Three Decades of Land Cover Changes Shifted Environment‐Driven Greening Towards Browning in Coastal China

ABSTRACT Coastal vegetation serves as a protective buffer against the deleterious impacts of storm surges, influencing the dynamic exchange of energy and matter and mediating the lateral transport of carbon from land to the ocean. Comprehensive understanding of coastal vegetation dynamics is crucial for sustaining the ecological and biogeochemical functions of coastal ecosystems. Despite the considerable influence of land cover change (LCC) on vegetation greenness, quantifying this impact along the rapidly developing Chinese coasts amid significant social and economic changes over the past decades remains inadequately addressed. In this study, using moderate‐resolution Landsat‐based Normalized Difference Vegetation Index (NDVI), we found that LCC generally reduced the vegetation greenness and shifted the environment‐driven greening towards browning in coastal China over the past three decades. Compared to ‘ Stable Land Cover areas ’, ‘Land Cover Change areas’ exhibited a 23% decrease in greening proportion and a 39% increase in browning proportion. Urbanization occurring in coastal regions during 1992–2018 dominated the browning effect over 29% of ‘ LCC areas ’, which outweighed the greening effect of climate change, CO 2 fertilization, and nitrogen enrichment. This negative effect of urbanization on coastal vegetation was scarcely compensated by afforestation, despite the concurrent implementation of the National Coastal Shelterbelt System Construction Project (NCSSCP). The coastal afforestation area under the green scenario (SSP1‐2.6) during 2030–2060 is projected to be substantially higher than that of the past 30 years. It is expected to mitigate the negative effect of LCC on coastal vegetation greenness and enhance coastal ecosystem sustainability through ecological conservation policies, particularly forest restoration in the coastal zone of China. Furthermore, the insights derived from satellite observations in this study will serve as fundamental information for representing the coastal vegetation in the next generation of Earth system models (ESMs), enhancing the predictions related to future coastal ecosystem function and adaptation.