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Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan / Katsuto Shimizu in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 106 (February 2022) . - n° 102658 Titre : Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan Type de document : Article/Communication Auteurs : Katsuto Shimizu, Auteur ; Tomohiro Nishizono, Auteur ; Fumiaki Kitahara, Auteur ; Keiko Fukumoto, Auteur ; Hideki Saito, Auteur Année de publication : 2022 Article en page(s) : n° 102658 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] estimation statistique [Termes IGN] hauteur des arbres [Termes IGN] image captée par drone [Termes IGN] Japon [Termes IGN] Pinophyta [Termes IGN] volume en bois Résumé : (auteur) The accurate estimation of tree attributes is essential for sustainable forest management. Terrestrial Laser Scanning (TLS) is a viable remote sensing technology suitable for estimating under canopy structure. However, TLS measurements generally underestimate tree height in taller trees, which leads to the underestimation of other tree attributes (e.g., stem volume). The integration of information derived from TLS and Unmanned Aerial Vehicle (UAV) photogrammetry could potentially improve tree height estimation. This study investigated the applicability of integrating TLS and UAV photogrammetry to estimate individual tree attributes in managed coniferous forests of Japan. Diameter at breast height (DBH), tree height, and stem volume were estimated by (1) TLS data only, (2) integrating TLS and UAV data with TLS tree locations, and (3) integrating TLS and UAV data with treetop detections of the tree canopy. The TLS data only approach achieved high accuracy for DBH estimations with a root mean squared error (RMSE) of 2.36 cm (RMSE% 5.6%); however, tree height was greatly underestimated, with an RMSE of 8.87 m (28.9%) and a bias of −8.39 m. Integrating TLS and UAV photogrammetric data improved tree height estimation accuracy for both the TLS tree location (RMSE of 1.89 m and a bias of −0.46 m) and the treetop detection (RMSE of 1.77 m and a bias of 0.36 m) approaches. Integrating TLS and UAV photogrammetric data also improved the accuracy of the stem volume estimations with RMSEs of 0.21 m3 (10.8%) and 0.21 m3 (10.5%) for the TLS tree location and treetop detection approaches, respectively. Although the tree height of suppressed trees tended to be overestimated by TLS and UAV photogrammetric data integration, a good performance was obtained for dominant trees. The results of this study indicate that the integration of TLS and UAV photogrammetry is beneficial for the accurate estimation of tree attributes in coniferous forests. Numéro de notice : A2022-071 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2021.102658 En ligne : https://doi.org/10.1016/j.jag.2021.102658 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99423 [article]