Improving spatial and temporal accuracy in coastal reclamation mapping using satellite image time series

Abstract

Driven by urban expansion and economic growth, China has carried out extensive coastal reclamation in the past four decades, leading to negative ecological impacts. Accurate mapping of reclamation dynamics helps analyze its environmental effects and supports the government in regulating reclamation projects. Nevertheless, existing methods for monitoring coastal reclamation dynamics face two major limitations: overestimating reclamation areas and low temporal accuracy. This study proposes a novel method to automatically distinguish artificial reclamation from natural expansion to reduce the overestimation of reclaimed areas and improve temporal dynamic accuracy through time-series analysis of long-term Landsat satellite imagery. In China’s coastal regions, our method achieves an overall classification accuracy of over 94 % for artificial reclamation and natural expansion. The estimation accuracies of the year of reclamation are 91.60 % (one-year tolerance) and 96.44 % (two-year tolerance), which are more accurate than the post-classification comparison method based on the Global Surface Water (GSW) dataset. From 1990 to 2022, China’s coastal reclamation totaled 5,121.1 km2, with a slowdown after 2014 and a shift toward green development after 2018. Reclamation patterns varied regionally, with most projects concentrated in economically developed bays, driven primarily by urbanization and industrialization. The results prove that the proposed method can improve the spatiotemporal accuracy of coastal reclamation mapping, hence providing a more reliable data foundation for project siting, ecological impact assessment, and coastal management.