As a critical component of global wetland ecosystems, coastal wetlands are facing dual pressures from climate change and human activities, highlighting the urgent need for a precise classification dataset with large spatial scale and high temporal resolution. The national coastal wetland mappings year by year over the last four decades are crucial for coastal integrated management. A robust and automated classification method was developed based on coastline delineation and integrations of multiple algorithms. By analyzing more than 60,000 Landsat images of China’s coastal areas and incorporating field survey validation data, an annual coastal wetland spatial distribution dataset with 30-meter spatial resolution spanning from 1985 to 2024 was established. The dataset obtained an average Kappa coefficient of 0.957 and a range from 0.978 to 0.935, and the average overall accuracy was 97.6% with a range of 97.12% - 97.85%. The proposed method has achieved high-precision annual coastal wetland spatial datasets and effectively monitored the impacts of invasive species and ecological restoration projects on interannual changes in coastal wetlands.

High spatiotemporal variance in land spatial development intensity occurs during rapid socioeconomic development. However, this remains poorly understood in large-scale coastal areas owing to limitations in quantification accuracy and spatial resolution. In this study, the land spatial development intensity in a large-scale coastal area of China was quantified by examining three major types of development areas: ecological, agricultural, and built-up areas. The quantity and quality of these area types were measured to improve quantification accuracy, and a spatial resolution of 100 m × 100 m was employed to capture detailed spatial information. Two time points, 2020 and 2010, were considered as the temporal interval to investigate the spatiotemporal characteristics of land spatial development intensity indices (DIIs) in the context of extensive ecological restoration. The effects of land spatial development intensity on soil organic carbon density (SOCD) were analyzed. The results revealed that ecological and built-up areas exhibited the “patch” spatial pattern, while agricultural areas exhibited the “area” pattern. The coastline is a unique land feature that influences the spatial distribution of ecological and agricultural areas. The DIIs of the ecological, agricultural, and built-up areas increased by 22.29%, 16.33%, and 32.55%, respectively, from 2010 to 2020. Quality improvement benefiting from ecological restoration largely drove the DII increase in ecological and agricultural areas, while quantity enlargement and quality promotion jointly determined the DII increase in built-up areas. Generally, the increase in DIIs contributed to an increase in the SOCD from 2010 to 2020. Specifically, the DII increase in ecological and agricultural areas led to a remarkable improvement in soil carbon sinks in large-scale coastal areas, while that in built-up areas decreased it to a lesser degree. The contributions of the ecological, agricultural, and built-up areas to the SOCD spatiotemporal variations were 45.12%, 40.87%, and 14.01%, respectively, in the entire study area.