Articles | Volume 13, issue 12
https://doi.org/10.5194/essd-13-5951-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-5951-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Harmonized in situ datasets for agricultural land use mapping and monitoring in tropical countries
Audrey Jolivot
CORRESPONDING AUTHOR
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Valentine Lebourgeois
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Louise Leroux
CIRAD, UPR AIDA, Dakar, Senegal
AIDA, Univ Montpellier, CIRAD, Montpellier, France
Centre de Suivi Ecologique (CSE), Dakar, Senegal
Mael Ameline
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Valérie Andriamanga
CIRAD, UMR TETIS, 34398 Montpellier, France
Centre National de la Recherche Appliquée au Développement
Rural (FOFIFA), Antsirabe, Madagascar
Beatriz Bellón
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Mathieu Castets
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Arthur Crespin-Boucaud
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Pierre Defourny
Université Catholique de Louvain (UCLouvain), Louvain-la-Neuve,
Belgium
Santiana Diaz
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Mohamadou Dieye
Institut Sénégalais de Recherches Agricoles (ISRA), Dakar,
Senegal
Stéphane Dupuy
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Rodrigo Ferraz
Brazilian Agricultural Research Corporation (EMBRAPA), Rio de Janeiro,
Brazil
Raffaele Gaetano
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Marie Gely
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Camille Jahel
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Bertin Kabore
independent consultant: Ouagadougou, Burkina Faso
Camille Lelong
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Guerric le Maire
CIRAD, UMR Eco&Sols, 34398 Montpellier, France
Eco&Sols, Univ Montpellier, CIRAD, INRAE, Institut Agro, IRD,
Montpellier, France
Danny Lo Seen
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Martha Muthoni
independent consultant: Nairobi, Kenya
Babacar Ndao
Centre de Suivi Ecologique (CSE), Dakar, Senegal
Institute of Environmental Sciences, Université Cheikh Anta Diop de Dakar (UCAD), Dakar, Senegal
Terry Newby
Agricultural Research Council (ARC), Pretoria, South Africa
Cecília Lira Melo de Oliveira Santos
Interdisciplinary Center on Energy Planning, NIPE, University of
Campinas, UNICAMP, Campinas, São Paulo 13083-896, Brazil
Eloise Rasoamalala
CIRAD, UMR TETIS, 34398 Montpellier, France
Centre National de la Recherche Appliquée au Développement
Rural (FOFIFA), Antsirabe, Madagascar
Margareth Simoes
Brazilian Agricultural Research Corporation (EMBRAPA), Rio de Janeiro,
Brazil
Ibrahima Thiaw
Institute of Environmental Sciences, Université Cheikh Anta Diop de Dakar (UCAD), Dakar, Senegal
Alice Timmermans
Université Catholique de Louvain (UCLouvain), Louvain-la-Neuve,
Belgium
Annelise Tran
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
Agnès Bégué
CIRAD, UMR TETIS, 34398 Montpellier, France
TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE,
Montpellier, France
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Cited
13 citations as recorded by crossref.
- Digital In Situ Data Collection in Earth Observation, Monitoring and Agriculture—Progress towards Digital Agriculture M. Teucher et al. 10.3390/rs14020393
- Maintaining the register of agricultural lands as a real step towards the implementation of the data management function for these lands by the state T. Papaskiri et al. 10.1051/e3sconf/202339504003
- Location, biophysical and agronomic parameters for croplands in northern Ghana J. Gómez-Dans et al. 10.5194/essd-14-5387-2022
- Two Years of Cotton (Gossypium hirsutum L.) Data from the Georgia Coastal Plain, USA A. Coffin et al. 10.1038/s41597-024-03716-z
- A constrastive semi-supervised deep learning framework for land cover classification of satellite time series with limited labels D. Ienco et al. 10.1016/j.neucom.2023.127031
- A spatialized assessment of ecosystem service relationships in a multifunctional agroforestry landscape of Senegal L. Leroux et al. 10.1016/j.scitotenv.2022.158707
- Crop area change in the context of civil war in Tigray, Ethiopia S. Peterson et al. 10.1088/2976-601X/ad3559
- Is a village level always relevant to describe land cover changes? Analysing the landscape to understand socio-environmental changes in western Burkina Faso S. Caillault & M. Marie 10.1016/j.landusepol.2023.106569
- A robust method for mapping soybean by phenological aligning of Sentinel-2 time series X. Huang et al. 10.1016/j.isprsjprs.2024.10.015
- Building a community-based open harmonised reference data repository for global crop mapping H. Boogaard et al. 10.1371/journal.pone.0287731
- Multisensor Temporal Unsupervised Domain Adaptation for Land Cover Mapping With Spatial Pseudo-Labeling and Adversarial Learning E. Capliez et al. 10.1109/TGRS.2023.3297077
- Harmonized in situ datasets for agricultural land use mapping and monitoring in tropical countries A. Jolivot et al. 10.5194/essd-13-5951-2021
- Temporal-Domain Adaptation for Satellite Image Time-Series Land-Cover Mapping With Adversarial Learning and Spatially Aware Self-Training E. Capliez et al. 10.1109/JSTARS.2023.3263755
10 citations as recorded by crossref.
- Digital In Situ Data Collection in Earth Observation, Monitoring and Agriculture—Progress towards Digital Agriculture M. Teucher et al. 10.3390/rs14020393
- Maintaining the register of agricultural lands as a real step towards the implementation of the data management function for these lands by the state T. Papaskiri et al. 10.1051/e3sconf/202339504003
- Location, biophysical and agronomic parameters for croplands in northern Ghana J. Gómez-Dans et al. 10.5194/essd-14-5387-2022
- Two Years of Cotton (Gossypium hirsutum L.) Data from the Georgia Coastal Plain, USA A. Coffin et al. 10.1038/s41597-024-03716-z
- A constrastive semi-supervised deep learning framework for land cover classification of satellite time series with limited labels D. Ienco et al. 10.1016/j.neucom.2023.127031
- A spatialized assessment of ecosystem service relationships in a multifunctional agroforestry landscape of Senegal L. Leroux et al. 10.1016/j.scitotenv.2022.158707
- Crop area change in the context of civil war in Tigray, Ethiopia S. Peterson et al. 10.1088/2976-601X/ad3559
- Is a village level always relevant to describe land cover changes? Analysing the landscape to understand socio-environmental changes in western Burkina Faso S. Caillault & M. Marie 10.1016/j.landusepol.2023.106569
- A robust method for mapping soybean by phenological aligning of Sentinel-2 time series X. Huang et al. 10.1016/j.isprsjprs.2024.10.015
- Building a community-based open harmonised reference data repository for global crop mapping H. Boogaard et al. 10.1371/journal.pone.0287731
3 citations as recorded by crossref.
- Multisensor Temporal Unsupervised Domain Adaptation for Land Cover Mapping With Spatial Pseudo-Labeling and Adversarial Learning E. Capliez et al. 10.1109/TGRS.2023.3297077
- Harmonized in situ datasets for agricultural land use mapping and monitoring in tropical countries A. Jolivot et al. 10.5194/essd-13-5951-2021
- Temporal-Domain Adaptation for Satellite Image Time-Series Land-Cover Mapping With Adversarial Learning and Spatially Aware Self-Training E. Capliez et al. 10.1109/JSTARS.2023.3263755
Latest update: 20 Nov 2024
Short summary
This paper presents nine standardized crop type reference datasets collected between 2013 and 2020 in seven tropical countries. It aims at participating in the difficult exercise of mapping agricultural land use through satellite image classification in those complex areas where few ground truth or census data are available. These quality-controlled datasets were collected in the framework of the international JECAM initiative and contain 27 074 polygons documented by detailed keywords.
This paper presents nine standardized crop type reference datasets collected between 2013 and...
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