A Satellite Full-Waveform Laser Decomposition Method for Forested Areas Based on Hidden Peak Detection and Adaptive Genetic Optimization
Laser waveform data that contain rich three-dimensional structural object information hold significant value in forest resource monitoring. However, traditional waveform decomposition algorithms are often constrained by complex waveform structures and depend on the initial parameter selections, whic...
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MDPI AG
2025-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/4/701 |
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| author | Fangxv Zhang Xiao Wang Leiguang Wang Fan Mo Liping Zhao Xiaomeng Yang Xin Lv Junfeng Xie |
| author_facet | Fangxv Zhang Xiao Wang Leiguang Wang Fan Mo Liping Zhao Xiaomeng Yang Xin Lv Junfeng Xie |
| author_sort | Fangxv Zhang |
| collection | DOAJ |
| description | Laser waveform data that contain rich three-dimensional structural object information hold significant value in forest resource monitoring. However, traditional waveform decomposition algorithms are often constrained by complex waveform structures and depend on the initial parameter selections, which affect the accuracy and robustness of the results. To address the issues of the strong dependence on initial parameters, susceptibility to local optima, and difficulty in detecting hidden peaks during waveform overlap in the traditional satellite laser waveform decomposition algorithms, this study proposes a waveform decomposition method that combines hidden peak detection and an adaptive genetic algorithm (HAGA). This method uses hidden peak detection algorithms to improve the accurate extraction of the Gaussian components from the original waveform and provides the initial parameters. The high-precision extraction of waveform parameters is achieved through the adaptive genetic algorithm (AGA) combined with Levenberg–Marquardt (LM) optimization. In the experimental validation, the proposed method outperformed the traditional methods in both waveform decomposition fitting accuracy and tree height extraction. The average waveform decomposition accuracy <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>R</mi><mrow><mi>m</mi><mi>e</mi><mi>a</mi><mi>n</mi></mrow><mn>2</mn></msubsup></mrow></semantics></math></inline-formula> for more than 2000 laser spots reaches 0.955, whereas the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>M</mi><mi>S</mi><mi>E</mi></mrow></semantics></math></inline-formula> of the tree height extractions is better than 2 m, demonstrating strong robustness and applicability. |
| format | Article |
| id | doaj-art-8d8d4f3e22f14c14a6dd15f50a90cbc3 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-8d8d4f3e22f14c14a6dd15f50a90cbc32025-08-20T02:44:56ZengMDPI AGRemote Sensing2072-42922025-02-0117470110.3390/rs17040701A Satellite Full-Waveform Laser Decomposition Method for Forested Areas Based on Hidden Peak Detection and Adaptive Genetic OptimizationFangxv Zhang0Xiao Wang1Leiguang Wang2Fan Mo3Liping Zhao4Xiaomeng Yang5Xin Lv6Junfeng Xie7School of Earth Sciences and Engineering, Hohai University, Nanjing 210024, ChinaAerospace Information Research Institute, Chinese Academy of Science, Beijing 100101, ChinaCollege of Biodiversity Conversation, Southwest Forestry University, Kunming 650224, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, ChinaLand Satellite Remote Sensing Application Center, Ministry of Natural Resources of China, Beijing 100048, ChinaLaser waveform data that contain rich three-dimensional structural object information hold significant value in forest resource monitoring. However, traditional waveform decomposition algorithms are often constrained by complex waveform structures and depend on the initial parameter selections, which affect the accuracy and robustness of the results. To address the issues of the strong dependence on initial parameters, susceptibility to local optima, and difficulty in detecting hidden peaks during waveform overlap in the traditional satellite laser waveform decomposition algorithms, this study proposes a waveform decomposition method that combines hidden peak detection and an adaptive genetic algorithm (HAGA). This method uses hidden peak detection algorithms to improve the accurate extraction of the Gaussian components from the original waveform and provides the initial parameters. The high-precision extraction of waveform parameters is achieved through the adaptive genetic algorithm (AGA) combined with Levenberg–Marquardt (LM) optimization. In the experimental validation, the proposed method outperformed the traditional methods in both waveform decomposition fitting accuracy and tree height extraction. The average waveform decomposition accuracy <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>R</mi><mrow><mi>m</mi><mi>e</mi><mi>a</mi><mi>n</mi></mrow><mn>2</mn></msubsup></mrow></semantics></math></inline-formula> for more than 2000 laser spots reaches 0.955, whereas the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>M</mi><mi>S</mi><mi>E</mi></mrow></semantics></math></inline-formula> of the tree height extractions is better than 2 m, demonstrating strong robustness and applicability.https://www.mdpi.com/2072-4292/17/4/701full-waveform LiDARwaveform decompositionLevenberg-Marquardt optimizationtree height inversion |
| spellingShingle | Fangxv Zhang Xiao Wang Leiguang Wang Fan Mo Liping Zhao Xiaomeng Yang Xin Lv Junfeng Xie A Satellite Full-Waveform Laser Decomposition Method for Forested Areas Based on Hidden Peak Detection and Adaptive Genetic Optimization Remote Sensing full-waveform LiDAR waveform decomposition Levenberg-Marquardt optimization tree height inversion |
| title | A Satellite Full-Waveform Laser Decomposition Method for Forested Areas Based on Hidden Peak Detection and Adaptive Genetic Optimization |
| title_full | A Satellite Full-Waveform Laser Decomposition Method for Forested Areas Based on Hidden Peak Detection and Adaptive Genetic Optimization |
| title_fullStr | A Satellite Full-Waveform Laser Decomposition Method for Forested Areas Based on Hidden Peak Detection and Adaptive Genetic Optimization |
| title_full_unstemmed | A Satellite Full-Waveform Laser Decomposition Method for Forested Areas Based on Hidden Peak Detection and Adaptive Genetic Optimization |
| title_short | A Satellite Full-Waveform Laser Decomposition Method for Forested Areas Based on Hidden Peak Detection and Adaptive Genetic Optimization |
| title_sort | satellite full waveform laser decomposition method for forested areas based on hidden peak detection and adaptive genetic optimization |
| topic | full-waveform LiDAR waveform decomposition Levenberg-Marquardt optimization tree height inversion |
| url | https://www.mdpi.com/2072-4292/17/4/701 |
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