文章基本信息

标题：Improving the Morphological Analysis for Tree Extraction: a Dynamic Approach to Lidar Data
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作者：A. Barilotti ; F. Sepic ; E. Abramo 等
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：2007
卷号：XXXVI-3/W52
页码：26-31
出版社：Copernicus Publications
摘要：The improvement of laser scanning as a proficient technology to better understand the complexity of the forest has recently allowed the detection of the forestry parameters at tree level. From a forest inventory point of view, however, a common use of such technology is related to the accuracy that can be obtained if vast and differently composed forestry surfaces are considered. In this paper, an improvement in the morphological analysis methods for tree extraction is presented. The method, developed in an open source environment, is based on the automatic determination of the forest structure by means of some LiDAR-extracted vegetation indexes. The study site is located in some mountainous parts of Friuli Venezia Giulia (N-E Italy) characterized by coniferous, mixed and broad-leaved forests with high variability in terms of population densities and composition. The results have been validated using topographic total station data surveyed in situ, in 13 forestry sample plots with a total of about 550 reference trees. Moreover, some further datasets have been studied by mean of photo-interpretation process on high resolution aerial images. The paper highlights the advantages of using this dynamic approach for tree extraction
关键词：LiDAR; Tree extraction; Morphological analysis; Region Growing; Vegetation indexes; Dynamic approaches