Surface Elevation Changes Estimation Underneath Mangrove Canopy Using SNERL Filtering Algorithm and DoD Technique on UAV-Derived DSM Data

Surface Elevation Changes Estimation Underneath Mangrove Canopy Using SNERL Filtering Algorithm and DoD Technique on UAV-Derived DSM Data

Estimating surface elevation changes in mangrove forests requires a technique to filter the mangrove canopy and quantify the changes underneath. Hence, this study estimates surface elevation changes underneath the mangrove canopy through vegetation filtering and Difference of DEM (DoD) techniques us...

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Bibliographic Details
Published in:ISPRS international journal of geo-information 2022-01, Vol.11 (1), p.32
Main Authors: Mohamad, Norhafizi, Ahmad, Anuar, Khanan, Mohd Faisal Abdul, Din, Ami Hassan Md
Format: Article
Language:eng
Subjects:
Accretion
Accuracy
Algorithms
Canopies
Canopy
Change detection
Deposition
Elevation
Estimation
filtering algorithm
Filtration
geomorphological change detection
Geomorphology
mangrove surface geomorphometry
Mangrove swamps
Mangroves
Morphology
Photogrammetry
Plant cover
Researchers
Sea level
Sea level changes
Sea level rise
Sensors
Software
Soil erosion
surface elevation changes mapping
Topography
UAV photogrammetry
Unmanned aerial vehicles
Vegetation
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Summary:Estimating surface elevation changes in mangrove forests requires a technique to filter the mangrove canopy and quantify the changes underneath. Hence, this study estimates surface elevation changes underneath the mangrove canopy through vegetation filtering and Difference of DEM (DoD) techniques using two epochs of unmanned aerial vehicle (UAV) data carried out during 2016 and 2017. A novel filtering algorithm named Surface estimation from Nearest Elevation and Repetitive Lowering (SNERL) is used to estimate the elevation height underneath the mangrove canopy. Consequently, DoD technique is used to quantify the elevation change rates at the ground surface, which comprise erosion, accretion, and sedimentation. The significant findings showed that region of interest (ROI) 5 experienced the highest volumetric accretion (surface raising) at 0.566 cm3. The most increased erosion (surface lowering) was identified at ROI 8 at −2.469 cm3. In contrast, for vertical change average rates, ROI 6 experienced the highest vertical accretion (surface raising) at 1.281 m. In comparison, the most increased vertical erosion (surface lowering) was spotted at ROI 3 at −0.568 m. The change detection map and the rates of surface elevation changes at Kilim River enabled authorities to understand the situation thoroughly and indicate the future situation, including its interaction with sea-level rise impacts.
ISSN:2220-9964
2220-9964