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Forest cover mapping based on a combination of aerial images and Sentinel-2 satellite data compared to National Forest Inventory data / Selina Ganz in Forests, vol 11 n° 12 (December 2020)  

Public [article]  inForests > vol 11 n° 12 (December 2020) . - n° 1322 Titre : Forest cover mapping based on a combination of aerial images and Sentinel-2 satellite data compared to National Forest Inventory data Type de document : Article/Communication Auteurs : Selina Ganz, Auteur ; Petra Adler, Auteur ; Gerald Kändler, Auteur Année de publication : 2020 Article en page(s) : n° 1322 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative [Termes IGN] Bade-Wurtemberg (Allemagne) [Termes IGN] carte forestière [Termes IGN] image aérienne [Termes IGN] image Sentinel-MSI [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle numérique de surface [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Research Highlights: This study developed the first remote sensing-based forest cover map of Baden-Württemberg, Germany, in a very high level of detail. Background and Objectives: As available global or pan-European forest maps have a low level of detail and the forest definition is not considered, administrative data are often oversimplified or out of date. Consequently, there is an important need for spatio-temporally explicit forest maps. The main objective of the present study was to generate a forest cover map of Baden-Württemberg, taking the German forest definition into account. Furthermore, we compared the results to NFI data; incongruences were categorized and quantified. Materials and Methods: We used a multisensory approach involving both aerial images and Sentinel-2 data. The applied methods are almost completely automated and therefore suitable for area-wide forest mapping. Results: According to our results, approximately 37.12% of the state is covered by forest, which agrees very well with the results of the NFI report (37.26% ± 0.44%). We showed that the forest cover map could be derived by aerial images and Sentinel-2 data including various data acquisition conditions and settings. Comparisons between the forest cover map and 34,429 NFI plots resulted in a spatial agreement of 95.21% overall. We identified four reasons for incongruences: (a) edge effects at forest borders (2.08%), (b) different forest definitions since NFI does not specify minimum tree height (2.04%), (c) land cover does not match land use (0.66%) and (d) errors in the forest cover layer (0.01%). Conclusions: The introduced approach is a valuable technique for mapping forest cover in a high level of detail. The developed forest cover map is frequently updated and thus can be used for monitoring purposes and for assisting a wide range of forest science, biodiversity or climate change-related studies. Numéro de notice : A2020-845 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f11121322 Date de publication en ligne : 12/12/2020 En ligne : https://doi.org/10.3390/f11121322 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98633 [article]