Objective: The goal of the present study was to use a methodology that accurately and reliably describes the availability, price and quality of healthy foods at both the store and community levels using the Nutrition Environment Measures Survey in Stores (NEMS-S), to propose a spatial methodology for integrating these store and community data into measures for defining objective food access. Setting: Two hundred and sixty-five retail food stores in and within 2 miles (3.2 km) of Flint, Michigan, USA, were mapped using ArcGIS mapping software. Design: A survey based on the validated NEMS-S was conducted at each retail food store. Scores were assigned to each store based on a modified version of the NEMS-S scoring system and linked to the mapped locations of stores. Neighbourhood characteristics (race and socio-economic distress) were appended to each store. Finally, spatial and kernel density analyses were run on the mapped store scores to obtain healthy food density metrics. Results: Regression analyses revealed that neighbourhoods with higher socio-economic distress had significantly lower dairy sub-scores compared with their lower-distress counterparts (beta coefficient=-1.3; P=0.04). Additionally, supermarkets were present only in neighbourhoods with <60 % African-American population and low socio-economic distress. Two areas in Flint had an overall NEMS-S score of 0. Conclusions: By identifying areas with poor access to healthy foods via a validated metric, this research can be used help local government and organizations target interventions to high-need areas. Furthermore, the methodology used for the survey and the mapping exercise can be replicated in other cities to provide comparable results.