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Investigating operational country-level crop monitoring with Sentinel~1 and~2 imagery

Authors :
Clément Mallet
Sébastien Giordano
Nicolas David
Institut National de l'Information Géographique et Forestière [IGN] (IGN)
Laboratoire sciences et technologies de l'information géographique (LaSTIG)
Ecole des Ingénieurs de la Ville de Paris (EIVP)-École nationale des sciences géographiques (ENSG)
Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel-Institut National de l'Information Géographique et Forestière [IGN] (IGN)-Université Gustave Eiffel
Agence de Services et de Paiements
ANR-18-CE23-0023,MAESTRIA,Analysis d'images multi-modales d'observation de la Terre(2018)
Source :
Remote Sensing Letters, Remote Sensing Letters, Taylor and Francis, 2021, 12 (10), pp.970-982
Publication Year :
2021
Publisher :
Informa UK Limited, 2021.

Abstract

International audience; In this paper, we propose an operational solution for the yearly classification of crop parcels at national scale (namely France) for Land Parcel Identification System updating, under the Common Agricultural Policy (CAP) open-source framework and fed with both time series of Sentinel-1 radar and Sentinel-2 optical images, with complementary contributions. Three conceivable scenarios are investigated with two sets of nomenclatures (17 and 43 classes): early, on-line, and late classifications. Experiments performed on 2017 show very satisfactory results (82–97%), locally almost on-par with state-of-the-art deep-based methods. We can conclude our framework offers a strong basis for country-scale operational deployment for 2020+CAP.

Details

ISSN :
21507058 and 2150704X
Volume :
12
Database :
OpenAIRE
Journal :
Remote Sensing Letters
Accession number :
edsair.doi.dedup.....fe03ad7e9cd92f9b25ee72451cebfccb
Full Text :
https://doi.org/10.1080/2150704x.2021.1950940