The Food Trust is dedicated to improving access to affordable, healthy food. The non-profit offers programming within a network of different sites in various communities. The aim of this project was to identify and create community categories in Philadelphia and develop a Food Trust programming index to help measure program impact and target programming.
Because certain populations are disproportionately affected by lack of food access, it is important to find the right kinds of communities to offer programming. To help address this problem, Carlos used the Grouping Analysis tool, which uses K-means clustering to find natural patterns within data. In this case, Census Block Group data of populations potentially vulnerable to food access was used to cluster geographies into specific groups. This technique was able to reliably identify up to 4 different communities in the city that share certain characteristics.
To score for program intensity, data was consolidated from many different sources and standardized. Each location was scored by program on binary and continuous scales. All layers created for this project were uploaded into an interactive web map. This map illustrates different communities throughout the city and program outreach throughout The Food Trust network. It will help the non-profit analyze and target programming in Philadelphia.