Journal
REMOTE SENSING LETTERS
Volume 13, Issue 3, Pages 311-321Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/2150704X.2022.2030068
Keywords
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Funding
- 2020 FORTH-Synergy Grant
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This study explores the feasibility of extracting high-resolution, shallow bathymetry from drone-based imagery using empirical methods. The results show that radiometric image corrections greatly enhance the correlation coefficient between bathymetry data and reflectance mosaics. It is also observed that the Red band and its associated logarithmic band ratios show good correlation with depth regardless of radiometric corrections. This study suggests that radiometric calibration is crucial in empirical bathymetry retrieval and that applying radiometric corrections on common RGB cameras is cost-effective.
Extracting high resolution, shallow bathymetry from drone-based imagery using empirical methods is a novel approach that gains increasing interest. However, due to the rapidly expanding character of this field, there are not sufficient guidelines for optimal pre-processing of drone-based imagery regarding bathymetry retrieval. This study explores the suitability of imagery resulted from commonly used drone cameras in terms of producing good correlation with ground-truth depth measurements obtained from an unmanned surface vehicle (USV). Thus, imagery with similar spectral responses, from two commercial sensors (DJI Phantom 4 Pro and MicaSense-RedEdge multispectral camera), is examined along with and without radiometric corrections applied, using proprietary software. The results show that radiometric image corrections using a reference reflectance panel, greatly enhance the correlation coefficient between bathymetry data and single-band or band-ratio reflectance mosaics at two study areas with mixed seafloor types. However, it was observed that the Red band and its associated logarithmic band ratios (Blue/Red, Green/Red) from both sensors show good correlation with depth as well, regardless of radiometric corrections. This result applies mainly to areas with favourable optical properties of water. This study suggests that radiometric calibration is crucial in empirical bathymetry retrieval from drone-based imagery. Furthermore, radiometric corrections applied on common Red, Green, Blue (RGB) cameras provide useful reflectance mosaics at lower costs compared to multispectral cameras.
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