Coastline Extraction and Spatiotemporal Change Analysis of Jiangsu Province Using Sentinel-2 Multispectral Imagery from 2018 to 2025

Accurate coastline extraction in muddy and macro-tidal environments is challenging due to tidal variability and complex coastal surfaces. The Jiangsu coast of China, characterized by extensive tidal flats, silty coastlines, and strong land–sea interactions, provides an ideal case for long-term coastline change analysis. This study investigates the spatiotemporal evolution of the Jiangsu coastline from 2018 to 2025 using multi-temporal Sentinel-2 imagery. A tide-independent coastline extraction framework was developed by integrating the Normalized Difference Water Index, Modified Normalized Difference Water Index, and Normalized Difference Vegetation Index for different coastal environments. An annual maximum spectral index composite was applied to approximate the highest water-level conditions without explicit tidal correction. Coastline dynamics were quantified using fractal dimension analysis and a transect-based method. The extracted coastlines yielded an average Root Mean Square Error (RMSE) of 13.14 m and an average Mean Absolute Distance Error (MADE) of 9.39 m. Results show that the total coastline length varied within 5% during the study period, with a maximum of 1079.84 km in 2022 and a minimum of 1004.99 km in 2018. Coastline change was dominated by erosion, accounting for 56.21% of the total coastline length. Land cover analysis revealed that accretion mainly occurred near river mouths and aquaculture areas, whereas erosion was more common at interfaces between forested land and engineered coastlines. The proposed framework provides an efficient and consistent approach for short-term coastline monitoring in muddy coastal environments.