cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14977626
title: Canopy height map in Iberian Peninsula - Predicted from GEDI-Sentinel based UNET model - 2017

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

Find out more...

 

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.
DOI: 10.5281/zenodo.14977728
title: Canopy height map 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

Find out more...

 

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.
DOI: 10.15468/dl.c85592
title: Occurrence Download

description: A dataset containing 121 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Prosopis juliflora var. juliflora)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 121 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023135-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14649953
title: Canopy height map in Iberian Peninsula - Predicted from ALS-Sentinel based UNET model - 2021

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

Find out more...

 

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.
DOI: 10.5281/zenodo.14649954
title: Canopy height map in Iberian Peninsula - ALS based - 2021

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 model and data, please contact the corresponding author for more details.

 

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 2 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
Find out more...

 

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.
DOI: 10.5281/zenodo.14977506
title: Canopy height map in Iberian Peninsula - Predicted from ALS-Sentinel based UNET model - 2021

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

Find out more...

 

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.
DOI: 10.15468/dl.228545
title: Occurrence Download

description: A dataset containing 45472 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mythimna unipuncta (Haworth, 1809)"
 ]
}

 The dataset includes 45472 records from 282 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023134-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t7afcv
title: Occurrence Download

description: A dataset containing 300549 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Turdus iliacus Linnaeus, 1758",
 "Year 1950-2000"
 ]
}

 The dataset includes 300549 records from 298 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069901-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yzkb8g
title: Occurrence Download

description: A dataset containing 340 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Jacquemontia heterantha (Nees & Mart.) Hallier fil."
 ]
}

 The dataset includes 340 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0256222-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2ya6s7
title: Occurrence Download

description: A dataset containing 1265 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Plethodon cheoah Highton & Peabody, 2000)"
 ]
}

 The dataset includes 1265 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005105-240202131308920/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gsp3e8
title: Occurrence Download

description: A dataset containing 157 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (CHN.6_1, CHN.HKG, CHN.MAC)",
 "OccurrenceStatus is Present",
 "TaxonKey is Oligodon formosanus (Günther, 1872)"
 ]
}

 The dataset includes 157 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027807-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x4pgfh
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ipomoea jalapoides Griseb."
 ]
}

 The dataset includes 24 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0253895-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fayt65
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is MEX.21.210_2",
 "TaxonKey is Coleoptera"
 ]
}

 The dataset includes 12 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0256223-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q77nrx
title: Occurrence Download

description: A dataset containing 153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (CHN.6_1, CHN.HKG, CHN.MAC)",
 "OccurrenceStatus is Present",
 "TaxonKey is Ptyas mucosa (Linnaeus, 1758)"
 ]
}

 The dataset includes 153 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027822-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.djqyt9
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Zea mays L.",
 "Year 2000-2023"
 ]
}

 The dataset includes 51 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0253882-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jnucws
title: Occurrence Download

description: A dataset containing 5346 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Araneidae specimen database of Osaka Museum of Natural History"
 ]
}

 The dataset includes 5346 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005100-240202131308920/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fktb5c
title: Occurrence Download

description: A dataset containing 292 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Adenocline Turcz."
 ]
}

 The dataset includes 292 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0256226-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q5nynm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Culicidae",
 "Country is Latvia"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027809-230530130749713/datasets/export for details.
DOI: 10.15468/dl.ph8bbj
title: Occurrence Download

description: A dataset containing 119501 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Crocodylia"
 ]
}

 The dataset includes 119501 records from 334 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005099-240202131308920/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w9ueem
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ipomoea jacalana Matuda"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0253893-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a3dj8q
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Culicidae",
 "Country is Macao"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027813-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5vjnn2
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Jacquemontia guaranitica Hassl."
 ]
}

 The dataset includes 34 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0256218-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hbgtqv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is incertae sedis",
 "Year is greater than 2013",
 "Geometry MULTIPOLYGON (((12.29322 44.354729,12.292916 44.355783,12.302003 44.355058,12.30251 44.355315,12.303097 44.354972,12.304491 44.35485,12.306615 44.355577,12.308252 44.35572,12.309929 44.355916,12.31043 44.356064,12.310795 44.356488,12.313433 44.359618,12.313562 44.359886,12.314201 44.360466,12.315056 44.360848,12.315401 44.36092,12.318399 44.361154,12.318407 44.361159,12.319165 44.361164,12.320832 44.360517,12.320917 44.360019,12.321475 44.359819,12.321794 44.360109,12.322639 44.359883,12.322438 44.359502,12.323576 44.359272,12.323557 44.359134,12.323345 44.358962,12.323362 44.358279,12.323882 44.356988,12.32507 44.355975,12.325271 44.355331,12.326351 44.35347,12.326792 44.351841,12.327903 44.349469,12.330098 44.345321,12.305974 44.335898,12.305243 44.335536,12.303491 44.340224,12.29322 44.354729)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027834-230530130749713/datasets/export for details.
DOI: 10.15468/dl.xwjfk7
title: Occurrence Download

description: A dataset containing 72363 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is ICN - Universidad Nacional de Colombia"
 ]
}

 The dataset includes 72363 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005106-240202131308920/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.