SEED: A Synthesized Multi-Dimensional Environmental Exposure Database for Neighborhood Profiling

The Synthesized Multi-Dimensional Environmental Exposure Database (SEED) has been developed to address the need for integrated, high-resolution data that captures the complexity of human–environment interactions. While much of the existing literature focuses on single exposures, SEED provides a comprehensive framework for examining the cumulative and interrelated effects of multiple environmental factors on health and well-being.The SEED includes a broad set of spatially harmonized indicators covering physical environmental, urban built environment, socioeconomic environment and population context. Physical environmental exposures are represented through measures of air pollution (e.g., AOD, NO2, CO), urban heat (e.g., land surface temperature), access to green spaces (e.g., normalized difference vegetation index, green view factor and canopy height), and built environment attributes (e.g., POI density, street connectivity). To account for population vulnerability and contextual disparities, socio-demographic variables and ethnicity profiles are systematically integrated. Human perception factors provide street-view–derived human perception indicators that represent the subjective dimension of environmental exposure.All indicators are standardized to a common spatial resolution, allowing fine-grained examination of exposure heterogeneity across neighborhoods. By combining these diverse datasets, SEED facilitates the construction of multidimensional neighborhood profiles that highlight both dominant exposure characteristics and underlying structural patterns. This database provides a robust empirical foundation for advanced spatial modelling, the assessment of environmental inequalities, and the design of policy-relevant interventions aimed at fostering healthier and more equitable urban environments.