Abstract: Modelling effects of forest disturbance history on carbon balance: a deep learning approach using Landsat-time series. (2017 AGU Fall Meeting)

Modelling effects of forest disturbance history on carbon balance: a deep learning approach using Landsat-time series.

Simon Besnard^1,2, Nuno Carvalhais^2,3, Jan Clevers¹, Loïc Dutrieux⁴, Fabian Gans², Martin Herold⁵, Markus Reichstein⁶ and Martin Jung², (1)Wageningen University and Research Center, Laboratory of Geo-Information Science and Remote Sensing, Wageningen, Netherlands, (2)Max Planck Institute for Biogeochemistry, Department of Biogeochemical Integration, Jena, Germany, (3)Universidade Nova de Lisboa, Departamento de Ciências e Engenharia do Ambiente, Lisbon, Portugal, (4)National Commission for the Knowledge and Use of Biodiversity (CONABIO), Mexico City, Mexico, (5)Wageningen University and Research, Wageningen, Netherlands, (6)Max Planck Institute for Biogeochemistry, Jena, Germany

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