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Above-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat / Stefano Puliti in Remote sensing of environment, vol 265 (November 2021)  

Public [article]  inRemote sensing of environment > vol 265 (November 2021) . - n° 112644 Titre : Above-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat Type de document : Article/Communication Auteurs : Stefano Puliti, Auteur ; Johannes Breidenbach, Auteur ; Johannes Schumacher, Auteur ; Marius Hauglin, Auteur ; T.F. Klingenberg, Auteur ; Rasmus Astrup, Auteur Année de publication : 2021 Article en page(s) : n° 112644 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] biomasse aérienne [Termes IGN] estimation statistique [Termes IGN] forêt boréale [Termes IGN] image Landsat [Termes IGN] image Sentinel-MSI [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Norvège [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] puits de carbone [Termes IGN] surveillance forestière Résumé : (auteur) This study aimed at estimating total forest above-ground net change (ΔAGB; Gg) over five years (2014–2019) based on model-assisted estimation utilizing freely available satellite imagery. The study was conducted for a boreal forest area (approx. 1.4 Mha) in Norway where bi-temporal national forest inventory (NFI), Sentinel-2, and Landsat data were available. Biomass change was modelled based on a direct approach. The precision of estimates using only the NFI data in a basic expansion estimator was compared to four different alternative model-assisted estimates using 1) Sentinel-2 or Landsat data, and 2) using bi- or uni-temporal remotely sensed data. We found that spaceborne optical data improved the precision of the purely field-based estimates by a factor of up to three. The most precise estimates were found for the model-assisted estimation using bi-temporal Sentinel-2 (standard error; SE = 1.7 Gg). However, the decrease in precision when using Landsat data was small (SE = 1.92 Gg). We also found that ΔAGB could be precisely estimated when remotely sensed data were available only at the end of the monitoring period. We conclude that satellite optical data can considerably improve ΔAGB estimates, when repeated and coincident field data are available. The free availability, global coverage, frequent update, and long-term time horizon make data from programs such as Sentinel-2 and Landsat a valuable data source for consistent and durable monitoring of forest carbon dynamics. Numéro de notice : A2021-938 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112644 Date de publication en ligne : 25/08/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112644 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99746 [article]