Afficher la notice abrégée

dc.rights.licenseopenen_US
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorPROENCA, Barbara
hal.structure.identifierLaboratoire d'études en Géophysique et océanographie spatiales [LEGOS]
dc.contributor.authorFRAPPART, Frédéric
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorLUBAC, Bertrand
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorMARIEU, Vincent
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorYGORRA, Bertrand
hal.structure.identifierLaboratoire de l'intégration, du matériau au système [IMS]
dc.contributor.authorBOMBRUN, Lionel
ORCID: 0000-0001-9036-3988
IDREF: 137837461
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorMICHALET, Richard
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorSOTTOLICHIO, Aldo
IDREF: 158099699
dc.date.accessioned2024-02-05T14:35:54Z
dc.date.available2024-02-05T14:35:54Z
dc.date.issued2019-04
dc.identifier.issn2072-4292en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/187828
dc.description.abstractEnAn early assessment of biological invasions is important for initiating conservation strategies. Instrumental progress in high spatial resolution (HSR) multispectral satellite sensors greatly facilitates ecosystems' monitoring capability at an increasingly smaller scale. However, species detection is still challenging in environments characterized by a high variability of vegetation mixing along with other elements, such as water, sediment, and biofilm. In this study, we explore the potential of Pléiades HSR multispectral images to detect and monitor changes in the salt marshes of the Bay of Arcachon (SW France), after the invasion of Spartina anglica. Due to the small size of Spartina patches, the spatial and temporal monitoring of Spartina species focuses on the analysis of five multispectral images at a spatial resolution of 2 m, acquired at the study site between 2013 and 2017. To distinguish between the different types of vegetation, various techniques for land use classification were evaluated. A description and interpretation of the results are based on a set of ground truth data, including field reflectance, a drone flight, historical aerial photographs, GNSS and photographic surveys. A preliminary qualitative analysis of NDVI maps showed that a multi-temporal approach, taking into account a delayed development of species, could be successfully used to discriminate Spartina species (sp.). Then, supervised and unsupervised classifications, used for the identification of Spartina sp., were evaluated. The performance of the species identification was highly dependent on the degree of environmental noise present in the image, which is season-dependent. The accurate identification of the native Spartina was higher than 75%, a result strongly affected by intra-patch variability and, specifically, by the presence of areas with a low vegetation density. Further, for the invasive Spartina anglica, when using a supervised classifier, rather than an unsupervised one, the accuracy of the classification increases from 10% to 90%. However, both algorithms highly overestimate the areas assigned to this species. Finally, the results highlight that the identification of the invasive species is highly dependent both on the seasonal presence of itinerant biological features and the size of vegetation patches. Further, we believe that the results could be strongly improved by a coupled approach, which combines spectral and spatial information, i.e., pattern-recognition techniques.
dc.language.isoENen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subject.enbiological invasions
dc.subject.encoastal wetlands
dc.subject.enmulti-spectral imagery
dc.subject.enNDVI
dc.subject.enPléiades
dc.subject.enPixel classification
dc.subject.ensalt marsh
dc.subject.enSpartina anglica
dc.subject.enSpartina maritima
dc.title.enPotential of High-Resolution Pléiades Imagery to Monitor Salt Marsh Evolution After Spartina Invasion
dc.typeArticle de revueen_US
dc.identifier.doi10.3390/rs11080968en_US
dc.subject.halInformatique [cs]/Traitement du signal et de l'imageen_US
bordeaux.journalRemote Sensingen_US
bordeaux.page968en_US
bordeaux.volume11en_US
bordeaux.hal.laboratoriesEPOC : Environnements et Paléoenvironnements Océaniques et Continentaux - UMR 5805en_US
bordeaux.issue8en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.institutionBordeaux INP
bordeaux.teamMETHYSen_US
bordeaux.teamECOBIOCen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcehal
hal.identifierhal-02294897
hal.version1
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exportfalse
workflow.import.sourcehal
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing&rft.date=2019-04&rft.volume=11&rft.issue=8&rft.spage=968&rft.epage=968&rft.eissn=2072-4292&rft.issn=2072-4292&rft.au=PROENCA,%20Barbara&FRAPPART,%20Fr%C3%A9d%C3%A9ric&LUBAC,%20Bertrand&MARIEU,%20Vincent&YGORRA,%20Bertrand&rft.genre=article


Fichier(s) constituant ce document

Thumbnail
Thumbnail

Ce document figure dans la(les) collection(s) suivante(s)

Afficher la notice abrégée