Articles | Volume 13, issue 12
https://doi.org/10.5194/essd-13-5951-2021
https://doi.org/10.5194/essd-13-5951-2021
Data description paper
 | 
23 Dec 2021
Data description paper |  | 23 Dec 2021

Harmonized in situ datasets for agricultural land use mapping and monitoring in tropical countries

Audrey Jolivot, Valentine Lebourgeois, Louise Leroux, Mael Ameline, Valérie Andriamanga, Beatriz Bellón, Mathieu Castets, Arthur Crespin-Boucaud, Pierre Defourny, Santiana Diaz, Mohamadou Dieye, Stéphane Dupuy, Rodrigo Ferraz, Raffaele Gaetano, Marie Gely, Camille Jahel, Bertin Kabore, Camille Lelong, Guerric le Maire​​​​​​​, Danny Lo Seen, Martha Muthoni, Babacar Ndao, Terry Newby, Cecília Lira Melo de Oliveira Santos, Eloise Rasoamalala, Margareth Simoes, Ibrahima Thiaw, Alice Timmermans, Annelise Tran, and Agnès Bégué

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Cited articles

Alemohammad, S. H., Ballantyne, A., Bromberg Gaber, Y., Booth, K., Nakanuku-Diggs, L., and Miglarese, A. H.: LandCoverNet: A Global Land Cover Classification Training Dataset, Radiant MLHub [data set], available at: https://radiant-mlhub.s3-us-west-2.amazonaws.com/landcovernet/Documentation.pdf, last access: 7 September 2020. 
Auricht, C., Dixon, J., Boffa, J.-M., and Garrity, D.: Farming Systems of Africa, in: Atlas of African agriculture research and development: Revealing agriculture's place in Africa, 14–15, https://doi.org/10.2499/9780896298460_06, 2014. 
Bégué, A., Arvor, D., Bellon, B., Betbeder, J., de Abelleyra, D., Ferraz, R. P. D., Lebourgeois, V., Lelong, C., Simões, M., and Verón, S. R.: Remote Sensing and Cropping Practices: A Review, Remote Sens., 10, 99, https://doi.org/10.3390/rs10010099, 2018. 
Bellón, B., Bégué, A., Lo Seen, D., Lebourgeois, V., Evangelista, B. A., Simões, M., and Demonte Ferraz, R. P.: Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach, Int. J. Appl. Earth Obs. Geoinf., 68, 127–138, https://doi.org/10.1016/j.jag.2018.01.019​​​​​​​, 2018. 
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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.
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