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Urban Land Cover Classification Using Airborne LiDAR Data:A Review. The Rigorous Geometric Model of Satellite Laser Altimeter and Preliminarily Accuracy Validation. TANG Xinming, LI Guoyuan, GAO Xiaoming, et al. Geomatics and Information Science of Wuhan University, 2017, 42(2):143-149. From Earth Observation Satellite to Earth Observation Brain. Automatic Forest Mapping at Individual Tree Levels from Terrestrial Laser Scanning Point Clouds with A Hierarchical Minimum Cut Method. YANG Bisheng, DAI Wenxia, DONG Zhen, et al. ISPRS Journal of Photogrammetry and Remote Sensing, 2015(101):275-290. Flexible Building Primitives for 3D Building Modeling. XIONG B, JANCOSEK M, ELBERINK S O, et al. ISPRS Journal of Photogrammetry and Remote Sensing, 2014(93):213-226. Cycle Graph Analysis for 3D Roof Structure Modelling:Concepts and Performance. ISPRS Journal of Photogrammetry and Remote Sensing, 2016(119):373-389. Two-Step Adaptive Extraction Method for Ground Points and Breaklines from Lidar Point Clouds. YANG Bisheng, HUANG Ronggang, DONG Zhen, et al. ISPRS Journal of Photogrammetry and Remote Sensing, 2014(92):98-111. An Adaptive Surface Filter for Airborne Laser Scanning Point Clouds by Means of Regularization and Bending Energy. Journal of Zhengzhou Institute of Surveying and Mapping, 2006, 23(2):127-129. Principle and Trend of Airborne Laser Scanning Remote Sensing. Key words: 3D LiDAR, point cloud, point cloud fusion, object extraction, 3D representation, ubiquitous point cloud Finally, some future perspectives are presented. Then the typical applications of 3D LiDAR in surveying and other related fields are listed, and current challenges in point cloud processing are concluded. Following the history of 3D LiDAR, this paper first reviews the status of 3D LiDAR system, and introduces the development of key technologies in data processing. Inspired by sensor technologies and national requirements, 3D LiDAR has got great progresses in hardware, data processing and applications, and is facing new challenges. As the vital 3D geospatial data for description of the world in the digital era, 3D point cloud plays an important role not only in earth science researches but also in national requirements (e.g., global change analysis, global mapping, and smart city). 3D LiDAR can perform an intensive sampling of the earth surface in a direct way, and yield the 3D point cloud that contains numerous and scattered points with the coordinates ( X, Y, Z) and attributes (e.g., intensity).
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