Multi-level filtering segmentation to measure individual tree parameters based on Lidar data: Application to a mountainous forest with heterogeneous stands |
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| Authors: | Cédric Véga Sylvie Durrieu |
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| Institution: | 1. UMR TETIS Cemagref-Cirad-ENGREF, Maison de la Télédétection en Languedoc-Roussillon, 500, rue J.F. Breton BP 5095, 34196 Montpellier Cedex 05, France;2. French Institute of Pondicherry (UMIFRE 21 CNRS-MAEE), Laboratory of Applied Informatics and Geomatics, 11, Saint Louis Street, Pondicherry - 605 001, India |
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| Abstract: | This paper presents a method for individual tree crown extraction and characterisation from a canopy surface model (CSM). The method is based on a conventional algorithm used for localising LM on a smoothed version of the CSM and subsequently for modelling the tree crowns around each maximum at the plot level. The novelty of the approach lies in the introduction of controls on both the degree of CSM filtering and the shape of elliptic crowns, in addition to a multi-filtering level crown fusion approach to balance omission and commission errors. The algorithm derives the total tree height and the mean crown diameter from the elliptic tree crowns generated. The method was tested and validated on a mountainous forested area mainly covered by mature and even-aged black pine (Pinus nigra ssp. nigra Arn.]) stands. Mean stem detection per plot, using this method, was 73.97%. Algorithm performance was affected slightly by both stand density and heterogeneity (i.e. tree diameter classes’ distribution). The total tree height and the mean crown diameter were estimated with root mean squared error values of 1.83 m and 1.48 m respectively. Tree heights were slightly underestimated in flat areas and overestimated on slopes. The average crown diameter was underestimated by 17.46% on average. |
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| Keywords: | Lidar Airborne laser scanning Mountainous forests Tree extraction Canopy surface model |
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