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Estimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery / Yanan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 277 - 289 Titre : Estimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery Type de document : Article/Communication Auteurs : Yanan Liu, Auteur ; Weishu Gong, Auteur ; Yanqiu Xing, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 277 - 289 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse aérienne [Termes IGN] biomasse forestière [Termes IGN] Chine [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] hauteur des arbres [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] modèle numérique de surface [Termes IGN] polarisation Résumé : (Auteur) Accurate mapping the forest stand mean height (FSMH) and aboveground biomass (AGB) with a high spatial resolution are important for monitoring carbon stocks on Earth and the variability and trends of terrestrial carbon fluxes. The recently launched Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity to map FSMH and AGB. Here we present a methodological framework to map the FSMH and AGB at a resolution of 10 m in Yichun, Northeast China, by integrating field plots, Sentinel imagery, topographic data, and national geographical conditions monitoring data. First, a spatial continuous FSMH product was retrieved using an empirical model, which adopts the backscattering of SAR Sentinel-1B and the fraction of vegetation cover (FVC) variable from multispectral Sentinel-2A imagery. Subsequently, three AGB estimation models were developed for different forest types to link the field measurements to the FSMH, biophysical variables, spectral vegetation index, and topographic variables using the random forest algorithm. The mapping results show that the FSMH estimated using SAR backscatter values from VH polarization is more robust and accurate than that based on VV polarization. Furthermore, the three AGB estimation models based on three different forest types perform better than the model built by grouping all forest types together. The determination coefficient (R2) and root-mean-squared error (RMSE) range from 0.69 to 0.74 and 23.38 Mg/ha to 24.21 Mg/ha, respectively. Overall, our study demonstrates that the proposed methodological framework can be used to map the FSMH and AGB products at a high spatial resolution utilizing freely accessible Sentinel-1 SAR and Sentinel-2 multispectral imagery. Numéro de notice : A2019-211 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.016 Date de publication en ligne : 30/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.016 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92677 [article]

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081-2019051	RAB	Revue	Centre de documentation	En réserve L003	Disponible
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