Comparative analyses for determining shallow water bathymetry potential of multispectral UAVs: case study in Tavşan Island, Sea of Marmara

Recently, the use of unmanned aerial vehicles (UAVs) in bathymetric applications has become very popular due to the rapid and periodic acquisition of high spatial resolution data that provide detailed modeling of shallow water body depths and obtaining geospatial information. In UAV-based bathymetry, the sensor characteristics, imaging geometries, and the quality of radiometric and geometric calibrations of the imagery are the basic factors to achieve most reliable results. Digital bathymetric models (DBMs) that enable three-dimensional bottom topography definition of water bodies can be generated using many different techniques. In this paper, the effect of different UAV imaging bands and DBM generation techniques on the quality of bathymetric 3D modeling was deeply analyzed by visual and statistical model-based comparison approaches utilizing reference data acquired by a single-beam echosounder. In total, four different DBMs were generated and evaluated, two from dense point clouds derived from red–green–blue (RGB) single-band and multispectral (MS) five-band aerial photos, and the other two from Stumpf and Lyzenga empirical satellite-based bathymetry (SDB) adapted to UAV data. The applications were performed in the Tavşan Island located in Istanbul, Turkey. The results of statistical model-based analyses demonstrated that the accuracies of the DBMs are arranged as RGB, MS, Lyzenga, and Stumpf from higher to lower and the standard deviation of height differences are between ±0.26 m and ±0.54 m. Visual results indicate that five-band MS DBM performs best in identifying the deepest areas.

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Publication Details

Journal
Frontiers in Marine Science
Published
2024-08-09
DOI
https://doi.org/10.3389/fmars.2024.1388704
Citations
5
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
1.03
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article

Comparative analyses for determining shallow water bathymetry potential of multispectral UAVs: case study in Tavşan Island, Sea of Marmara

Mertcan Nazar, İrşad Bayırhan, Umut Güneş Sefercik, Gürcan Büyüksali̇h et al.
5 citations
Frontiers in Marine Science
Remote Sensing and LiDAR Applications
1.03
article

Comparative analyses for determining shallow water bathymetry potential of multispectral UAVs: case study in Tavşan Island, Sea of Marmara

Mertcan Nazar, İrşad Bayırhan, Umut Güneş Sefercik, Gürcan Büyüksali̇h, Cem Gazioğlu, Ilyas Aydin
article en
5 citations

Abstract

Recently, the use of unmanned aerial vehicles (UAVs) in bathymetric applications has become very popular due to the rapid and periodic acquisition of high spatial resolution data that provide detailed modeling of shallow water body depths and obtaining geospatial information. In UAV-based bathymetry, the sensor characteristics, imaging geometries, and the quality of radiometric and geometric calibrations of the imagery are the basic factors to achieve most reliable results. Digital bathymetric models (DBMs) that enable three-dimensional bottom topography definition of water bodies can be generated using many different techniques. In this paper, the effect of different UAV imaging bands and DBM generation techniques on the quality of bathymetric 3D modeling was deeply analyzed by visual and statistical model-based comparison approaches utilizing reference data acquired by a single-beam echosounder. In total, four different DBMs were generated and evaluated, two from dense point clouds derived from red–green–blue (RGB) single-band and multispectral (MS) five-band aerial photos, and the other two from Stumpf and Lyzenga empirical satellite-based bathymetry (SDB) adapted to UAV data. The applications were performed in the Tavşan Island located in Istanbul, Turkey. The results of statistical model-based analyses demonstrated that the accuracies of the DBMs are arranged as RGB, MS, Lyzenga, and Stumpf from higher to lower and the standard deviation of height differences are between ±0.26 m and ±0.54 m. Visual results indicate that five-band MS DBM performs best in identifying the deepest areas.

Frontiers in Marine ScienceVol. 11
Gebze Technical University (TR), Istituto di Scienze Marine del Consiglio Nazionale delle Ricerche (IT), Institut de Ciències del Mar (ES), Istanbul University (TR)
Life below water
Openalex Percentile: Top 27%
Remote Sensing and LiDAR Applications
1.03
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