Waveform Information Accurate Extraction for Massive and Complex Waveform Data of Hyperspectral Lidar
Hyperspectral lidar (HSL) has high-precision geometric information and high-resolution spectral information, and its advantageous detection capability has been recognized by scientists at home and abroad. However, how to extract massive and complex HSL data effectively and accurately is an important...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10748379/ |
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| author | Shuo Shi Chengyu Gong Qian Xu Ao Wang Xingtao Tang Sifu Bi Wei Gong |
| author_facet | Shuo Shi Chengyu Gong Qian Xu Ao Wang Xingtao Tang Sifu Bi Wei Gong |
| author_sort | Shuo Shi |
| collection | DOAJ |
| description | Hyperspectral lidar (HSL) has high-precision geometric information and high-resolution spectral information, and its advantageous detection capability has been recognized by scientists at home and abroad. However, how to extract massive and complex HSL data effectively and accurately is an important issue in the current development of HSL. A methodological system that caters to HSL data features is required to achieve high-precision spatial–spectral integrated data interpretation. This requirement represents a significant scientific challenge, for which research on appropriate HSL waveform data processing methods remains scarce. This study aims to address the challenges posed by the massive data and complex waveform situations associated with HSL. Based on an experimental verification, the single-channel algorithm suggested in this article proves to be advantageous over Gaussian decomposition, specifically for asymmetric and overlapping echoes. This algorithm produces an average <italic>R</italic><sup>2</sup> increase of 0.023 and reduces the standard deviation by 63%. It also accurately extracts hidden overlapping echoes. Furthermore, this study proposes a multi-channel-assisted optimization algorithm that can precisely extract faint and overlapping echoes that a single-channel algorithm cannot extract. Its accuracy is remarkably high, with the ranging accuracy boosted by 98% compared with that of the single-channel algorithm. |
| format | Article |
| id | doaj-art-86ed70efded24cd6b3cc833b17d7a812 |
| institution | OA Journals |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-86ed70efded24cd6b3cc833b17d7a8122025-08-20T02:33:48ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-01181020103810.1109/JSTARS.2024.349503910748379Waveform Information Accurate Extraction for Massive and Complex Waveform Data of Hyperspectral LidarShuo Shi0https://orcid.org/0000-0003-0008-3443Chengyu Gong1https://orcid.org/0009-0002-2900-7081Qian Xu2Ao Wang3Xingtao Tang4Sifu Bi5Wei Gong6https://orcid.org/0000-0002-2276-8024State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaSchool of Geography and Information Engineering, China University of Geosciences, Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaHyperspectral lidar (HSL) has high-precision geometric information and high-resolution spectral information, and its advantageous detection capability has been recognized by scientists at home and abroad. However, how to extract massive and complex HSL data effectively and accurately is an important issue in the current development of HSL. A methodological system that caters to HSL data features is required to achieve high-precision spatial–spectral integrated data interpretation. This requirement represents a significant scientific challenge, for which research on appropriate HSL waveform data processing methods remains scarce. This study aims to address the challenges posed by the massive data and complex waveform situations associated with HSL. Based on an experimental verification, the single-channel algorithm suggested in this article proves to be advantageous over Gaussian decomposition, specifically for asymmetric and overlapping echoes. This algorithm produces an average <italic>R</italic><sup>2</sup> increase of 0.023 and reduces the standard deviation by 63%. It also accurately extracts hidden overlapping echoes. Furthermore, this study proposes a multi-channel-assisted optimization algorithm that can precisely extract faint and overlapping echoes that a single-channel algorithm cannot extract. Its accuracy is remarkably high, with the ranging accuracy boosted by 98% compared with that of the single-channel algorithm.https://ieeexplore.ieee.org/document/10748379/Complex waveformhyperspectral lidar (HSL)massive raw datamultichannel assistwaveform decomposition |
| spellingShingle | Shuo Shi Chengyu Gong Qian Xu Ao Wang Xingtao Tang Sifu Bi Wei Gong Waveform Information Accurate Extraction for Massive and Complex Waveform Data of Hyperspectral Lidar IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Complex waveform hyperspectral lidar (HSL) massive raw data multichannel assist waveform decomposition |
| title | Waveform Information Accurate Extraction for Massive and Complex Waveform Data of Hyperspectral Lidar |
| title_full | Waveform Information Accurate Extraction for Massive and Complex Waveform Data of Hyperspectral Lidar |
| title_fullStr | Waveform Information Accurate Extraction for Massive and Complex Waveform Data of Hyperspectral Lidar |
| title_full_unstemmed | Waveform Information Accurate Extraction for Massive and Complex Waveform Data of Hyperspectral Lidar |
| title_short | Waveform Information Accurate Extraction for Massive and Complex Waveform Data of Hyperspectral Lidar |
| title_sort | waveform information accurate extraction for massive and complex waveform data of hyperspectral lidar |
| topic | Complex waveform hyperspectral lidar (HSL) massive raw data multichannel assist waveform decomposition |
| url | https://ieeexplore.ieee.org/document/10748379/ |
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