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标题：Small-Footprint Discrete-Return LIDAR in Tree Species Recognition
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作者：I. Korpela ; T. Tokola ; H.O. Ørka 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：2016
卷号：XL-3/W4
出版社：Copernicus Publications
摘要：In forest inventories, the species information is crucial for economical, ecological and technical reasons. Species recognition is currently a bottleneck in practical remote sensing applications. Here, we examined species discrimination using tree-level LiDAR features in discrete-return data. The aim was to examine the robustness and explanatory power of the intensity and height distribution features. A dataset consisting of 13890 trees from 117 stands in southern Finland (61°50'N, 24°20'E) was used. The data of two LiDAR sensors was fused using intensity normalization in natural targets. Age dependency of first-return intensity was observed in spruce and birch trees, which needs to be considered in using LiDAR intensity metrics. Classification of Scots pine, Norway spruce and birch was tested and accuracy was 81.85%. Separation of pine and spruce was more accurate, 91.93%. We also present results for 15 rare conifer and broadleaved species. To enhance the classification accuracy of birch, we propose co-use of image features
关键词：Airborne laser scanning; Single tree; Intensity; Classification; Monoplotting; Crown modeling