Shoreline change rate detection applying the DSAS technique on low and medium resolution data: Case study along Ash Shu’aybah-Al Mujayrimah coastal Area of the Eastern Red Sea, Saudi Arabia

Abstract

The Ash Shu’aybah and Al Mujayrimah coast area in Saudi Arabia is threatened by constantly changing shoreline dynamics. This work explains how to appropriately quantify shoreline change rates using the Landsat and Sentinel-2 datasets, predict the coastline after twenty years (2022–2042) and compare the results from both satellite data. The technique used depends on the integration of remote sensing data and Geographic Information Systems (GIS) with a Digital Shoreline Analysis System tool (DSAS). For calculating shoreline change rates and predicting future shoreline positions in 2042, eight Landsat satellite images over 36 years from 1986 to 2022 were analysed along with four Sentinel-2 satellite images from 2015 to 2022. Based on the LRR models’ data, the shoreline is exposed to erosion with average values of −3.25 and −2.12 m/yr for the Sentinel-2 and the Landsat datasets, respectively. Segment 2 in the central part of the coastline is the area most affected by the dynamics of the shoreline. To assess the accuracy of the obtained results, the root mean square error (RMSE), the mean annual error (MAE) and coefficient of determination (R2) were used. The results indicated that both the Sentinel-2 and the Landsat datasets can reliably calculate the shoreline change rate of the study area based on the similar patterns of their data, although the Sentinel-2 had a somewhat better ability in calculating the change of the shoreline.