Abstract
Geospatial tools such as GIS (Geographic Information Systems) serve as a popular technology to assess and evaluate spatial dimensions of the food environment. While local-level policy decisions can be aided using GIS analysis and GIS data, little work has been invested in the holistic understanding of the data on which these decisions are made. In this paper, we address what entails high-quality geospatial data, challenges and opportunities that exist in the field of geospatial data development as applied to local-scale food environment research. We further explored factors of geospatial data quality assessment and quality control (QA/QC) for a commercially available business (CAB) database typically used in high-scale geospatial data analysis of the food environment. Factors related to the physical location of all food sources such as grocery stores and farmers markets and individualized vehicular transportation (roads) rated highest. They outweighed those related to land cover, utilities and zoning, which are more important in medium and low-scale (national level) analysis. When ranking various dimensions of data quality, subject matter experts found positional accuracy and attribute accuracy to be the most important in data development. However, errors related to temporal accuracy (age of data) exhibited the greatest number of errors within a CAB database. This schism serves as the impetus of this project and further addresses challenges between conceptual and practical geospatial data development policies and procedures.
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