期刊
AGRICULTURAL AND FOREST METEOROLOGY
卷 151, 期 9, 页码 1252-1266出版社
ELSEVIER
DOI: 10.1016/j.agrformet.2011.05.004
关键词
Terrestrial LiDAR Scanner; Voxel; 3D leaf area distribution; Savanna; Leaf Area Density (LAD); Leaf Area Index (LAI); Occlusion effects
资金
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Fond Quebecois de la Recherche sur la Nature et les Technologies (FQRNT) through the Global Environmental and Climate Change Centre (GEC3)
Vegetation structure parameters are key elements in the study of ecosystem functioning and global scale ecosystemic interactions. The detailed retrieval of many of these parameters by direct measurements is impractical due to the quantity of plant material in trees. Terrestrial LiDAR Scanners (TLSs) have been shown to hold great potential as an indirect means of estimating plant structure parameters with a high level of detail, while some studies identified a number of challenges inherent to this approach. In this study we investigate the use of a voxel-based approach to retrieve leaf area distribution of individual trees. The approach is based on the contact frequency method applied to co-registered TLS returns from two or more scanning positions. The contact frequency was computed for voxels being 10, 30, and 50 cm in size and subsequently corrected for the influence of occlusion effects, leaf inclination, the presence of non-photosynthetic material, and the laser beam size. The leaf area of voxels for which occlusion effects were too pronounced was estimated using modeled values based on the availability of light. We compared the TLS derived leaf area estimates against direct measurements, obtained by the harvesting of leaves, in a broad-leaved savanna of central Mali. The measured leaf area values of the sampled trees ranged from 30 to 530 m(2), and crown LAI values between 0.8 and 7.2. The leaf area estimates lay on average 14% from the reference measurements (general bias). Our method provides vertical as well as radial distributions of leaf area in individual trees, and lends itself to the estimation of savanna vegetation structural parameters with a high level of detail. (C) 2011 Elsevier B.V. All rights reserved.
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