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Palabras clave – provistas por la editorial

hyperspectral; spectroscopy; equivalent water thickness; canopy water content; agriculture; EnMAP; LAI; LCC; FAPAR; FVC; CCC; PROSAIL; GPR; machine learning; active learning; Landsat 8; surface reflectance; LEDAPS; LaSRC; 6SV; SREM; NDVI; artificial neural networks; canopy chlorophyll content; INFORM; leaf area index; SAIL; fluorescence; in vivo; spectrometry; ASD Field Spec; lead ions; remote sensing indices; meteosat second generation (MSG); biophysical parameters (LAI; FAPAR); SEVIRI; climate data records (CDR); stochastic spectral mixture model (SSMM); Satellite Application Facility for Land Surface Analysis (LSA SAF); the fraction of radiation absorbed by photosynthetic components (FAPARgreen); triple-source; leaf area index (LAI); woody area index (WAI); clumping index (CI); Moderate Resolution Imaging Spectroradiometer (MODIS); soil albedo; unmanned aircraft vehicle; multispectral sensor; vegetation indices; rapeseed crop; site-specific farming; Sentinel-2; forest; vegetation radiative transfer model; Discrete Anisotropic Radiative Transfer (DART) model; MODIS; fraction of photosynthetically active radiation absorbed by vegetation (FPAR); three-dimensional radiative transfer model (3D RTM); uncertainty assessment; vertical foliage profile (VFP); terrestrial laser scanning (TLS); airborne laser scanning (ALS); spaceborne laser scanning (SLS); riparian; invasive vegetation; burn severity; canopy loss; wildfire