Comparative Analysis of Multi-Spectral Shoreline Delineation Using Landsat-8, Sentinel-2, and PlanetScope Imageries in Coastal Environments of Nigeria

Changes in the shoreline position are a result of climate change-induced sea level rise and morphological changes caused by coastal processes. The delineation of shoreline positions relies on robust techniques and data sources, with remote sensing being particularly advantageous due to its cost-effectiveness and technological advancements. The study focuses on the eastern Niger Delta region of Nigeria, utilising mid-resolution multispectral datasets from Landsat-8 OLI, Sentinel-2 MSI, and PlanetScope to compare shoreline positions derived from different water indices (NDVI and NDWI) and classification methods. The research utilises mid-resolution multispectral datasets from Landsat-8 OLI, Sentinel-2 MSI, and PlanetScope to compare shoreline positions derived from different water indices (NDVI and NDWI) and threshold values. The methodology involves preprocessing optical imagery, applying water indices for shoreline delineation, and employing unsupervised classification techniques. The accuracy of shoreline positions is assessed using metrics such as mean error position (MEP) and root mean square error (RMSE), revealing significant discrepancies between datasets, particularly between high-resolution PlanetScope and coarser Landsat-8 imagery. Results indicate that the highest positional accuracy was achieved between PlanetScope and Sentinel-2, while Landsat-8 showed higher errors due to its coarser resolution. This study indicates that higher-resolution sensors provide more precise shoreline mapping, essential for effective coastal management. The study underscores the necessity of sensor-specific calibration and highlights the potential of integrating multiple satellite datasets to enhance the accuracy of shoreline monitoring and environmental assessments.