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Palabras clave – provistas por la editorial

feature selection; spectral angle mapper; support vector machine; support vector regression; hyperspectral imaging; UAV; cross-scale; yellow rust; spatial resolution; winter wheat; MODIS; northern Mongolia; remote sensing indices; spring wheat; yield estimation; UAV-based LiDAR; biomass; crop height; field phenotyping; oasis crop type mapping; Sentinel-1 and 2 integration; statistically homogeneous pixels (SHPs); red-edge spectral bands and indices; recursive feature increment (RFI); random forest (RF); unmanned aerial vehicles (UAVs); remote sensing (RS); thermal UAV RS; thermal infrared (TIR); precision agriculture (PA); crop water stress monitoring; plant disease detection; vegetation status monitoring; Landsat; data blending; crop yield prediction; gap-filling; volumetric soil moisture; synthetic aperture radar (SAR); Sentinel-1; soil moisture semi-empirical model; soil moisture Karnataka India; reflectance; digital number (DN); vegetation index (VI); Parrot Sequoia (Sequoia); DJI Phantom 4 Multispectral (P4M); Synthetic Aperture Radar; SAR; lodging; Hidden Markov Random Field; HMRF; CDL; corn; soybean; crop Monitoring; crop management; apple orchard damage; polarimetric decomposition; entropy; anisotropy; alpha angle; storm damage mapping; economic loss; insurance support