Tree coverage ratio in Iberian Peninsula predicted from GEDI-Sentinel based UNET model - 2018
Description
This is the data used or generated in the paper, "Canopy height and biomass distribution across the forests of Iberian Peninsula".
Authors
Yang Su a, b, c, Martin Schwartz b, Ibrahim Fayad b, García Alonso Mariano d, Miguel A. Zavala e, Julián Tijerín-Triviño e, Julen Astigarraga e, Verónica Cruz f, Siyu Liu g, Xianglin Zhang c, h, Songchao Chen h,i, François Ritter b, Nikola Besic j, Alexandre d'Aspremont a, Philippe Ciais b
Affiliations
a Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France
b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France
c UMR ECOSYS, INRAE AgroParisTech, Université Paris-Saclay, 91120 Palaiseau, France
d University of Alcalá, Department of Geology, Geography and the Environment, Enviromental Remote Sensing Research Group, 28801 Alcalá de Henares, Spain
e University of Alcalá, Department of Life Sciences, 28801 Alcalá de Henares, Spain
f Department of Biodiversity, Ecology and Evolution, Complutense University of Madrid, 28040 Madrid, Spain
g Department of Geosciences and Natural Resource Management, Copenhagen University, 1958 Frederiksberg, Denmark
h College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China
i ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, 311215 Hangzhou, China
j IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France
Corresponding Author
Yang Su
yang.su@ens.fr
+33 1 89 10 07 67
École normale supérieure - PSL
To use the data, please cite this study, and in case of difficulties when using the model and data, please contact the corresponding author for further details and possible assistance
The maps of canopy height and above-ground biomass provided by this study can be found on Zenodo, detailed information about how to access those datasets can be found in Table 1-5 in this study. A preview of those maps can be found here: https://ens-yangsu-forest-spain-als.projects.earthengine.app/view/ai4forest-iberian-peninsula
Funding
Artificial Intelligence for forest monitoring from space – AI4Forests
Agence Nationale de la Recherche
MAZ, JTT, JA and VCA acknowledge support from the Spanish Ministry of Science and Innovation (grant LARGE, Nº PID2021-123675OB-C41).
MG acknowledges support from the Spanish Ministry of Science and Innovation (grant REMOTE, Nº PID2021-123675OB-C42).
VCA was supported by the Ministry of Universities, Spain, and Next Generation-EU, with “Maria Zambrano” fellowship.
Files
Predicted_tree_coverage_ratio_from_GEDI_Sentinel_based_UNET_model_2018_batch_0.tif
Files
(45.8 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:713f84138e1e9aa6ffcd3e9dce665579
|
3.5 GB | Preview Download |
|
md5:e4713719fbc1ba954419288e0ea55e35
|
3.5 GB | Preview Download |
|
md5:e78e1bf3e9f5795b0027aaab2c42e854
|
3.5 GB | Preview Download |
|
md5:1f7431acb2d67293120b5367c62b7381
|
3.5 GB | Preview Download |
|
md5:36628144897f146637ec1bf385eaf3f9
|
3.5 GB | Preview Download |
|
md5:3120e66b2064186e18f231eddf03d6e4
|
428.1 MB | Preview Download |
|
md5:f12eb3617fed068fd7b048d9b55c2050
|
3.5 GB | Preview Download |
|
md5:a7a0b706deb99be56e376b0b89255852
|
3.3 GB | Preview Download |
|
md5:c1576c4eeae3cf42d3b791ccf17567a1
|
3.6 GB | Preview Download |
|
md5:207983d2d947539c5e2c686bc5ab9486
|
3.5 GB | Preview Download |
|
md5:545eba2746c0b898dd0c98403ab32871
|
3.5 GB | Preview Download |
|
md5:d483a799bd8ff66c6da84d414f9bcbad
|
3.5 GB | Preview Download |
|
md5:785583a130d30c907f23742befe47f33
|
3.5 GB | Preview Download |
|
md5:fb4838ea0c7f2fe97a534130e99f3012
|
3.5 GB | Preview Download |