Introduction to LiDAR Remote Sensing - Wang, Cheng; Dong, Pinliang; Nie, Sheng; Xi, Xiaohuan; Yang, Xuebo
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Explains the fundamental concepts of LiDAR technology and its extended spaceborne, airborne, terrestrial, mobile, UAV platforms. It addresses the challenges of massive LiDAR data intelligent processing, LiDAR software, and in-depth applications. A comprehensive resource for students and practitioners in the field of LiDAR remote sensing.

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Produktbeschreibung
Explains the fundamental concepts of LiDAR technology and its extended spaceborne, airborne, terrestrial, mobile, UAV platforms. It addresses the challenges of massive LiDAR data intelligent processing, LiDAR software, and in-depth applications. A comprehensive resource for students and practitioners in the field of LiDAR remote sensing.
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Autorenporträt
Cheng Wang is a Professor at the Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), Beijing, China. He earned a PhD in remote sensing at the University of Strasbourg, France, in 2005. He presently serves as Director of the LiDAR sub-committee of Chinese National Committee of International Society for Digital Earth (CNISDE). He has over 20 years of research experience in LiDAR remote sensing mechanism, data processing and applications. He has been the Principal Investigator for over 15 national projects related to LiDAR in China. He has been teaching a LiDAR remote sensing course at the University of Chinese Academy of Sciences for about 10 years. Professor Wang has published more than 200 papers and four books and is the principal award recipient of ten domestic science and technology prizes. Xuebo Yang is an Assistant Research Fellow at the Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China. She earned a PhD at the Chinese Academy of Sciences (CAS), Beijing, China, in 2021. Her research interests include LiDAR remote sensing mechanisms, LiDAR sensor development, and LiDAR applications. She has presided over and participated in scientific research programs such as the National Natural Science Foundation of China and the National Key Research and Development Program of China. She was awarded the Xiaowen Li Remote Sensing Science Youth Award and outstanding PhD thesis of Chinese Academy of Sciences. Xiaohuan Xi is an Associate Professor and a Master Supervisor at the Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China. She earned an MS in environmental geography at Peking University, Beijing, China, in 2000. Her research interests include LiDAR data acquisition, LiDAR urban application, and agricultural application. She is the Secretary-General of the LiDAR sub-committee of the Chinese National Committee of the International Society for Digital Earth. She is the Principal Investigator of eight national scientific research projects of China and the principal award recipient of five domestic science and technology prizes. Sheng Nie is an Associate Professor at the Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China. He earned a PhD at the Chinese Academy of Sciences (CAS), Beijing, China, in 2017. His research interests include multi-mode LiDAR data processing, LiDAR for topography surveying and mapping, and LiDAR vegetation applications. He presides over the National Natural Science Foundation of China and the National Key Research and Development Program of China. He was awarded the Chinese LiDAR Young Scientist award and elected to the Youth Innovation Promotion Association of the Chinese Academy of Sciences. Pinliang Dong is a Professor and a Doctoral Supervisor in the Department of Geography and the Environment, University of North Texas (UNT), Denton, Texas. He earned a BSc at Peking University, China, an MSc at the Institute of Remote Sensing Applications (IRSA), Chinese Academy of Sciences, and a PhD at the University of New Brunswick, Canada. His research interests include LiDAR data analysis and applications in forestry and vegetation mapping, urban environments, disaster damage assessment, and geosciences.