Nyhet

Photogrammetry Principles and Applications

LiDAR 3D Point Cloud Intelligent Processing

AvJonathan Li,Yiping Chen

Häftad, Engelska, 2026

Del i serien Earth Observation

1 837 kr

Kommande

Beskrivning

Photogrammetry Principles and Applications: LiDAR 3D Point Cloud Intelligent Processing addresses the growing demand for advanced 3D point cloud processing in geospatial and Earth observation fields. With LiDAR technology playing a vital role in autonomous driving, smart cities, and environmental monitoring, this book offers a systematic overview of core algorithms, including 3D reconstruction, DEM generation, and semantic segmentation, utilizing cutting-edge artificial intelligence methods like deep learning and large language models. It combines foundational knowledge with practical case studies from diverse regions such as Toronto, Xiamen, and Nanjing, illustrating how these techniques are applied in real-world scenarios. The content spans hardware descriptions, software workflows, and algorithmic insights, making it suitable for both self-study and academic courses. Featuring templates, flow diagrams, step-by-step processes, and tables, the book ensures ease of cross-referencing and practical understanding. It empowers researchers, students, and industry professionals to process complex, massive point cloud data efficiently, leading to more accurate spatial analysis, environmental assessments, and urban planning. By integrating AI into traditional photogrammetric workflows, this volume paves the way for innovations in geospatial intelligence and autonomous systems.

Delivers a comprehensive introduction to point cloud intelligent processing
Incorporates recent AI algorithms, including deep learning and large language models
Explains cutting-edge AI methods for 3D modeling and semantic segmentation

Produktinformation

Utgivningsdatum:2026-08-01
Mått:152 x 229 x undefined mm
Format:Häftad
Språk:Engelska
Serie:Earth Observation
Antal sidor:380
Förlag:Elsevier Science
ISBN:9780443516979

Utforska kategorier

Geografi inom Naturvetenskap och teknik

Mer om författaren

Jonathan Li is currently a Professor of Geomatics and Systems Design Engineering in the Department of Geography and Environmental Management, with a cross-appointment in the Department of Systems Design Engineering at the University of Waterloo, Canada. He is a Fellow of the Canadian Academy of Engineering, the Royal Society of Canada (Academy of Science), the Engineering Institute of Canada, and IEEE. Dr. Li serves as the President of the Canadian Institute of Geomatics and is the Editor-in-Chief of the International Journal of Applied Earth Observation and Geoinformation (JAG). His primary research interests include AI-empowered Earth observation for geospatial mapping and LiDAR remote sensing for digital twin cities and autonomous driving. He has co-authored over 600 publications, more than 300 of which have appeared in top remote sensing journals and leading computer vision and AI conferences. His work has garnered over 20,000 citations on Google Scholar, with an h-index of 76. Additionally, he has supervised over 200 master's and Ph.D. students, as well as postdoctoral fellows and visiting scholars, to successful completion. Yiping Chen is an Associate Professor at Sun Yat-sen University, China, specializing in mobile laser scanning data analysis, 3D point cloud computer vision, and autonomous driving. She has published over 70 peer-reviewed articles in leading journals such as ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, and IEEE Transactions on Intelligent Transportation Systems. Her work has been presented at major conferences including CVPR, IGARSS, and ISPRS; and she received the 2020 Best Paper award from the Journal of Applied Geodesy. Haiyan Guan is a Senior Member of the IEEE. She is a Professor at the School of Remote Sensing and Geomatics Engineering at Nanjing University of Information Science and Technology, China. Her research interests include information extraction from LiDAR point clouds and Earth observation images. Prof. Guan has published over 40 research papers in peer-reviewed journals, books, and conference proceedings, including IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Intelligent Transportation Systems, IEEE Geoscience and Remote Sensing Letters, ISPRS Journal of Photogrammetry and Remote Sensing, as well as proceedings from IGARSS and ISPRS. Additionally, Prof. Haiyan Guan edited the book Urban Remote Sensing (Wiley, 2011) and has published more than 50 papers related to LiDAR 3D point clouds using AI.

Innehållsförteckning

1. Laser Scanners2. Laser Registration3. 3D reconstruction4. Digital Elevation Models5. Point cloud expression and description6. Point clouds detection and tracking7. Point clouds semantic segmentation8. Point clouds instance segmentation9. Point clouds interactive segmentation10. Point clouds software11. Application examples