太阳成8722(中国)有限公司-GREEN NO.1

标题：Classification of ALS Point Cloud with Improved Point Cloud Segmentation and Random Forests作者：Ni, H (Ni, Huan); Lin, XG (Lin, Xiangguo); Zhang, JX (Zhang, Jixian)

来源出版物：REMOTE SENSING 卷：9期：3 文献编号：288 DOI：10.3390/rs9030288 出版年： MAR 2017

摘要： This paper presents an automated and effective framework for classifying airborne laser scanning (ALS) point clouds. The framework is composed of four stages: (i) step-wise point cloud segmentation, (ii) feature extraction, (iii) Random Forests (RF) based feature selection and classification, and (iv) post-processing. First, a step-wise point cloud segmentation method is proposed to extract three kinds of segments, including planar, smooth and rough surfaces. Second, a segment, rather than an individual point, is taken as the basic processing unit to extract features. Third, RF is employed to select features and classify these segments. Finally, semantic rules are employed to optimize the classification result. Three datasets provided by Open Topography are utilized to test the proposed method. Experiments show that our method achieves a superior classification result with an overall classification accuracy larger than 91.17%, and kappa coefficient larger than 83.79%.

入藏号：WOS:000398720100102

文献类型：Article

语种：English

作者关键词： airborne laser scanning; point cloud segmentation; random forests; feature extraction; feature selection; semantic

扩展关键词： AIRBORNE LIDAR DATA; LASER-SCANNING DATA; EXTRACTION; RECONSTRUCTION; DENSIFICATION; ALGORITHMS; BUILDINGS; OBJECTS; INDEX

通讯作者地址：Zhang, JX (reprint author), Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

电子邮件地址： nih2015@yeah.net; linxiangguo@gmail.com; zhangjx@casm.ac.cn

地址： [Ni, Huan; Zhang, Jixian] Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 430079, Peoples R China.

[Lin, Xiangguo] Chinese Acad Surveying & Mapping, 28 Lianhuachixi Rd, Beijing 100830, Peoples R China.

研究方向：Remote Sensing

ISSN：2072-4292

影响因子：3.036