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A Photon Cloud Filtering Method in Forested Areas Considering the Density Difference Between Canopy Photons and Ground Photons

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成果类型:
期刊论文
作者:
Li, Yi;Fu, Haiqiang;Zhu, Jianjun;Wang, Li;Zhao, Rong;...
通讯作者:
Fu, HQ
作者机构:
[Fu, Haiqiang; Wang, Li; Zhu, Jianjun; Li, Yi; Wang, Changcheng] Cent South Univ, Sch Geosci & Info Phys, Changsha 410083, Peoples R China.
[Zhao, Rong] Cent South Univ Forestry & Technol, Sch Civil Engn, Changsha 410004, Peoples R China.
通讯机构:
[Fu, HQ ] C
Cent South Univ, Sch Geosci & Info Phys, Changsha 410083, Peoples R China.
语种:
英文
关键词:
Photonics;Filtering;Histograms;Forestry;Background noise;Laser radar;Standards;forest canopy height;forested areas;modified elevation histogram statistics vector;moving window detection approach;photon cloud data
期刊:
IEEE Transactions on Geoscience and Remote Sensing
ISSN:
0196-2892
年:
2023
卷:
61
页码:
1-14
基金类别:
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 41820104005, 41904004 and 42030112)
机构署名:
本校为其他机构
院系归属:
土木工程学院
摘要:
Photon cloud data filtering is crucial when obtaining forest vertical structure parameters from photon-counting LiDAR data. The proposed method, for the first time, takes into account the influence of the density difference between canopy photons and ground photons. A moving overlapping window approach is introduced to reduce the impact of an uneven background noise environment first. In each window, a modified elevation histogram statistics vector in the elevation direction is proposed to increase the density difference between signal and noise photons while also reducing the density differen...

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