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ReCuSum: A polyvalent method to monitor tropical forest disturbances

hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
hal.structure.identifierVisioTerra
dc.contributor.authorBERTRAND, Ygorra
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.authorCHRISTOPHE, Moisy
hal.structure.identifierUMR 228 Espace-Dev, Espace pour le développement
dc.contributor.authorTHIBAULT, Catry
hal.structure.identifierUMR 228 Espace-Dev, Espace pour le développement
dc.contributor.authorBENJAMIN, Pillot
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorJONAS, Courtalon
hal.structure.identifierUMR 228 Espace-Dev, Espace pour le développement
dc.contributor.authorANNA, Kharlanova
hal.structure.identifierVisioTerra
dc.contributor.authorSERGE, Riazanoff
dc.date.accessioned2024-04-08T11:40:48Z
dc.date.available2024-04-08T11:40:48Z
dc.date.issued2023-09
dc.identifier.issn0924-2716
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195053
dc.description.abstractEnChange detection methods based on Earth Observations are increasingly used to monitor rainforest in the intertropical band. Until recently, deforestation monitoring was mainly based on remotely sensed optical images which often face limitations in humid tropical areas due to frequent cloud coverage. This leads to late detections of disturbance events. Since the launch of Sentinel-1 acquiring images with a revisit time of 12 days and a spatial resolution of 5 x 20 m in Brazil, Synthetic Aperture Radar (SAR) images have been increasingly used to monitor deforestation. In this study, we propose a multitemporal version of the change detection method we previously applied to timeseries of Sentinel-1 SAR images, to monitor deforestation/degradation in the Congo rainforest. Our approach is based on a Cumulative Sum (CuSum) method combined with a spatial recombination of Critical Thresholds (CuSum cross-Tc). The newly developed multitemporal CuSum method (ReCuSum) was applied to a time-series of 82 dual polarization (VH, VV) Ground Range Detected (GRD) Sentinel-1 images acquired in the Para State, in the Brazilian Amazonia, from 29/09/2016 to 01/07/2019. The ReCuSum method consists of iteratively applying the CuSum cross-Tc to monitor multiple changes in a time-series by splitting the time-series at each date of detected change and by independently iterating over the time periods resulting from the splits. The number of changes in the time-series was then analysed according to the vegetation type (Forest, non-forest vegetation) determined by visual inspection of optical Sentinel-2 image and PlanetScope monthly mosaic. This showed a difference between non-forest vegetation and forested areas. A threshold based on the number of changes (Tnbc) was then developed to differentiate forest from non-forest disturbances. The ability to monitor non-forest vegetation was analysed: the CuSum cross-Tc detected up to 90% of the total non-forest vegetation area over the study region in the past period. After removing past disturbances and past non-forest vegetation, then removing the pixels covered with non-forest vegetations based on Tnbc, the application of the ReCuSum led to a precision of 81%, a recall of 68%, a kappa coefficient of 0.72 and a F1-score of 0.74 in forest disturbance monitoring. According to these results, ReCuSum applied to Sentinel-1 time-series of images can be used for efficient forest disturbance monitoring and for generating a forest / non-forest map after the application of newly developed post-processing steps. Sentinel-1 imagery can be used for both Forest / Non-forest mapping and for forest disturbance detection. ReCuSum was released as an open-source GIT project available at: https://forgemia. inra.fr/bertrand.ygorra/cusum-deforestation_monitoring.
dc.language.isoen
dc.publisherElsevier
dc.subject.enRemote Sensing
dc.subject.enSentinel-1
dc.subject.enCumulative Sum Algorithm
dc.subject.enTropical Deforestation
dc.subject.enMultiple Change Detection
dc.subject.enForest/Non-Forest
dc.subject.enmap
dc.title.enReCuSum: A polyvalent method to monitor tropical forest disturbances
dc.typeArticle de revue
dc.identifier.doi10.1016/j.isprsjprs.2023.08.006
dc.subject.halSciences de l'environnement
bordeaux.journalISPRS Journal of Photogrammetry and Remote Sensing
bordeaux.page358-372
bordeaux.volume203
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-04288649
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04288649v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=ISPRS%20Journal%20of%20Photogrammetry%20and%20Remote%20Sensing&rft.date=2023-09&rft.volume=203&rft.spage=358-372&rft.epage=358-372&rft.eissn=0924-2716&rft.issn=0924-2716&rft.au=BERTRAND,%20Ygorra&FRAPPART,%20Fr%C3%A9d%C3%A9ric&J.-P.,%20Wigneron&CHRISTOPHE,%20Moisy&THIBAULT,%20Catry&rft.genre=article


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