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Drones 2019, 3(2), 32; https://doi.org/10.3390/drones3020032

Estimating Mangrove Forest Volume Using Terrestrial Laser Scanning and UAV-Derived Structure-from-Motion

School of Science and Engineering, University of the Sunshine Coast, 90 Sippy Downs Dr, Sippy Downs, Queensland 4556, Australia
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Author to whom correspondence should be addressed.
Received: 6 March 2019 / Revised: 20 March 2019 / Accepted: 28 March 2019 / Published: 1 April 2019
(This article belongs to the Special Issue Drones for Coastal Environments)
PDF [1509 KB, uploaded 1 April 2019]

Abstract

Mangroves provide a variety of ecosystem services, which can be related to their structural
complexity and ability to store carbon in the above ground biomass (AGB). Quantifying AGB in
mangroves has traditionally been conducted using destructive, time-consuming, and costly
methods, however, Structure-from-Motion Multi-View Stereo (SfM-MVS) combined with
unmanned aerial vehicle (UAV) imagery may provide an alternative. Here, we compared the ability
of SfM-MVS with terrestrial laser scanning (TLS) to capture forest structure and volume in three
mangrove sites of differing stand age and species composition. We describe forest structure in terms
of point density, while forest volume is estimated as a proxy for AGB using the surface differencing
method. In general, SfM-MVS poorly captured mangrove forest structure, but was efficient in
capturing the canopy height for volume estimations. The differences in volume estimations between
TLS and SfM-MVS were higher in the juvenile age site (42.95%) than the mixed (28.23%) or mature
(12.72%) age sites, with a higher stem density affecting point capture in both methods. These results
can be used to inform non-destructive, cost-effective, and timely assessments of forest structure or
AGB in mangroves in the future.
Keywords: mangroves; forest structure; terrestrial laser scanning; structure-from-motion mangroves; forest structure; terrestrial laser scanning; structure-from-motion
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Warfield, A.D.; Leon, J.X. Estimating Mangrove Forest Volume Using Terrestrial Laser Scanning and UAV-Derived Structure-from-Motion. Drones 2019, 3, 32.

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