0000000000653925

AUTHOR

Gonçal Grau-muedra

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Multitemporal and multiresolution leaf area index retrieval for operational local rice crop monitoring

2016

Abstract This paper presents an operational chain for high-resolution leaf area index (LAI) retrieval from multiresolution satellite data specifically developed for Mediterranean rice areas. The proposed methodology is based on the inversion of the PROSAIL radiative transfer model through the state-of-the-art nonlinear Gaussian process regression (GPR) method. Landsat and SPOT5 data were used for multitemporal LAI retrievals at high-resolution. LAI estimates were validated using time series of in situ LAI measurements collected during the rice season in Spain and Italy. Ground LAI data were collected with smartphones using PocketLAI, a specific phone application for LAI estimation. Temporal…

2. Zero hunger010504 meteorology & atmospheric sciencesMean squared error0211 other engineering and technologiesSoil ScienceGeologyInversion (meteorology)02 engineering and technologyCrop monitoring; Rice; Leaf area index (LAI) retrieval; PROSAIL; Smartphone; Gaussian process regression (GPR); Landsat; SPOT5 Take501 natural sciencesAtmospheric radiative transfer codesKrigingSatellite dataGround-penetrating radarEnvironmental scienceComputers in Earth SciencesLeaf area indexRice crop021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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