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Comparaison de méthodes de spatialisation pour l'agrégation par parcelle des estimations de paramètres forestiers par LiDAR aéroporté

Abstract : While the use of field plots and airborne LiDAR data for the estimation of forest parameters has been intensively investigated in the past ten years, the issue of the evaluation of their accuracy at the compartment level (surface of a few hectares)remains poorly documented. Based on a full-calliper inventory of 35 compartments representing 380 ha, the present study compares different strategies for the mapping of LiDAR predictions and their aggregation by compartment. Results show that the prediction error decreases between estimations at the plot and those at the compartment levels : from 15 to 6.4%for basal area, 26 to 7.7% for stem density and 6.5 to 3.4% for mean diameter. At the compartment level, a LiDAR-based inventory thus displays an accuracy similar to a full-calliper inventory, for basal area. For the mapping step, it is crucial to respect the size of field plots used for calibration, whereas for the aggregation step the handling of compartment borders remains tricky for all forest parameters.
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Submitted on : Saturday, May 16, 2020 - 8:23:35 AM
Last modification on : Friday, December 17, 2021 - 9:38:03 AM

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J.M. Monnet, A. Munoz. Comparaison de méthodes de spatialisation pour l'agrégation par parcelle des estimations de paramètres forestiers par LiDAR aéroporté. Revue Française de Photogrammétrie et de Télédétection, Société Française de Photogrammétrie et de Télédétection, 2015, 1 (211-212), pp.93-102. ⟨10.52638/rfpt.2015.548⟩. ⟨hal-02603041⟩

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