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

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ADS bibcode
2017AGUFM.B31A1967B
year
2017
Listed Authors
Besnard, S.
Carvalhais, N.
Clevers, J.
Dutrieux, L.
Gans, F.
Herold, M.
Reichstein, M.
Jung, M.
Listed Institutions
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research Center, Wageningen, Netherlands Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Departamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, Caparica, Portugal; Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research Center, Wageningen, Netherlands
National Commission for the Knowledge and Use of Biodiversity (CONABIO), Mexico City, Mexico
Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Laboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research Center, Wageningen, Netherlands
Department of Biogeochemical Integration, Max-Planck Institute for Biogeochemistry, Jena, Germany
Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany

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