Horizontal Geolocation Error Evaluation and Correction on Full-Waveform LiDAR Footprints via Waveform Matching
The geolocation accuracy of spaceborne LiDAR (Light Detection And Ranging) data is important for quantitative forest inventory. Geolocation errors in Global Ecosystem Dynamics Investigation (GEDI) footprints are almost unavoidable because of the instability of orbital parameter estimation and GNSS (...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/3/776 |
| _version_ | 1797623313117216768 |
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| author | Yifang Xu Sheng Ding Peimin Chen Hailong Tang Hongkai Ren Huabing Huang |
| author_facet | Yifang Xu Sheng Ding Peimin Chen Hailong Tang Hongkai Ren Huabing Huang |
| author_sort | Yifang Xu |
| collection | DOAJ |
| description | The geolocation accuracy of spaceborne LiDAR (Light Detection And Ranging) data is important for quantitative forest inventory. Geolocation errors in Global Ecosystem Dynamics Investigation (GEDI) footprints are almost unavoidable because of the instability of orbital parameter estimation and GNSS (Global Navigation Satellite Systems) positioning accuracy. This study calculates the horizontal geolocation error of multiple temporal GEDI footprints using a waveform matching method, which compares original GEDI waveforms with the corresponding simulated waveforms from airborne LiDAR point clouds. The results show that the GEDI footprint geolocation error varies from 3.04 m to 65.03 m. In particular, the footprints from good orbit data perform better than those from weak orbit data, while the nighttime and daytime footprints perform similarly. After removing the system error, the average waveform similarity coefficient of multi-temporal footprints increases obviously in low-waveform-similarity footprints, especially in weak orbit footprints. When the waveform matching effect is measured using the threshold of the waveform similarity coefficient, the waveform matching method can significantly improve up to 32% of the temporal GEDI footprint datasets from a poor matching effect to a good matching effect. In the improvement of the ratio of individual footprint waveform similarity, the mean value of the training set and test set is about two thirds, but the variance in the test set is large. Our study first quantifies the geolocation error of the newest version of GEDI footprints (Version 2). Future research should focus on the improvement of the detail of the waveform matching method and the combination of the terrain matching method with GEDI waveform LiDAR. |
| first_indexed | 2024-03-11T09:26:54Z |
| format | Article |
| id | doaj.art-366e4bb8c68540cb80a93f80f94c436f |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T09:26:54Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-366e4bb8c68540cb80a93f80f94c436f2023-11-16T17:54:05ZengMDPI AGRemote Sensing2072-42922023-01-0115377610.3390/rs15030776Horizontal Geolocation Error Evaluation and Correction on Full-Waveform LiDAR Footprints via Waveform MatchingYifang Xu0Sheng Ding1Peimin Chen2Hailong Tang3Hongkai Ren4Huabing Huang5School of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, ChinaForestry Surveying and Designing Institute of Guangdong Province, Guangzhou 510520, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, ChinaThe geolocation accuracy of spaceborne LiDAR (Light Detection And Ranging) data is important for quantitative forest inventory. Geolocation errors in Global Ecosystem Dynamics Investigation (GEDI) footprints are almost unavoidable because of the instability of orbital parameter estimation and GNSS (Global Navigation Satellite Systems) positioning accuracy. This study calculates the horizontal geolocation error of multiple temporal GEDI footprints using a waveform matching method, which compares original GEDI waveforms with the corresponding simulated waveforms from airborne LiDAR point clouds. The results show that the GEDI footprint geolocation error varies from 3.04 m to 65.03 m. In particular, the footprints from good orbit data perform better than those from weak orbit data, while the nighttime and daytime footprints perform similarly. After removing the system error, the average waveform similarity coefficient of multi-temporal footprints increases obviously in low-waveform-similarity footprints, especially in weak orbit footprints. When the waveform matching effect is measured using the threshold of the waveform similarity coefficient, the waveform matching method can significantly improve up to 32% of the temporal GEDI footprint datasets from a poor matching effect to a good matching effect. In the improvement of the ratio of individual footprint waveform similarity, the mean value of the training set and test set is about two thirds, but the variance in the test set is large. Our study first quantifies the geolocation error of the newest version of GEDI footprints (Version 2). Future research should focus on the improvement of the detail of the waveform matching method and the combination of the terrain matching method with GEDI waveform LiDAR.https://www.mdpi.com/2072-4292/15/3/776GEDIspaceborne full-waveform LiDARgeolocation errorairborne LiDARwaveform matching |
| spellingShingle | Yifang Xu Sheng Ding Peimin Chen Hailong Tang Hongkai Ren Huabing Huang Horizontal Geolocation Error Evaluation and Correction on Full-Waveform LiDAR Footprints via Waveform Matching Remote Sensing GEDI spaceborne full-waveform LiDAR geolocation error airborne LiDAR waveform matching |
| title | Horizontal Geolocation Error Evaluation and Correction on Full-Waveform LiDAR Footprints via Waveform Matching |
| title_full | Horizontal Geolocation Error Evaluation and Correction on Full-Waveform LiDAR Footprints via Waveform Matching |
| title_fullStr | Horizontal Geolocation Error Evaluation and Correction on Full-Waveform LiDAR Footprints via Waveform Matching |
| title_full_unstemmed | Horizontal Geolocation Error Evaluation and Correction on Full-Waveform LiDAR Footprints via Waveform Matching |
| title_short | Horizontal Geolocation Error Evaluation and Correction on Full-Waveform LiDAR Footprints via Waveform Matching |
| title_sort | horizontal geolocation error evaluation and correction on full waveform lidar footprints via waveform matching |
| topic | GEDI spaceborne full-waveform LiDAR geolocation error airborne LiDAR waveform matching |
| url | https://www.mdpi.com/2072-4292/15/3/776 |
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