Discovering optimum method to extract depth information for nearshore coastal waters from Sentinel-2A imagery-case study: Nayband Bay, Iran

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Abstract

The capabilities of Sentinel-2A imagery to determine bathymetric information in shallow coastal waters were examined. In this regard, two Sentinel-2A images (acquired on February and March 2016 in calm weather and relatively low turbidity) were selected from Nayband Bay, located in the northern Persian Gulf. In addition, a precise and accurate bathymetric map for the study area were obtained and used for both calibrating the models and validating the results. Traditional linear and ratio transform techniques, as well as a novel integrated method, were employed to determine depth values. All possible combinations of the three bands (Band 2: blue (458-523 nm), Band 3: green (543-578 nm), and Band 4: red (650-680 nm), spatial resolution: 10 m) have been considered (11 options) using the traditional linear and ratio transform techniques, together with 10 model options for the integrated method. The accuracy of each model was assessed by comparing the determined bathymetric information with field measured values. The correlation coefficients (R2), and root mean square errors (RMSE) for validation points were calculated for all models and for two satellite images. When compared with the linear transform method, the method employing ratio transformation with a combination of all three bands yielded more accurate results (R2Mac = 0.795, R2Feb = 0.777, RMSEMac = 1.889 m, and RMSEFeb =2.039 m). Although most of the integrated transform methods (specifically the method including all bands and band ratios) have yielded the highest accuracy, these increments were not significant, hence the ratio transformation has selected as optimum method.

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Kabiri, K. (2017). Discovering optimum method to extract depth information for nearshore coastal waters from Sentinel-2A imagery-case study: Nayband Bay, Iran. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 42, pp. 105–110). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprs-archives-XLII-4-W4-105-2017

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