期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2009
卷号：XXXVIII-3/W8
页码：129-134
出版社：Copernicus Publications
摘要：In this paper we explore the potential of LiDAR to distinguish between principal forest typology of alpine latitudes surveyed in leaf- on conditions. To this aim, a complete processing chain was developed, starting with the point cloud as input data and ending with derived curvature value of single trees useful for species classification. First, the dominant trees are detected by means of a mathematical morphology approach and the laser points are clustered as belonging to the single crowns. To enhance the quality of the calculated clusters, a statistical analysis of the height frequency distribution for each tree is performed which allows the filtering process of the low vegetation under-canopy. Afterwards a Taylor's expansion nonparametric model is applied to study the local differential properties of the surface that approximates single crowns. Classification of single species is based on the study of the surface Gaussian and mean curvatures, computed for each tree from estimated differential parameters of the Taylor's formula extended to second order terms. The extracted data are verified using very high resolution aerial photography as well as forestry typology maps and existing assessment plans. Moreover, a field survey campaign in 5 geo-referenced plots is performed in order to assess the species of single trees in the following three investigated species composition: spruce, beech and mixed forest. The results highlights that, even in leaf-on condition, the LiDAR technology can be used to determine the principal species composition and distribution of a forest at single tree level, which is very important for biodiversity maintenance, stem volume and biomass estimation, habitat mapping and conservation
关键词：LiDAR; Tree extraction; Curvature analysis; Crown delineation; Forest typology; Species
