book

Introduction to LiDAR Remote Sensing

Name: Introduction to LiDAR Remote Sensing
ISBN: 9781040034569

by Cheng Wang, Xuebo Yang, Xiaohuan Xi, Sheng Nie, Pinliang Dong

June 2024

Beginner

259 pages

8h 32m

English

CRC Press

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Cover Page
Half-Title Page
Title Page
Copyright Page
Contents
Foreword
Preface
Authors
Chapter 1 Introduction
1.1 Introduction to LiDAR1.1.1 LiDAR1.1.2 Characteristics of LiDAR1.1.3 Classification of LiDAR1.1.4 Development History of LiDAR1.2 LiDAR System1.2.1 LiDAR System Composition1.2.2 Major Commercial LiDAR Systems1.2.3 Data Format and Processing Software1.3 LiDAR Remote Sensing Applications1.3.1 Topographic Mapping1.3.2 Forest Resource Investigation1.3.3 Digital Cities1.3.4 Digital Power Grid1.3.5 Crop Monitoring1.3.6 Cultural Heritage Digitization and Preservation1.3.7 Unmanned Driving1.3.8 Transportation Route Planning1.3.9 Mine Monitoring1.3.10 Other Applications1.4 SummaryExercisesReferences
Chapter 2 LiDAR Remote Sensing Principles
2.1 LiDAR Ranging Principle2.1.1 Ranging Principle of Pulsed LiDAR2.1.2 Ranging Principle of Phased LiDAR2.1.3 Ranging Precision of LiDAR2.2 LiDAR Radiation Principle2.2.1 LiDAR Equation2.2.2 LiDAR Waveform Model2.2.3 LiDAR Radiative Transfer Model2.3 Principles of LiDAR on Different Platforms2.3.1 Spaceborne LiDAR2.3.2 Airborne LiDAR2.3.3 Terrestrial LiDAR2.4 Principles of LiDAR with Different Methods of Detection and Digitization2.4.1 Full-Waveform LiDAR2.4.2 Discrete Return LiDAR2.4.3 Photon Counting LiDAR2.5 Influence Mechanism of the Sky on the LiDAR Signal2.5.1 Effect of Atmosphere2.5.2 Effect of Sunlight2.6 SummaryExercisesReferences

Chapter 3 LiDAR Data Acquisition
3.1 Airborne LiDAR Data Acquisition3.1.1 Plan Preparation Stage3.1.2 Flight Implementation Stage3.1.3 Data Preprocessing Stage3.2 Terrestrial LiDAR Data Acquisition3.2.1 Plan Preparation Stage3.2.2 Scan Implementation Stage3.2.3 Data Collection Stage3.3 Spaceborne LiDAR Data Acquisition3.3.1 ICESat/GLAS Mission3.3.2 ICESat-2/ATLAS Mission3.3.3 GEDI Mission3.3.4 China's Laser Altimetry Satellite Program3.4 SummaryExercisesReferences
Chapter 4 LiDAR Data Processing
4.1 LiDAR Point Cloud Processing4.1.1 Point Cloud Denoising4.1.2 Point Cloud Filtering4.1.3 Point Cloud Classification4.2 LiDAR Waveform Processing4.2.1 Waveform Denoising4.2.2 Waveform Decomposition4.2.3 Waveform Deconvolution4.2.4 Waveform Feature Parameter Extraction4.3 LiDAR Photon-Counting Processing4.3.1 Photon-Counting Denoising4.3.2 Photon-Counting Classification4.4 SummaryExercisesReferences
Chapter 5 LiDAR Remote Sensing Applications
5.1 Topographic Mapping5.1.1 LiDAR Point Cloud Processing5.1.2 DEM and DSM Constructions5.1.3 Contour Line Generation5.2 Forest Investigation5.2.1 Individual Tree Parameter Retrievals5.2.2 Canopy Parameter Retrievals5.2.3 Forest Parameter Mapping at the Regional Scale5.2.4 Tree Species Classification5.3 Power Line Inspection5.3.1 Transmission Corridor Point Cloud Classification5.3.2 3D Modeling of the Transmission Corridor5.3.3 Transmission Corridor Safety Analysis5.4 Building 3D Modeling5.4.1 Building Point Cloud Extraction5.4.2 Building Roof Segmentation5.4.3 Building Contour Extraction5.4.4 Building Model Generation5.5 Automatic Driving5.5.1 Environmental Perception5.5.2 Autonomous Positioning5.6 Crop Monitoring5.6.1 Identification of Corn Planted Area5.6.2 Identification of Stem and Leaf Points5.6.3 Estimation of Leaf Angle Distribution5.6.4 Estimation of Leaf Area Volume Density5.6.5 Estimation of Factional Absorbed Photosynthetically Active Radiation5.7 Cultural Heritage Conservation5.7.1 Cultural Heritage Conservation Based on Terrestrial Laser Scanning5.7.2 Ancient Heritage Site Discovery Based on Airborne Laser Scanning5.7.3 Archaeology by Combining Airborne and Terrestrial Laser Scanning5.8 Indoor 3D Modeling and Navigation5.8.1 Point Cloud–Based Indoor Modeling5.8.2 Point Cloud–Based Indoor Navigation5.9 Underwater Mapping5.9.1 Water Level Extraction5.9.2 Water Depth Survey5.10 SummaryExercisesReferences
Chapter 6 LiDAR Remote Sensing Prospects
6.1 Continuously Optimized Sensor Performance6.2 A Flood of New LiDAR Sensors6.2.1 Hyperspectral/Multi-Spectral LiDAR6.2.2 Solid-State LiDAR6.2.3 Quantum LiDAR6.3 Arrival of the LiDAR Big Data Era6.3.1 Multi-Platform Coexistence, Multi-Source Data Fusion6.3.2 LiDAR Big Data Era6.4 Comprehensive Applications of LiDAR6.4.1 LiDAR Satellite Missions Promote the Development of Global Surface Products toward the Direction of High Precision and High Resolution6.4.2 LiDAR Improves Natural Resource Monitoring from Two-Dimensional to Three-Dimensional Space6.4.3 LiDAR Promotes the Further Development of Smart City6.4.4 LiDAR Assists with Automatic Driving6.5 SummaryExercisesReferences
Appendix: LiDAR Terminology
Index

Content preview from Introduction to LiDAR Remote Sensing

4LiDAR Data Processing

DOI: 10.1201/9781032671512-4

4.1 LiDAR POINT CLOUD PROCESSING

The purpose of point cloud processing is to extract key features from the massive and disordered three-dimensional (3D) point clouds by specific algorithms and provide high-precision data and accurate information for subsequent digital surface model generation, 3D modeling of features, and other related applications (Yang et al., 2017). Point cloud denoising, point cloud filtering, and point cloud classification are the key steps in the point cloud processing, which are described in this section.

4.1.1 POINT CLOUD DENOISING

In the process of point cloud acquisition, equipment errors, personnel operations, object reflections, and environmental interference ...

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Introduction to LiDAR Remote Sensing

by Cheng Wang, Xuebo Yang, Xiaohuan Xi, Sheng Nie, Pinliang Dong

4LiDAR Data Processing