scholarly journals Influence of a target’s inclination on LiDAR waveform and its application

2021 ◽  
Author(s):  
Tao Yang ◽  
Jiancheng Lai ◽  
Chunyong Wang ◽  
Wei Yan ◽  
Yunjing Ji ◽  
...  
Keyword(s):  
Lidar Waveform

scholarly journals Iterative decomposition method for small foot-print LiDAR waveform

2013 ◽  
Vol 32 (4) ◽  
pp. 319 ◽  
Author(s):  
Xu-Dong LAI ◽  
Nan-Nan QIN ◽  
Xiao-Shuang HAN ◽  
Jun-Hong WANG ◽  
Wen-Guang HOU
Keyword(s):  
Decomposition Method ◽  
Iterative Decomposition ◽  
Lidar Waveform

Analysis and exploitation of lidar waveform data

2019 ◽  
Author(s):  
Richard C. Olsen ◽  
Andrew S. Davis ◽  
Jeremy P. Metcalf
Keyword(s):  
Waveform Data ◽  
Lidar Waveform

Bathymetry Retrieval Method of LiDAR Waveform Based on Multi-Gaussian Functions

2019 ◽  
Vol 90 (sp1) ◽  
pp. 324 ◽  
Author(s):  
Yi Ma ◽  
Jie Zhang ◽  
Zhen Zhang ◽  
Jing-Yu Zhang
Keyword(s):  
Retrieval Method ◽  
Gaussian Functions ◽  
Lidar Waveform

scholarly journals Retrieval of Nearshore Bathymetry around Ganquan Island from LiDAR Waveform and QuickBird Image

2019 ◽  
Vol 9 (20) ◽  
pp. 4375
Author(s):  
Zhang ◽  
Zhang ◽  
Ma ◽  
Tian ◽  
Jiang
Keyword(s):  
Remote Sensing ◽  
Relative Error ◽  
Water Depth ◽  
Conflicts Of Interest ◽  
Gaussian Function ◽  
Measurement Data ◽  
Validation Data ◽  
Waveform Data ◽  
Depth Measurement ◽  
Lidar Waveform

Optical remote sensing is an effective means of water depth measurement, but the current approach of mainstream bathymetric retrieval requires a large amount of onsite measurement data. Such data are hard to obtain from places where underwater terrains are complicated and unsteady, and from sea areas affected by issues with rights and conflicts of interest. In recent years, the emergence of airborne light detection and ranging (LiDAR) provided a new technical means for field bathymetric survey. In this study, water depth inversion was carried out around an island far from the mainland by using remote sensing images and real LiDAR waveform data. Multi-Gaussian function fitting was proposed to extract water depth data from waveform data, and bathymetric values were used as control and validation data of the active and passive combination of water depth inversion. Results show that the relative error was 5.6% for the bathymetric retrieval from LiDAR waveform data, and the accuracy meets the requirements of ocean bathymetry. The average relative error of water depth inversion based on active and passive remote sensing was less than 9%. The method used in this study can also reduce the use of LiDAR data and the cost, thus providing a new idea for future coastal engineering application and construction.

Stepwise decomposition and relative radiometric normalization for small footprint LiDAR waveform

2010 ◽  
Vol 54 (4) ◽  
pp. 625-630 ◽  
Author(s):  
YuChu Qin ◽  
Bin Li ◽  
Zheng Niu ◽  
WenJiang Huang ◽  
ChangYao Wang
Keyword(s):  
Small Footprint ◽  
Stepwise Decomposition ◽  
Lidar Waveform
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