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Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables / Kimmo Nurminen in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 83 (September 2013) . - pp 104 - 115 Titre : Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables Type de document : Article/Communication Auteurs : Kimmo Nurminen, Auteur ; Mika Karjalainen, Auteur ; Xiaowei Yu, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 104 - 115 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse comparative [Termes IGN] appariement d'images [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt [Termes IGN] hauteur des arbres [Termes IGN] image aérienne [Termes IGN] modèle numérique de surface [Termes IGN] semis de points [Termes IGN] tronc Résumé : (Auteur) Recent research results have shown that the performance of digital surface model extraction using novel high-quality photogrammetric images and image matching is a highly competitive alternative to laser scanning. In this article, we proceed to compare the performance of these two methods in the estimation of plot-level forest variables. Dense point clouds extracted from aerial frame images were used to estimate the plot-level forest variables needed in a forest inventory covering 89 plots. We analyzed images with 60% and 80% forward overlaps and used test plots with off-nadir angles of between 0° and 20°. When compared to reference ground measurements, the airborne laser scanning (ALS) data proved to be the most accurate: it yielded root mean square error (RMSE) values of 6.55% for mean height, 11.42% for mean diameter, and 20.72% for volume. When we applied a forward overlap of 80%, the corresponding results from aerial images were 6.77% for mean height, 12.00% for mean diameter, and 22.62% for volume. A forward overlap of 60% resulted in slightly deteriorated RMSE values of 7.55% for mean height, 12.20% for mean diameter, and 22.77% for volume. According to our results, the use of higher forward overlap produced only slightly better results in the estimation of these forest variables. Additionally, we found that the estimation accuracy was not significantly impacted by the increase in the off-nadir angle. Our results confirmed that digital aerial photographs were about as accurate as ALS in forest resources estimation as long as a terrain model was available. Numéro de notice : A2013-490 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.06.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.06.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32628 [article]

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