Estimation of surface elevation changes at bare earth riverbank using differential DEM technique of UAV imagery data

Norhafizi Mohamad, Anuar Ahmad, Ami Hassan Md Din

Abstract


Estimating surface elevation changes at bare earth riverbank is challenging because of the non-visibility effect of this phenomenon, especially for short observation periods. Hence, the spatio-temporal detection at a short-term period determines the geomorphological changes by comparing the same area at different observation epochs. This study attempts to assess surface elevation changes components which include erosion and accretion, using the geomorphological changes detection (GCD) technique based on multi-temporal unmanned aerial vehicle (UAV) imagery. Using a multi-rotor UAV and high accuracy Global Navigation Satellite System instrument, the data acquisition process was conducted in Kilim River in the December 2016 and December 2017 to complete a one-year interval. To generate a very high accuracy of orthomosaics and digital elevation model (DEM), the structured from motion and multi-view stereo techniques were used. Then, GCD method, which involves a difference of DEM (DoD) was performed to evaluate the surface elevation changes that comprising erosion and accretion using GCD analysis tool. This study discovered that surface raising was more dominant than surface lowering, at 31.70% (raw) and 31.67% (thresholded), the per cent elevation raising at 68.30% (raw) and 68.33% (thresholded), the per cent imbalance (departure from equilibrium) at 18.30% (raw) and 18.33% (thresholded) and the net to total volume ratio at 36.60% (raw) and 36.67% (thresholded). The results showed how the UAV platform provides a way to evaluate surface elevation changes in bare earth areas with decent accuracy and enables further study on river geomorphological-related issues in the future.

Keywords: DEM, GCD Analysis, GNSS, SfM-MVS, Surface Elevation Changes, UAV Photogrammetry


Keywords


Surface Elevation Changes; GCD Analysis; UAV Photogrammetry; GNSS; DEM; SfM-MVS

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References


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DOI: http://dx.doi.org/10.17576/geo-2021-1704-23

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