Search results for "YIELD ESTIMATION"

showing 2 items of 2 documents

Early assessment of crop yield from remotely sensed water stress and solar radiation data

2018

Soil moisture (SM) available for evapotranspiration is crucial for food security, given the significant interannual yield variability of rainfed crops in large agricultural regions. Also, incoming solar radiation (Rs) influences the photosynthetic rate of vegetated surfaces and can affect productivity. The aim of this work is to evaluate the ability of crop water stress and Rs remotely sensed data to forecast yield at regional scale. Temperature Vegetation Dryness Index (TVDI) was computed as an indicator of crop water stress and soil moisture availability. TVDI during critical growth stage of crops was calculated from MODIS products: MODIS/AQUA 8-day composite LST at 1 km and 16-day compos…

Limiting factor010504 meteorology & atmospheric sciences0211 other engineering and technologies02 engineering and technologyGeociencias multidisciplinariaAtmospheric sciences01 natural sciencesCiencias de la Tierra y relacionadas con el Medio AmbienteCropYIELD ESTIMATIONYield (wine)EvapotranspirationComputers in Earth SciencesEngineering (miscellaneous)Water content021101 geological & geomatics engineering0105 earth and related environmental sciencesEVAPOTRANSPIRATIONCrop yieldFOOD SECURITYCROP WATER STRESSVegetationAtomic and Molecular Physics and OpticsComputer Science ApplicationsSoil waterEnvironmental scienceCIENCIAS NATURALES Y EXACTASISPRS Journal of Photogrammetry and Remote Sensing
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Synergistic integration of optical and microwave satellite data for crop yield estimation

2019

Developing accurate models of crop stress, phenology and productivity is of paramount importance, given the increasing need of food. Earth observation (EO) remote sensing data provides a unique source of information to monitor crops in a temporally resolved and spatially explicit way. In this study, we propose the combination of multisensor (optical and microwave) remote sensing data for crop yield estimation and forecasting using two novel approaches. We first propose the lag between Enhanced Vegetation Index (EVI) derived from MODIS and Vegetation Optical Depth (VOD) derived from SMAP as a new joint metric combining the information from the two satellite sensors in a unique feature or des…

Signal Processing (eess.SP)FOS: Computer and information sciencesEarth observationCoefficient of determinationTeledetecció010504 meteorology & atmospheric sciencesEnhanced vegetation index0208 environmental biotechnologyFOS: Physical sciencesSoil Science02 engineering and technologyStatistics - Applications01 natural sciencesArticleModerate resolution imaging spectroradiometer (MODIS)Robustness (computer science)Machine learningLinear regressionFOS: Electrical engineering electronic engineering information engineeringFeature (machine learning)Kernel ridge regressionCrop yield estimationVegetation optical depthApplications (stat.AP)Electrical Engineering and Systems Science - Signal ProcessingComputers in Earth Sciences0105 earth and related environmental sciencesRemote sensingMathematics2. Zero hungerCrop yieldProcessos estocàsticsGeologyEnhanced vegetation indexAgro-ecosystems020801 environmental engineeringPhysics - Data Analysis Statistics and ProbabilityMetric (mathematics)Soil moisture active passive (SMAP)Data Analysis Statistics and Probability (physics.data-an)Imatges Processament
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