Discrimination of vegetation strata in a multi-layered Mediterranean forest ecosystem using height and intensity information derived from airborne laser scanning

REMOTE SENSING OF ENVIRONMENT

卷:114

Article

Morsdorf, Felix¹  Marell, Anders^2,3  Cassagne, Nathalie²  Pimont, Francois²  Rigolot, Eric² 

[1] Univ Zurich, Remote Sensing Labs, Inst Geog, CH-8057 Zurich, Switzerland

[2] INRA, URFM, UR 629, F-84914 Avignon, France

[3] Irstea, UR EFNO, F-45290 Nogent Sur Vernisson, France

关键词: Airborne laser scanning;    LiDAR;    Shrubland;    Wildland fires;    Cluster analysis;    Canopy profile;    Supervised classification;    Vertical stratification;    Gaussian mixture models;    Multi-layered ecosystems;   

DOI  :  10.1016/j.rse.2010.01.023

来源: Elsevier

【 摘 要 】

Height and intensity information derived from Airborne Laser Scanning (ALS) was used to obtain a quantitative vertical stratification of vegetation in a multi-layered Mediterranean ecosystem. A new methodology for the separation of different vegetation strata was implemented using supervised classification of a two-dimensional feature space spanned by ALS return height (terrain corrected) and intensity. The classification was carried out using Gaussian mixture models tuned on a control plot. The approach was validated using extensive field measurements from treated plots, ranging from single vegetation strata to a more complex multi-layered ecosystem. Plot-level canopy profiles derived from ALS and from a geometric reconstruction based on field measurements were in very good agreement, with correlation coefficients ranging from 0.73 (for complex, 3-layered) to 0.96 (simple, single-layered). In addition, it was possible to derive plot-level information on layer height, vertical extent and coverage with absolute accuracies of some decimetres (simple plots) to a meter (complex plots) for both height and vertical extent and about 10 to 15% for layer coverage. The approach was then used to derive maps of the layer height, vertical extent and percentage of ground cover for a larger area, and classification accuracy was evaluated on a per-pixel basis. The method performed best for single-layered plots or dominant layers on multi-layered plots, obtaining an overall accuracy of 80 to 90%. For subdominant layers in the more complex plots, accuracies obtained were as low as 48%. Our results demonstrate the possibility of deriving qualitative (presence and absence of specific vegetation layers) and quantitative, physical data ( height, vertical extent and ground cover) describing the vertical structure of complex multi-layered forest ecosystems using ALS-based height and intensity information. (C) 2010 Elsevier Inc. All rights reserved.

【 授权许可】

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