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Cover: 9780128238943 | LiDAR Principles, Processing and Applications in Forest Ecology | Buch
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Lidar Principles, Processing and Applications in Forest Ecology
Taschenbuch von Qinghua Guo (u. a.)
Sprache: Englisch

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Beschreibung
LiDAR Principles, Processing and Applications in Forest Ecology introduces the principles of LiDAR technology and explains how to collect and process LiDAR data from different platforms based on real-world experience. The book provides state-of the-art algorithms on how to extract forest parameters from LiDAR and explains how to use them in forest ecology. It gives an interdisciplinary view, from the perspective of remote sensing and forest ecology. Because LiDAR is still rapidly developing, researchers must use programming languages to understand and process LiDAR data instead of established software. In response, this book provides Python code examples and sample data.

Sections give a brief history and introduce the principles of LiDAR, as well as three commonly seen LiDAR platforms. The book lays out step-by-step coverage of LiDAR data processing and forest structure parameter extraction, complete with Python examples. Given the increasing usefulness of LiDAR in forest ecology, this volume represents an important resource for researchers, students and forest managers to better understand LiDAR technology and its use in forest ecology across the world. The title contains over 15 years of research, as well as contributions from scientists across the world.
LiDAR Principles, Processing and Applications in Forest Ecology introduces the principles of LiDAR technology and explains how to collect and process LiDAR data from different platforms based on real-world experience. The book provides state-of the-art algorithms on how to extract forest parameters from LiDAR and explains how to use them in forest ecology. It gives an interdisciplinary view, from the perspective of remote sensing and forest ecology. Because LiDAR is still rapidly developing, researchers must use programming languages to understand and process LiDAR data instead of established software. In response, this book provides Python code examples and sample data.

Sections give a brief history and introduce the principles of LiDAR, as well as three commonly seen LiDAR platforms. The book lays out step-by-step coverage of LiDAR data processing and forest structure parameter extraction, complete with Python examples. Given the increasing usefulness of LiDAR in forest ecology, this volume represents an important resource for researchers, students and forest managers to better understand LiDAR technology and its use in forest ecology across the world. The title contains over 15 years of research, as well as contributions from scientists across the world.
Über den Autor
Dr. Qinghua Guo is currently a professor in Peking University, and serves as the director of the Institute of Remote Sensing & Geographical Information System, Peking University. He received the B.S. and M.S. degrees in Peking University, and the Ph.D degrees in University of California Berkeley. His recent research interests lie in developing near-surface (e.g., backpack, UAV and mobile) Lidar hardware and data processing software systems and combining them with airborne and spaceborne remote sensing data to map vegetation attributes (e.g., tree height, LAI, AGB, vegetation type) from individual plant scale to national and global scales. So far, he has published over 160 peer-reviewed papers.
Inhaltsverzeichnis
1. The Origin and Development of LiDAR Active Remote Sensing Technology
2. Working principle of LiDAR 2.1 Ranging principle of LiDAR
3. Field work flow and system error source of LiDAR
4. LiDAR data format
5. LiDAR data filtering and digital elevation model generation
6. Data Analysis and Feature Extraction of Terrestrial LiDAR
7. Data Analysis and Feature Extraction of Airborne LiDAR
8. Data Analysis and Feature Extraction of Spaceborne LiDAR
9. Forest Structural Parameters Extraction
10. Ecosystem Function Parameters Inversion and Large-scale Simulation
11. Applications of LiDAR in dynamic monitoring of forest ecosystem
12. Applications of LiDAR technology in forest biodiversity, hydrology, and ecological models
13. 3D visualization and reconstruction of vegetation based on LiDAR technology
14. Emerging and ecological application of the near-surface LiDAR platform
15. Challenges and applications of LiDAR
Details
Erscheinungsjahr: 2023
Fachbereich: Landwirtschaft & Gartenbau
Genre: Umwelt
Produktart: Nachschlagewerke
Rubrik: Ökologie
Medium: Taschenbuch
ISBN-13: 9780128238943
ISBN-10: 0128238941
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Guo, Qinghua
Su, Yanjun
Hu, Tianyu
Hersteller: Elsevier Science
Maße: 229 x 152 x 34 mm
Von/Mit: Qinghua Guo (u. a.)
Erscheinungsdatum: 10.03.2023
Gewicht: 0,84 kg
Artikel-ID: 121438089
Über den Autor
Dr. Qinghua Guo is currently a professor in Peking University, and serves as the director of the Institute of Remote Sensing & Geographical Information System, Peking University. He received the B.S. and M.S. degrees in Peking University, and the Ph.D degrees in University of California Berkeley. His recent research interests lie in developing near-surface (e.g., backpack, UAV and mobile) Lidar hardware and data processing software systems and combining them with airborne and spaceborne remote sensing data to map vegetation attributes (e.g., tree height, LAI, AGB, vegetation type) from individual plant scale to national and global scales. So far, he has published over 160 peer-reviewed papers.
Inhaltsverzeichnis
1. The Origin and Development of LiDAR Active Remote Sensing Technology
2. Working principle of LiDAR 2.1 Ranging principle of LiDAR
3. Field work flow and system error source of LiDAR
4. LiDAR data format
5. LiDAR data filtering and digital elevation model generation
6. Data Analysis and Feature Extraction of Terrestrial LiDAR
7. Data Analysis and Feature Extraction of Airborne LiDAR
8. Data Analysis and Feature Extraction of Spaceborne LiDAR
9. Forest Structural Parameters Extraction
10. Ecosystem Function Parameters Inversion and Large-scale Simulation
11. Applications of LiDAR in dynamic monitoring of forest ecosystem
12. Applications of LiDAR technology in forest biodiversity, hydrology, and ecological models
13. 3D visualization and reconstruction of vegetation based on LiDAR technology
14. Emerging and ecological application of the near-surface LiDAR platform
15. Challenges and applications of LiDAR
Details
Erscheinungsjahr: 2023
Fachbereich: Landwirtschaft & Gartenbau
Genre: Umwelt
Produktart: Nachschlagewerke
Rubrik: Ökologie
Medium: Taschenbuch
ISBN-13: 9780128238943
ISBN-10: 0128238941
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Guo, Qinghua
Su, Yanjun
Hu, Tianyu
Hersteller: Elsevier Science
Maße: 229 x 152 x 34 mm
Von/Mit: Qinghua Guo (u. a.)
Erscheinungsdatum: 10.03.2023
Gewicht: 0,84 kg
Artikel-ID: 121438089
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