Quantifying Mangrove Forest Attributes Using Terrestrial Laser Scanning

被引:0
|
作者
Thomas Dunlop [1 ]
Alejandra Gijón Mancheño [2 ]
William Glamore [2 ]
Stefan Felder [1 ]
Bregje K. van Wesenbeeck [1 ]
机构
[1] UNSW Sydney,Water Research Laboratory, School of Civil and Environmental Engineering
[2] Delft University of Technology,Department of Hydraulic Engineering
[3] Unit for Marine and Coastal Systems,undefined
[4] Deltares,undefined
关键词
Allometry; Mangrove; Point cloud; Projected area; Terrestrial laser scanning (TLS);
D O I
10.1007/s12237-025-01533-0
中图分类号
学科分类号
摘要
Mangroves are increasingly recognised for their ecosystem services, including their capacity to store carbon and adapt to climate pressures by stabilising shorelines and acting as storm barriers. To quantify these services, relevant parameters such as mangrove biomass and drag coefficients have been calculated using allometric equations fitted to field measurements of physical mangrove attributes. However, previous research to quantify mangrove attributes has involved time-consuming hand measurements and long processing times associated with terrestrial laser scanning (TLS). To more efficiently capture and process mangrove attributes, such as the density, diameter, height, and projected area of stems and roots, a novel method for collecting mangrove field data using TLS was developed. Recorded TLS data were compared to field measurements conducted in 12 Avicennia marina forests across 10 estuaries and 4 unique estuary typologies. The results demonstrated the reliable estimation of mangrove attributes using TLS and revealed a link between these attributes and estuarine geomorphology. Mangrove stems were accurately identified in all estuary typologies, with attribute estimations more accurate for forests in Drowned River Valleys (DRVs). A sensitivity analysis revealed that 10–20 trees for DRVs and 35–45 trees for barrier estuaries require point cloud processing to characterise a forest area of 400–1300 m2 and to achieve convergent stem diameter and tree height results. The method presented herein offers an efficient way to quantify aboveground stem and root attributes and the surface area of mangrove trees. This data can be used to characterise mangrove forests worldwide and provide fundamental attributes for quantifying ecosystem services.
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