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Article

Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments

1
Department of Geography & Anthropology, Louisiana State University, Baton Rouge, LA 70803, USA
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Coastal Studies Institute, Louisiana State University, Baton Rouge, LA 70803, USA
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Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
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Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
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Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA
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Department of Geography, Zhejiang Normal University, Jinhua 321004, China
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Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Emmanouil Psomiadis, Konstantinos X. Soulis and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2021, 10(10), 665; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10100665
Received: 9 August 2021 / Revised: 24 September 2021 / Accepted: 27 September 2021 / Published: 1 October 2021
(This article belongs to the Special Issue GIS and Remote Sensing Applications in Geomorphology)
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. View Full-Text
Keywords: terrestrial LiDAR; mapping micro-topography; dense vegetation; coastal environments terrestrial LiDAR; mapping micro-topography; dense vegetation; coastal environments
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MDPI and ACS Style

Zhang, X.; Meng, X.; Li, C.; Shang, N.; Wang, J.; Xu, Y.; Wu, T.; Mugnier, C. Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments. ISPRS Int. J. Geo-Inf. 2021, 10, 665. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10100665

AMA Style

Zhang X, Meng X, Li C, Shang N, Wang J, Xu Y, Wu T, Mugnier C. Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments. ISPRS International Journal of Geo-Information. 2021; 10(10):665. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10100665

Chicago/Turabian Style

Zhang, Xukai, Xuelian Meng, Chunyan Li, Nan Shang, Jiaze Wang, Yaping Xu, Tao Wu, and Cliff Mugnier. 2021. "Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments" ISPRS International Journal of Geo-Information 10, no. 10: 665. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10100665

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