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Near real-time agriculture monitoring at national scale at parcel resolution: Performance assessment of the Sen2-Agri automated system in various cropping systems around the world

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Title Near real-time agriculture monitoring at national scale at parcel resolution: Performance assessment of the Sen2-Agri automated system in various cropping systems around the world
 
Creator Defourny, Pierre
Bontemps, Sophie
Bellemans, Nicolas
Cara, Cosmin
Dedieu, Gérard
Guzzonato, Eric
Hagolle, Olivier
Inglada, Jordi
Nicola, Laurentiu
Rabaute, Thierry
Savinaud, Mickael
Udroiu, Cosmin
Valero, Silvia
Bégué, Agnès
Dejoux, Jean-François
El Harti, Abderrazak
Ezzahar, Jamal
Kussul, Nataliia
Labbassi, Kamal
Lebourgeois, Valentine
Miao, Zhang
Newby, Terrence
Nyamugama, Adolph
Salh, Norakhan
Shelestov, Andrii
Simonneaux, Vincent
Sibiry Traoré, Pierre C.
Traoré, Souleymane S
Koet, Benjamin
 
Subject agriculture
monitoring
learning
crop management
food security
climate change
geology
 
Description The convergence of new EO data flows, new methodological developments and cloud computing infrastructure calls for a paradigm shift in operational agriculture monitoring. The Copernicus Sentinel-2 mission providing a systematic 5-day revisit cycle and free data access opens a completely new avenue for near real-time crop specific monitoring at parcel level over large countries. This research investigated the feasibility to propose methods and to develop an open source system able to generate, at national scale, cloud-free composites, dynamic cropland masks, crop type maps and vegetation status indicators suitable for most cropping systems. The so-called Sen2-Agri system automatically ingests and processes Sentinel-2 and Landsat 8 time series in a seamless way to derive these four products, thanks to streamlined processes based on machine learning algorithms and quality controlled in situ data. It embeds a set of key principles proposed to address the new challenges arising from countrywide 10m resolution agriculture monitoring. The full-scale demonstration of this system for three entire countries (Ukraine, Mali, South Africa) and five local sites distributed across the world was a major challenge met successfully despite the availability of only one Sentinel-2 satellite in orbit. In situ data were collected for calibration and validation in a timely manner allowing the production of the four Sen2-Agri products over all the demonstration sites. The independent validation of the monthly cropland masks provided for most sites overall accuracy values higher than 90%, and already higher than 80% as early as the mid-season. The crop type maps depicting the 5 main crops for the considered study sites were also successfully validated: overall
 
Date 2019-02
2020-03-13T20:06:33Z
2020-03-13T20:06:33Z
 
Type Journal Article
 
Identifier Defourny P, Bontemps S, Bellemans N, Cara C, Dedieu G, Guzzonato E, Hagolle O, Inglada J, Nicola L, Rabaute T, Savinaud M, Udroiu C, Valero S, Bégué A, Dejoux JF, El Harti A, Ezzahar J, Kussul N, Labbassi K, Lebourgeois V, Miao Z, Newby T, Nyamugama A, Salh N, Shelestov A, Simonneaux V, Sibiry Traore P, Traore S, Koet B. 2019. Near real-time agriculture monitoring at national scale at parcel resolution: Performance assessment of the Sen2-Agri automated system in various cropping systems around the world. Remote Sensing of Environment 221: 551-568.
0034-4257
https://hdl.handle.net/10568/107771
https://doi.org/10.1016/j.rse.2018.11.007
 
Language en
 
Rights CC-BY-4.0
Open Access
 
Format 551-568
 
Publisher Elsevier
 
Source Remote Sensing of Environment