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Classification and Deforestation Monitoring Using Sentinel-1 C-SAR Images in a Temperate Exploited Pine Forest

hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
hal.structure.identifierVisioTerra
dc.contributor.authorYGORRA, B.
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorFRAPPART, Frédéric
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorJ.-P., Wigneron
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorMOISY, Christophe
hal.structure.identifierInstitut de Recherche pour le Développement (IRD en Occitanie) [IRD (Occitanie)]
dc.contributor.authorPILLOT, B
hal.structure.identifierDirection Régionale de l’Agriculture, de l’Alimentation et de la Forêt [DRAAF]
dc.contributor.authorPUISEUX, J.
hal.structure.identifierVisioTerra
dc.contributor.authorRIAZANOFF, S.
dc.date.accessioned2024-04-08T11:44:07Z
dc.date.available2024-04-08T11:44:07Z
dc.date.issued2023
dc.date.conference2022-07-17
dc.identifier.isbn978-1-6654-2792-0
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195138
dc.description.abstractEnEarth Observation data is often used for land cover classification or change monitoring. It is rarely used for both goals in a single algorithm. The multi-change Cumulative Sum (CuSum) algorithm proposed in this study allows both classification and change monitoring in a single algorithm using Sentinel-1 C-SAR time series. The multi-change CuSum approach allowed to classify pixels belonging to the fused non-forest vegetation and bare soil classes apart from the pixels belonging to new cuts. The distinction of each class is better made using the two polarizations: VV is more accurate for detecting non-forest vegetation (Kappa coefficient of 0.62) and VH for detecting new cuts (Kappa coefficient of 0.65). The algorithm showed an accuracy up to 0.82.
dc.language.isoen
dc.publisherIEEE
dc.source.titleIEEE International Symposium on Geoscience and Remote Sensing IGARSS
dc.subject.enCuSum
dc.subject.enSentinel-1
dc.subject.enC-SAR
dc.subject.envegetation cover change
dc.subject.entemperate forest
dc.subject.endeforestation
dc.subject.enclassification
dc.title.enClassification and Deforestation Monitoring Using Sentinel-1 C-SAR Images in a Temperate Exploited Pine Forest
dc.typeCommunication dans un congrès
dc.identifier.doi10.1109/IGARSS46834.2022.9884389
dc.subject.halSciences de l'environnement
bordeaux.page691-694
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.conference.titleIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
bordeaux.countryMY
bordeaux.title.proceedingIEEE International Symposium on Geoscience and Remote Sensing IGARSS
bordeaux.conference.cityKuala Lumpur
bordeaux.peerReviewedoui
hal.identifierhal-04099628
hal.version1
hal.invitednon
hal.proceedingsnon
hal.conference.end2022-07-22
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04099628v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=IEEE%20International%20Symposium%20on%20Geoscience%20and%20Remote%20Sensing%20IGARSS&rft.date=2023&rft.spage=691-694&rft.epage=691-694&rft.au=YGORRA,%20B.&FRAPPART,%20Fr%C3%A9d%C3%A9ric&J.-P.,%20Wigneron&MOISY,%20Christophe&PILLOT,%20B&rft.isbn=978-1-6654-2792-0&rft.genre=unknown


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