Search results for "Índice de Superficie Foliar"

showing 2 items of 2 documents

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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Quantifying Irrigated Winter Wheat LAI in Argentina Using Multiple Sentinel-1 Incidence Angles

2022

Synthetic aperture radar (SAR) data provides an appealing opportunity for all-weather day or night Earth surface monitoring. The European constellation Sentinel-1 (S1) consisting of S1-A and S1-B satellites offers a suitable revisit time and spatial resolution for the observation of croplands from space. The C-band radar backscatter is sensitive to vegetation structure changes and phenology as well as soil moisture and roughness. It also varies depending on the local incidence angle (LIA) of the SAR acquisition’s geometry. The LIA backscatter dependency could therefore be exploited to improve the retrieval of the crop biophysical variables. The availability of S1 radar time-series data at d…

Satellite ImageryLeaf Area Indexleaf area index; Sentinel-1; time-series; local incidence angle; Whittaker smoother; Gaussian processes regressionWheatWinterGeneral Earth and Planetary SciencesInviernoSentinel-1TrigoImágenes por SatélitesÍndice de Superficie FoliarIrrigationRiegoRemote Sensing; Volume 14; Issue 22; Pages: 5867
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