Search results for "Hybrid Retrieval Workflow"

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Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery

2022

Earth observation offers an unprecedented opportunity to monitor intensively cultivated areas providing key support to assess fertilizer needs and crop water uptake. Routinely, vegetation traits mapping can help farmers to monitor plant development along the crop’s phenological cycle, which is particularly relevant for irrigated agricultural areas. The high spatial and temporal resolution of the Sentinel-2 (S2) multispectral instrument leverages the possibility to estimate leaf area index (LAI), canopy chlorophyll content (CCC), and vegetation water content (VWC) from space. Therefore, our study presents a hybrid retrieval workflow combining a physically-based strategy with a machine learni…

Leaf Area IndexVegetation Water and Chlorophyll ContentActive LearningContenido de Agua y Clorofila de la VegetaciónDimencionality ReductionÍndice de Superficie FoliarAprendizaje ActivoReducción de DimensionalidadKrigingImágenesHybrid Retrieval WorkflowFlujo de Trabajo de Recuperación HíbridoGeneral Earth and Planetary SciencesImageryleaf area index; vegetation water and chlorophyll content; Gaussian processes regression; hybrid retrieval workflow; dimensionality reduction; active learningKrigeageRemote Sensing
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