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In this talk, we present our work on structure-preserving machine learning (ML) moment closure models for the radiative transfer equation. Most of the existing ML closure models are not able to guaran...
Light is reflected, transmitted and absorbed by green leaves. Chlorophyll fluorescence (ChlF) is the signal emitted by chlorophyll molecules in the leaf after the absorption of light. ChlF can be used...
A forest canopy is a complex system with a highly structural multi-scale architecture. Physical based radiative transfer (RT) modelling has been shown to be an effective tool for retrieval of vegetati...
Most methods for retrieving foliar content from hyperspectral data are well adapted either to remote-sensing scale, for which each spectral measurement has a spatial resolution ranging from a few doze...
Leaf area index (LAI) is a key variable for the understanding and modelling of several eco-physiological processes within a vegetation canopy. The LAI could thus provide vital information for the man...
Modeling of the radiation regime of a mixture of vegetation species is a fundamental problem of the Earth’s land remote sensing and climate applications. The major existing approaches, including the ...
Natural surfaces, such as vegetation and soil, do not - as a rule - reflect incident solar radiation equally in all directions. This reflectance anisotropy is formally described by a Bidirectional Re...
In the past, obtaining reliable measurements of key forest canopy metrics has been difficult, even after the development of remote sensing technology.Fortunately, next-generation lidar systems are pro...
Aerosol optical depth retrieval over land surface using remote sensing employs the use of radiative transfer simulations and/or simultaneous measurements of atmospheric parameters at the time of satel...
A method for estimation of forest parameters, species, tree shape, distance between canopies by means of Monte-Carlo based radiative transfer model with forestry surface model is proposed. The model i...

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