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Adaptive model for the water depth bias correction of bathymetric LiDAR point cloud data

  • Published:2023-04 Issue: Volume:118 Page:103253
  • ISSN:1569-8432
  • Container-title:International Journal of Applied Earth Observation and Geoinformation
  • language:en
  • Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Zhou Guoqing,Wu Gongbei,Zhou Xiang,Xu Chao,Zhao Dawei,Lin Jinchun,Liu Zhexian,Zhang Haotian,Wang Qingyang,Xu Jiasheng,Song Bo,Zhang Lieping

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference56 articles.

1. UCL: Unsupervised Curriculum Learning for water body classification from remote sensing imagery;Abid;Int. J. Appl. Earth Obs. Geoinf.,2021

2. Effects of distance measure choice on k-nearest neighbor classifier performance: a review;Abu Alfeilat;Big Data.,2019

3. DepthLearn: learning to correct the refraction on point clouds derived from aerial imagery for accurate dense shallow water bathymetry based on SVMs-fusion with LiDAR point clouds;Agrafiotis;Remote Sens.,2019

4. Geostatistical estimations of bathymetric LiDAR errors on rivers;Bailly;Earth Surf. Process. Landf.,2010

5. Modeling depth bias in an airborne laser hydrographic system;Billard;Appl. Opt.,1986
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