Satellite-derived bathymetry for shallow coastal waters in Cyprus
12 September 2021 in Δημοσίευση
Proceedings Volume 11857, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2021; 1185703. Event: SPIE Remote Sensing, 2021, Online Only https://doi.org/10.1117/12.2599911
Η μελέτη αυτή αφορά την εκτίμηση δορυφορικής βαθυμετρίας για τα ρηχά νερά της Κύπρου με την χρήση του δορυφορικού οπτικού αισθητήρα Spot 6 & 7
Evagoras Evagorou, Christodoulos Mettas, Diofantos Hadjimitsis
Department of Civil Engineering and Geomatics, School of Engineering and Technology, Cyprus University of Technology, 30 Arch. Kyprianos Str., 3036 Limassol, Cyprus
Eratosthenes Centre of Excellence, 30 Arch. Kyprianos Str., 3036 Limassol, Cyprus
Published: 12 September 2021
Abstract. During the last years, many studies related to Satellite-Derived Bathymetry (SDB) emphasize the potential use of optical satellite remote sensing sensors for bathymetric estimation. For this study, ten multispectral SPOT 6/7 satellite images with a medium resolution covering the coastal waters of the study areas were analyzed. These images were geometric, radiometric, and atmospheric corrected and acquired in three different sensing dates having coverage with at least 30% of lidar data. A number of 5284 random depth measurements with 0 to 50 meters depth were acquired for the ratio conversion algorithm with absolute depths and error assessment. A series of steps were performed to obtain reliable results using satellite optical data such as, sun glint process, land/sea extraction, kernel filters. The study area was divided into three sub-regions, based on the sensing date of the satellite imageries. The light attenuation in the water column increases at a depth of about thirty meters as seen in other related studies. This study identified the depth of light attenuation to determine the maximum depth that can be estimated through optical sensors. The results show that better correlation was identified up to 15 meters depth. Results of the regression analysis show the following correlation coefficients R² :0.90, 0.87, 0.80, and 0.89 with the Root Mean Square Error (RMSE) for the respective study areas to be 1.34, 1.53 1.70 and, 1.15.
