First application of AlphaEarth Data for detecting coastline and land use changes in the Pearl River Estuary, China

Continuous dynamic monitoring of coastline changes is essential for revealing the evolutionary laws and spatiotemporal characteristics of coastal systems. In this study, we employed AlphaEarth Foundations (AEF) data and Sentinel-2 imagery to investigate coastline and land use changes in the Pearl River Estuary (PRE) region over the period 2017–2023. The Random Forest (RF) algorithm was adopted to extract coastlines and classify coastal land-use types, after which their spatiotemporal evolution was quantitatively analyzed. The results demonstrate that the classification performance of AEF data is significantly better than that of Sentinel-2 imagery, with the average overall accuracy and Kappa coefficient exceeding 92% and 89%, respectively. The PRE coastline shows an evolutionary pattern of “overall contraction accompanied by regional differentiation”: its total length first increased and then decreased, peaking at 1029.05 km in 2019, representing a cumulative net reduction of 7.54 km over the 2017–2023 period. Meanwhile, land use expansion driven by reclamation resulted in a cumulative net increase of 25.26 km2. Aquaculture ponds (AP) constitute the dominant type of newly reclaimed land, accounting for more than 50%, while the expansion of impervious surface (IS) accounts for 24.52%. This study provides novel insights and a scientific basis for the refined management of coastlines, sustainable land use planning, and coastal-marine ecological protection in the Pearl River Estuary and similar regions worldwide.