wetland; water retention service; models; Qinghai–Tibetan Plateau; carbon dioxide emissions; global climate change; human footprint index; human pressures; macro control; Ebinur Lake; spatio-temporal fusion model; Sentinel-2; images reconstruction; suspended particulate matter (SPM); n/a

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libros

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Suiza