文献类型：期刊文献

英文题名：Evaluating Different Methods for Estimating Diameter at Breast Height from Terrestrial Laser Scanning

作者：Liu, Chang[1] Xing, Yanqiu[1] Duanmu, Jialong[1] Tian, Xin[2]

第一作者：Liu, Chang

通信作者：Xing, YQ[1]

机构：[1]Northeast Forestry Univ, Coll Engn & Technol, Ctr Forest Operat & Environm, Harbin 150040, Heilongjiang, Peoples R China;[2]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China

年份：2018

卷号：10

期号：4

外文期刊名：REMOTE SENSING

收录：;EI(收录号：20181805115555);Scopus(收录号：2-s2.0-85045973054);WOS:【SCI-EXPANDED(收录号:WOS:000435187500025)】；

基金：This work is supported by the Special Fund for Forest Scientific Research in the Public Welfare (No. 201504319), the National Key R&D Program of China (Granted: 2017YFD0600904), and the National Basic Research Program of China (Granted: 2013CB733404).

语种：英文

外文关键词：TLS; DBH; estimation algorithm; preprocessing condition; natural secondary forest; plantation

摘要：The accurate measurement of diameter at breast height (DBH) is essential to forest operational management, forest inventory, and carbon cycle modeling. Terrestrial laser scanning (TLS) is a measurement technique that allows rapid, automatic, and periodical estimates of DBH information. With the multitude of DBH estimation approaches available, a systematic study is needed to compare different algorithms and evaluate the ideal situations to use a specific algorithm. To contribute to such an approach, this study evaluated three commonly used DBH estimation algorithms: Hough-transform, linear least square circle fitting, and nonlinear least square circle fitting. They were each evaluated on their performance using two forest types of TLS data under numerous preprocessing conditions. The two forest types were natural secondary forest and plantation. The influences of preprocessing conditions on the performance of the algorithms were also investigated. Results showed that among the three algorithms, the linear least square circle fitting algorithm was the most appropriate for the natural secondary forest, and the nonlinear least square circle fitting algorithm was the most appropriate for the plantation. In the natural secondary forest, a moderate gray scale threshold of three and a slightly large height bin of 0.24 m were the optimal parameters for the appropriate algorithm of the multi-scan scanning method, and a moderate gray scale threshold of three and a large height bin of 1.34 m were the optimal parameters for the appropriate algorithm of the single-scan scanning method. A small gray scale threshold of one and a small height bin of 0.1 m were the optimal parameters for the appropriate algorithm of the single-scan scanning method in the plantation.