标題：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)

來源出版物：REMOTE SENSING 卷：9期：3 文獻編号：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

文獻類型：Article

語種：English

作者關鍵詞： airborne laser scanning; point cloud segmentation; random forests; feature extraction; feature selection; semantic

擴展關鍵詞： AIRBORNE LIDAR DATA; LASER-SCANNING DATA; EXTRACTION; RECONSTRUCTION; DENSIFICATION; ALGORITHMS; BUILDINGS; OBJECTS; INDEX

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

電子郵件地址： 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

影響因子：3.036