Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments
Terrestrial Light Detection And Ranging (LiDAR), also referred to as terrestrial laser scanning (TLS), has gained increasing popularity in terms of providing highly detailed micro-topography with millimetric measurement precision and accuracy. However, accurately depicting terrain under dense vegeta...
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| Format: | Article |
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MDPI AG
2021-10-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/10/10/665 |
| _version_ | 1797514416120397824 |
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| author | Xukai Zhang Xuelian Meng Chunyan Li Nan Shang Jiaze Wang Yaping Xu Tao Wu Cliff Mugnier |
| author_facet | Xukai Zhang Xuelian Meng Chunyan Li Nan Shang Jiaze Wang Yaping Xu Tao Wu Cliff Mugnier |
| author_sort | Xukai Zhang |
| collection | DOAJ |
| description | Terrestrial Light Detection And Ranging (LiDAR), also referred to as terrestrial laser scanning (TLS), has gained increasing popularity in terms of providing highly detailed micro-topography with millimetric measurement precision and accuracy. However, accurately depicting terrain under dense vegetation remains a challenge due to the blocking of signal and the lack of nearby ground. Without dependence on historical data, this research proposes a novel and rapid solution to map densely vegetated coastal environments by integrating terrestrial LiDAR with GPS surveys. To verify and improve the application of terrestrial LiDAR in coastal dense-vegetation areas, we set up eleven scans of terrestrial LiDAR in October 2015 along a sand berm with vegetation planted in Plaquemines Parish of Louisiana. At the same time, 2634 GPS points were collected for the accuracy assessment of terrain mapping and terrain correction. Object-oriented classification was applied to classify the whole berm into tall vegetation, low vegetation and bare ground, with an overall accuracy of 92.7% and a kappa value of 0.89. Based on the classification results, terrain correction was conducted for the tall-vegetation and low-vegetation areas, respectively. An adaptive correction factor was applied to the tall-vegetation area, and the 95th percentile error was calculated as the correction factor from the surface model instead of the terrain model for the low-vegetation area. The terrain correction method successfully reduced the mean error from 0.407 m to −0.068 m (RMSE errors from 0.425 m to 0.146 m) in low vegetation and from 0.993 m to −0.098 m (RMSE from 1.070 m to 0.144 m) in tall vegetation. |
| first_indexed | 2024-03-10T06:31:18Z |
| format | Article |
| id | doaj.art-f725ab04d2374ce8b308fc25e1672777 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T06:31:18Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-f725ab04d2374ce8b308fc25e16727772023-11-22T18:29:37ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-10-01101066510.3390/ijgi10100665Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal EnvironmentsXukai Zhang0Xuelian Meng1Chunyan Li2Nan Shang3Jiaze Wang4Yaping Xu5Tao Wu6Cliff Mugnier7Department of Geography & Anthropology, Louisiana State University, Baton Rouge, LA 70803, USADepartment of Geography & Anthropology, Louisiana State University, Baton Rouge, LA 70803, USACoastal Studies Institute, Louisiana State University, Baton Rouge, LA 70803, USADepartment of Geography & Anthropology, Louisiana State University, Baton Rouge, LA 70803, USAOak Ridge National Laboratory, Oak Ridge, TN 37830, USADepartment of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USADepartment of Geography, Zhejiang Normal University, Jinhua 321004, ChinaDepartment of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USATerrestrial Light Detection And Ranging (LiDAR), also referred to as terrestrial laser scanning (TLS), has gained increasing popularity in terms of providing highly detailed micro-topography with millimetric measurement precision and accuracy. However, accurately depicting terrain under dense vegetation remains a challenge due to the blocking of signal and the lack of nearby ground. Without dependence on historical data, this research proposes a novel and rapid solution to map densely vegetated coastal environments by integrating terrestrial LiDAR with GPS surveys. To verify and improve the application of terrestrial LiDAR in coastal dense-vegetation areas, we set up eleven scans of terrestrial LiDAR in October 2015 along a sand berm with vegetation planted in Plaquemines Parish of Louisiana. At the same time, 2634 GPS points were collected for the accuracy assessment of terrain mapping and terrain correction. Object-oriented classification was applied to classify the whole berm into tall vegetation, low vegetation and bare ground, with an overall accuracy of 92.7% and a kappa value of 0.89. Based on the classification results, terrain correction was conducted for the tall-vegetation and low-vegetation areas, respectively. An adaptive correction factor was applied to the tall-vegetation area, and the 95th percentile error was calculated as the correction factor from the surface model instead of the terrain model for the low-vegetation area. The terrain correction method successfully reduced the mean error from 0.407 m to −0.068 m (RMSE errors from 0.425 m to 0.146 m) in low vegetation and from 0.993 m to −0.098 m (RMSE from 1.070 m to 0.144 m) in tall vegetation.https://www.mdpi.com/2220-9964/10/10/665terrestrial LiDARmapping micro-topographydense vegetationcoastal environments |
| spellingShingle | Xukai Zhang Xuelian Meng Chunyan Li Nan Shang Jiaze Wang Yaping Xu Tao Wu Cliff Mugnier Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments ISPRS International Journal of Geo-Information terrestrial LiDAR mapping micro-topography dense vegetation coastal environments |
| title | Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments |
| title_full | Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments |
| title_fullStr | Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments |
| title_full_unstemmed | Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments |
| title_short | Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments |
| title_sort | micro topography mapping through terrestrial lidar in densely vegetated coastal environments |
| topic | terrestrial LiDAR mapping micro-topography dense vegetation coastal environments |
| url | https://www.mdpi.com/2220-9964/10/10/665 |
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