Suitable LiDAR Platform for Measuring the 3D Structure of Mangrove Forests
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Published:2023-02-14
Issue:4
Volume:15
Page:1033
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
Niwa Hideyuki1ORCID, Ise Hajime2, Kamada Mahito3
Affiliation:
1. Faculty of Bioenvironmental Science, Kyoto University of Advanced Science, 1-1 Sogabe-cho Nanjyo Otani, Kameoka 621-8555, Japan 2. Graduate School of Advanced Technology and Science, Tokushima University, Tokushima 770-8506, Japan 3. Graduate School of Technology, Industrial and Social Sciences, Tokushima University, Tokushima 770-8506, Japan
Abstract
Investigating the three-dimensional structure of mangrove forests is critical for their conservation and restoration. However, mangrove forests are difficult to survey in the field, and their 3D structure is poorly understood. Light detection and ranging (LiDAR) is considered an accurate and dependable method of measuring the 3D structure of mangrove forests. This study aimed to find a suitable LiDAR platform for obtaining attributes such as breast height diameter and canopy area, as well as for measuring a digital terrain model (DTM), the base data for hydrological analysis. A mangrove forest near the mouth of the Oura River in Aza-Oura, Nago City, Okinawa Prefecture, Japan, was studied. We used data from terrestrial LiDAR scanning “TLS” and unmanned aerial vehicle (UAV) LiDAR scanning “ULS” as well as data merged from TLS and ULS “Merge”. By interpolating point clouds of the ground surface, DTMs of 5 cm × 5 cm were created. DTMs obtained from ULS could not reproduce the heaps of Thalassina anomala or forest floor microtopography compared with those obtained from TLS. Considering that ULS had a few point clouds in the forest, automatic trunk identification could not be used to segment trees. TLS could segment trees by automatically identifying trunks, but the number of trees identified roughly doubled that of the visual identification results. The number of tree crowns identified using TLS and ULS was approximately one quarter of those identified visually, and many of them were larger in area than the visually traced crowns. The accuracy of tree segmentation using the canopy height model (CHM) was low. The number of canopy trees identified using Merge produced the best results, accounting for 61% of the visual identification results. Results of tree segmentation by CHM suggest that combining TLS and ULS measurements may improve tree canopy identification. Although ULS is a promising new technology, its applications are clearly limited, at least in mangrove forests such as the Oura River, where Bruguiera gymnorhiza is dominant. Depending on the application, using different LiDAR platforms, such as airborne LiDAR scanning, UAV LiDAR scanning, and TLS, is important. Merging 3D point clouds acquired by different platforms, as proposed in this study, is an important option in this case.
Subject
General Earth and Planetary Sciences
Reference26 articles.
1. Ecosystem service values for mangroves in Southeast Asia: A meta-analysis and value transfer application;Brander;Ecosyst. Serv.,2012 2. Pham, T.D., Yokoya, N., Bui, D.T., Yoshino, K., and Friess, D.A. (2019). Remote sensing approaches for monitoring mangrove species, structure, and biomass: Opportunities and challenges. Remote Sens., 11. 3. Spalding, M., Kainuma, M., and Collins, L. (2010). World Atlas of Mangroves (Version 3.1). A Collaborative Project of ITTO, ISME, FAO, UNEP-WCMC, UNESCO-MAB, UNU-INWEH and TNC. London (UK): Earthscan, London, Routledge. 4. Bunting, P., Rosenqvist, A., Hilarides, L., Lucas, R.M., Thomas, T., Tadono, T., Worthington, T.A., Spalding, M., Murray, N.J., and Rebelo, L.-M. (2022). Global Mangrove Extent Change 1996–2020: Global Mangrove Watch Version 3.0. Remote Sensing., 14. 5. A review of remote sensing for mangrove forests: 1956–2018;Wang;Remote Sens. Environ.,2019
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