Rapid urbanization to support population growth and economic development has led to substantial land use changes, exerting strain on the health of both ecosystems and people. This raises concerns about environmental justice, as marginalized communities often bear a disproportionate burden of these impacts due to historical inequities, economic disparities, and systemic barriers. This research evaluated neighborhood environments and health and well-being outcomes from an environmental justice perspective in several U.S. cities, by developing a novel method using open-source geodata to analyze a landscape’s level of green space accessibility and built density. Leveraging open-source geodata from OpenStreetMap, QGIS and Python were used to characterize landscapes by green space access and density exposure. R was used to perform path analysis aimed at assessing these parameters as mediators between demographic factors and health outcomes. The results revealed disparities in green space access across the three cities, influenced by race and income. Furthermore, significant associations were found between socio-economic status, environmental factors, and health outcomes. Green space access mediated the relationship between race and health outcomes with mixed results: in San Francisco, access to green space mitigated obesity risk, while in Boston, it was associated with increased depression levels. These nuanced findings highlight the complexity of urban environmental dynamics and emphasize the need for further research on the interplay between urban landscapes, socio-economic factors, and health outcomes. The novel method developed in this study provides opportunities for future research and practical applications that support health equity and well-being in urban environments.