Search results for "Copernicus programme"

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Deep Gaussian processes for biogeophysical parameter retrieval and model inversion

2020

Parameter retrieval and model inversion are key problems in remote sensing and Earth observation. Currently, different approximations exist: a direct, yet costly, inversion of radiative transfer models (RTMs); the statistical inversion with in situ data that often results in problems with extrapolation outside the study area; and the most widely adopted hybrid modeling by which statistical models, mostly nonlinear and non-parametric machine learning algorithms, are applied to invert RTM simulations. We will focus on the latter. Among the different existing algorithms, in the last decade kernel based methods, and Gaussian Processes (GPs) in particular, have provided useful and informative so…

Signal Processing (eess.SP)FOS: Computer and information sciencesComputer Science - Machine LearningEarth observation010504 meteorology & atmospheric sciencesIASIComputer science0211 other engineering and technologiesExtrapolation02 engineering and technologyDeep Gaussian Processes01 natural sciencesArticleMachine Learning (cs.LG)symbols.namesakeCopernicus programmeSentinelsMachine learningRadiative transferFOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal ProcessingComputers in Earth SciencesModel inversionStatistical retrievalEngineering (miscellaneous)Gaussian processChlorophyll contentMoisture021101 geological & geomatics engineering0105 earth and related environmental sciencesbusiness.industryInorganic suspended matterTemperatureInversion (meteorology)Statistical modelAtomic and Molecular Physics and OpticsComputer Science ApplicationsInfrared sounderNonlinear systemsymbolsGlobal Positioning SystemColoured dissolved matterbusinessAlgorithm
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