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Estimation and mapping of forest structure parameters from open access satellite images: development of a generic method with a study case on coniferous plantation

hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorMORIN, David
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorPLANELLS, Milena
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorGUYON, Dominique
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorVILLARD, Ludovic
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
hal.structure.identifierGlobal Earth Observation
dc.contributor.authorMERMOZ, Stéphane
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorBOUVET, Alexandre
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorTHEVENON, Hervé
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorDEJOUX, Jean-François
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorLE TOAN, Thuy
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorDEDIEU, Gérard
dc.date.accessioned2024-04-08T12:03:36Z
dc.date.available2024-04-08T12:03:36Z
dc.date.issued2019
dc.identifier.issn2072-4292
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/196276
dc.description.abstractEnTemperate forests are under climatic and economic pressures. Public bodies, NGOs and the wood industry are looking for accurate, current and affordable data driven solutions to intensify wood production while maintaining or improving long term sustainability of the production, biodiversity, and carbon sequestration. Free tools and open access data have already been exploited to produce accurate quantitative forest parameters maps suitable for policy and operational purposes. These efforts have relied on different data sources, tools, and methods that are tailored for specific forest types and climatic conditions. We hypothesized we could build on these efforts in order to produce a generic method suitable to perform as well or better in a larger range of settings. In this study we focus on building a generic approach to create forest parameters maps and confirm its performance on a test site: a maritime pine (Pinus pinaster) forest located in south west of France. We investigated and assessed options related with the integration of multiple data sources (SAR L- and C-band, optical indexes and spatial texture indexes from Sentinel-1, Sentinel-2 and ALOS-PALSAR-2), feature extraction, feature selection and machine learning techniques. On our test case, we found that the combination of multiple open access data sources has synergistic benefits on the forest parameters estimates. The sensibility analysis shows that all the data participate to the improvements, that reach up to 13.7% when compared to single source estimates. Accuracy of the estimates is as follows: aboveground biomass (AGB) 28% relative RMSE, basal area (BA) 27%, diameter at breast height (DBH) 20%, age 17%, tree density 24%, and height 13%. Forward feature selection and SVR provided the best estimates. Future work will focus on validating this generic approach in different settings. It may prove beneficial to package the method, the tools, and the integration of open access data in order to make spatially accurate and regularly updated forest structure parameters maps effortlessly available to national bodies and forest organizations.
dc.language.isoen
dc.publisherMDPI
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.subjectforest plantation
dc.subjectSentinel
dc.subjectdata combinations
dc.subjectmanagement tools
dc.subject.enforest structure parameters
dc.subject.enaboveground biomass
dc.subject.enmap
dc.subject.enALOS-PALSAR
dc.subject.ensupport vector regression
dc.title.enEstimation and mapping of forest structure parameters from open access satellite images: development of a generic method with a study case on coniferous plantation
dc.typeArticle de revue
dc.identifier.doi10.3390/rs11111275
dc.subject.halSciences du Vivant [q-bio]
dc.subject.halSciences de l'environnement
bordeaux.journalRemote Sensing
bordeaux.page1-25
bordeaux.volume11
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.issue11
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-02629195
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02629195v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing&rft.date=2019&rft.volume=11&rft.issue=11&rft.spage=1-25&rft.epage=1-25&rft.eissn=2072-4292&rft.issn=2072-4292&rft.au=MORIN,%20David&PLANELLS,%20Milena&GUYON,%20Dominique&VILLARD,%20Ludovic&MERMOZ,%20St%C3%A9phane&rft.genre=article


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