Investigating operational country-level crop monitoring with Sentinel~1 and~2 imagery
In: ISSN: 2150-704X, 2021
Online
academicJournal
Zugriff:
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.
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Investigating operational country-level crop monitoring with Sentinel~1 and~2 imagery
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| Autor/in / Beteiligte Person: | David, Nicolas ; Giordano, Sébastien ; Mallet, Clément ; 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) |
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| Zeitschrift: | ISSN: 2150-704X, 2021 |
| Veröffentlichung: | HAL CCSD ; Taylor and Francis, 2021 |
| Medientyp: | academicJournal |
| DOI: | 10.1080/2150704X.2021.1950940 |
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