Skip to main content
U.S. flag

An official website of the United States government

Surface elevation change evaluation in mangrove forests using a low‐cost, rapid‐scan terrestrial laser scanner

October 26, 2020

Mangrove forests have adapted to sea level rise (SLR) increases by maintaining their forest floor elevation via belowground root growth and surface sediment deposits. Researchers use surface elevation tables (SETs) to monitor surface elevation change (SEC) in mangrove forests, after which this information is used to assess SLR resiliency or to dictate active forest management for vulnerable systems. This method requires significant investments in terms of time and human resources and is limited in the number of points it can measure per plot. We use a low‐cost, portable terrestrial laser scanning (TLS) system to assess SEC for three mangrove forests on Pohnpei Island (Federated States of Micronesia). Cloth simulation filtering was used for ground detection, after which results were refined by filtering points using angular orientation. Digital elevation models then were generated via kriging interpolation for data collected in 2017 and 2019, after which the heights of corresponding points were compared across years. Extreme elevation changes, due to disturbances such as footprints or fallen logs, were removed using interquartile range analysis. The TLS‐obtained average SEC ranged between −6.92 and +6.01 mm, which exhibited an average consistency of 72% when compared to simultaneously collected SET data (root mean square error = 1.36 mm). We contend that this approach represents an improvement over the manual method, where very few points typically are used, that is, ≅ 36 points vs. ≅ 30,000 points in the case of TLS, and could contribute to improved monitoring and management of these rapidly changing forest environments.

Citation Information

Publication Year 2021
Title Surface elevation change evaluation in mangrove forests using a low‐cost, rapid‐scan terrestrial laser scanner
DOI 10.1002/lom3.10401
Authors Ali Rouzbeh Kargar, Richard A. MacKenzie, Alexander Fafard, Ken Krauss, Jan van Aardt
Publication Type Article
Publication Subtype Journal Article
Series Title Limnology and Oceanography Methods
Series Number
Index ID 70215758
Record Source USGS Publications Warehouse
USGS Organization Wetland and Aquatic Research Center