Improved Forest Signal Detection for Space-Borne Photon-Counting LiDAR Using Automatic Machine Learning-Reference-Cited by-同舟云学术

Improved Forest Signal Detection for Space-Borne Photon-Counting LiDAR Using Automatic Machine Learning

Published:2024 Issue: Volume:17 Page:1-13
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Zhang Bo¹^ORCID,Zhang Li¹^ORCID,Pang Yong²^ORCID,North Peter³^ORCID,Yan Min¹^ORCID,Ren Hongge¹,Ruan Linlin¹^ORCID,Yang Zhenyu⁴,Chen Bowei¹^ORCID

Affiliation:

1. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

2. Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China

3. Global Environmental Modelling and Earth Observation (GEMEO), Department of Geography, Swansea University, Swansea, U.K.

4. School of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

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4. ATLAS/ICESat-2 L3A land and vegetation height, Version 5;neuenschwander,2021

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