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hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorGUYON, Dominique
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLAVENTURE, Sylvio
hal.structure.identifierInstitut National de l'Information Géographique et Forestière [IGN] [IGN]
dc.contributor.authorBELOUARD, Thierry
hal.structure.identifierTelespazio
dc.contributor.authorSAMALENS, Jean-Charles
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorWIGNERON, Jean-Pierre
dc.date.accessioned2024-04-08T11:59:22Z
dc.date.available2024-04-08T11:59:22Z
dc.date.issued2015
dc.date.conference2015-07-26
dc.identifier.isbn978-1-4799-7929-5
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195988
dc.description.abstractEnThe availability of Landsat data (Landsat 4, 5, 7 and 8) from ~30 years makes it possible to analyze the forest long term dynamics at high resolution (30m). The performances of the Landsat time-series have been already demonstrated for mapping and monitoring the annual clear-cuts and the storm damage in the Landes Forest, that covers ∼1 million ha in southwestern France and that is heavily managed with even-aged stands with rather short rotations after clear-cut harvesting. Our objectives aimed at improving, automating, and enriching these previous methods. This was to operationally produce over the whole Landes Forest not only (1) the annual maps of clear-cutting from 1984 up the current year but also (2) the map of the current age that was derived from the forest change detected every year since 1984. The developed methodology used the time-series of surface reflectance and cloud mask provided for Landsat by USGS and sought to cope the possible absence of cloud-free image during the interest season or the numerous missing data in Landsat 7 images after 2002. The retrospective processing of the Landsat time-series from 1984 to 2014 made it possible the prediction of actual current age with a satisfactory accuracy.
dc.language.isoen
dc.publisherIEEE Geoscience and Remote Sensing Society
dc.publisher.locationPiscataway (united states)
dc.source.titleIEEE International Geoscience and Remote Sensing Symposium Proceedings
dc.subjectdynamics
dc.subject.enLandsat
dc.subject.enage
dc.subject.enclear-cutting
dc.subject.enforest
dc.subject.enforest change
dc.subject.enlong-term
dc.title.enRetrieving the stand age from a retrospective detection of multinannual forest changes using Landsat data. Application on the heavily managed maritime pine forest in Southwestern France from a 30-year Landsat time-series (1984-2014)
dc.typeCommunication dans un congrès
dc.identifier.doi10.1109/IGARSS.2015.7326182
dc.subject.halSciences du Vivant [q-bio]
dc.subject.halSciences de l'environnement
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.conference.titleGeoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
bordeaux.countryIT
bordeaux.title.proceedingIEEE International Geoscience and Remote Sensing Symposium Proceedings
bordeaux.conference.cityMilan
bordeaux.peerReviewedoui
hal.identifierhal-02740624
hal.version1
hal.invitednon
hal.proceedingsnon
hal.conference.organizerIEEE Geoscience and Remote Sensing Society (GRSS). USA.
hal.conference.end2015-07-31
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02740624v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=IEEE%20International%20Geoscience%20and%20Remote%20Sensing%20Symposium%20Proceedings&rft.date=2015&rft.au=GUYON,%20Dominique&LAVENTURE,%20Sylvio&BELOUARD,%20Thierry&SAMALENS,%20Jean-Charles&WIGNERON,%20Jean-Pierre&rft.isbn=978-1-4799-7929-5&rft.genre=unknown


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