multi-source fusion seasonal coastline dataset of China at 10m resolution (2019-2025)

This dataset provides a high-frequency (seasonal) and high-resolution (10m) tracking of China's coastline dynamics from 2019 to 2025. It is developed using the Google Earth Engine (GEE) platform by integrating Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 multispectral imagery. Methodology: Robust Compositing: Provincial-level coastlines were extracted from 50th percentile (median) composites of seasonal time-series data (MNDWI and SAR VV). This statistical strategy effectively suppresses transient noise such as wave foam, cloud shadows, and ship interference. Adaptive Extraction: A Tiled OTSU (block-based adaptive thresholding) algorithm was employed to handle spatial heterogeneity in water-land reflectance across the vast Chinese coastline, ensuring geometric continuity. Tidal Normalization: For four representative port sites (Binhai, Weihai, Kanmen, and Chongwu), the dataset provides both original median waterlines and tidally corrected coastlines. The latter were generated by coupling the FES2022 global tide model with a local slope-inversion algorithm, normalizing instantaneous waterlines to the Mean Sea Level (MSL) datum.