As China’s urbanization accelerates, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA)—a national strategic priority and globally significant urban agglomeration—has experienced rapid and intensive spatial expansion. While driving high-quality economic development, the region is also facing mounting ecological pressures, including habitat fragmentation, degradation of ecosystem functions, and diminishing environmental carrying capacity. Concurrently, the spatial distribution of population density increasingly overlaps with areas of ecological vulnerability, giving rise to spatial inequities between habitat quality and population exposure. These mismatches pose serious challenges for ecological justice, public health, and urban sustainability. This study aims to identify and evaluate spatial inequities in the relationship between habitat quality and population exposure across the GBA. We construct an integrated assessment framework that couples ecological degradation risk with population pressure. Habitat quality is quantified using the InVEST Habitat Quality model, incorporating land use classifications, threat intensity, and landscape sensitivity to produce a spatially continuous habitat quality index. Population exposure is estimated using high-resolution gridded data from WorldPop, capturing the extent to which residents are situated in ecologically degraded environments. Through spatial overlay and mismatch analysis, we identify “high exposure–low habitat” zones and classify exposure gradients via a cross-matrix of ecological risk and population intensity. Preliminary findings suggest that core metropolitan areas exhibit significant mismatches—high exposure coinciding with low habitat quality—while several peripheral regions, though ecologically intact, have low population carrying capacities, indicating inefficiencies in spatial resource distribution. This study contributes to understanding the spatial mechanisms behind habitat–population mismatches and highlights areas of environmental inequity. The results provide a scientific basis for prioritizing habitat restoration, optimizing green space allocation, and improving ecological governance. These insights are intended to support the development of resilient, inclusive, and ecologically balanced urban regions.