Comparing Landsat-8 OLI, Sentinel-2 MSI, and PlanetScope Imagery for Coastline Change Detection: A Case Study of El-Alamein Coast, Egypt

The coastline extraction and change detection analysis is an important task that has application in different fields such as coastal development and planning, hazard mapping, erosion-accretion studies, predictive modeling of coastal morphodynamics. Coastline delineation is difficult, time consuming, and sometimes impossible for entire coastal system when using traditional ground survey techniques. Satellites provide data at spatial-temporal scales that can be used for coastal change detection. PlanetScope nano-satellites have spatial (3 m) and temporal (daily) resolutions that may help improve coastal monitoring compared to
coarser-resolution satellites. This work compared different Sensors of Landsat-8 OLI (15m resampled spatial resolution), Sentinel-2 MSI (10m resampled spatial resolution), and PlanetScope (3m) to detect coastline change overtime. Recent advances in remote sensing and geographical information system (GIS) techniques are overcoming the difficulties in extraction of shoreline position and detection of coastline changes.

In the paper, the area of El-Alamein area along the Egyptian Mediterranean coast, which facing recently a dramatically changes due to the urbanization and human impacts, has been chosen and coastline extracted from Landsat-8 (OLI), Sentinel-2 MSI, and PlanetScope satellite images (2015, 2018 and 2021). The Normalized Difference Water Index (NDWI) was applied to water/land separation using ERDAS Imagine 2015 Package, and then shoreline detection using ENVI 5.3 Software. The delineated coastlines have been analyzed using Digital Shoreline Analysis System (DSAS.v5), a GIS Software tool for estimation of shoreline change rates calculated through two statistical techniques such as, End Point Rate (EPR) and Linear Regression Rate (LRR). The results refers to mapping Coastline change and rates overtime-using different sensors, and evaluation the spatial accuracy.