###### Abstract  
As urbanization processes are no longer characterized by simple linear expansion but exhibit leaping, edge-sparse, and discontinuous features, spatiotemporally continuous impervious surface coverage data are needed to better characterize urbanization processes. This study utilized GAIA impervious surface binary data and employed spatiotemporal aggregation methods to convert thirty years of 30 m resolution data into 1 km resolution spatiotemporal impervious surface coverage data, constructing a long-term time series annual impervious surface coverage dataset for the Beijing-Tianjin-Hebei region. Based on this dataset, we analyzed urban expansion processes and landscape pattern indices in the Beijing-Tianjin-Hebei region, exploring the spatiotemporal response relationships of ecological environment changes. Results revealed that the impervious surface area increased dramatically from 7579.3 km\({}^{2}\) in 1985 to 37,484.0 km\({}^{2}\) in 2020, representing a year-on-year growth of 88.5%. Urban expansion rates showed two distinct peaks: 800 km\({}^{2}\)/year around 1990 and approximately 1700 km\({}^{2}\)/year during 2010-2015. In high-density urbanized areas with impervious surfaces, the average forest area significantly increased from approximately 2500 km\({}^{2}\) to 7000 km\({}^{2}\) during 1985-2005 before rapidly declining, grassland patch fragmentation intensified, while in low-density areas, grassland area showed fluctuating decline with poor ecosystem stability. Furthermore, by incorporating natural and social factors such as Fractional Vegetation Coverage (FVC), Habitat Quality Index (HQI), Land Surface Temperature (LST), slope, and population density, we assessed the vulnerability of urbanization development in the Beijing-Tianjin-Hebei region. Results showed that high vulnerability areas (EVI > 0.5) in the Beijing-Tianjin core region continue to expand, while the proportion of low vulnerability areas (EVI < 0.25) in the northern mountainous regions decreased by 4.2% in 2020 compared to 2005. This study provides scientific support for the sustainable development of the Beijing-Tianjin-Hebei urban agglomeration, suggesting location-specific and differentiated regulation of urbanization processes to reduce ecological risks. 2025 14 1599 10.390/land14081599 10.390/land14081599 10.390/10/14081599 10.  
urban expansion and ecological vulnerability has become critical. Urban expansion leads to habitat loss [2], reduced carbon storage, and decreased regional climate regulation capacity [3], particularly in developing countries experiencing rapid growth. Impervious surfaces are ground areas where water cannot penetrate, such as rooftops, roads, parking lots, and sidewalks [4]. In recent years, they have been widely applied in monitoring and assessment studies of urbanization processes [5], involving mapping and estimating impervious surface area using remote sensing data [6; 7], and further used to study long-term dynamic changes in urban expansion [8]. There are now many mature impervious surface data products available, such as artificial impervious surfaces mapped at 250-500 m resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) data [9]; 30 m resolution GAIA (Global Artificial Impervious Area) data generated based on Landsat satellite imagery and auxiliary data [10; 11]; and 100 m resolution GISA (Global Impervious Surface Area) data generated by fusing multi-source data [12]. Specifically, GAIA constructs long-term remote sensing index features (such as NDVI, NDBI, MNDWI) by analyzing Landsat satellite imagery (30 m resolution), combined with machine learning methods such as random forest for pixel-level classification judgment; based on the annual impervious status, temporal consistency judgment and threshold setting are further applied to form the final binary product. Grid values of 1 indicate that the pixel is identified as an impervious surface in that year and thereafter, while values of 0 indicate a non-impervious surface [10].