This thesis is an analysis of the traditional data and methods used to evaluate food access and investigates the use of volunteered geographic information (VGI) in order to improve outcomes. It explores VGI as a potential improvement in the classification of food businesses and concludes with field research conducted on a subset of the selected facilities in order to determine the actual quality of the data retrieved from the experimental sources. The goal is to create a more nuanced and accurate representation of food access for a given person in a given place. Data is compared for areas with different socio-economic conditions in the Los Angeles metropolitan area. Median income, car access, and percent minority from the 2010-2014 American Community Survey (ACS) 5-year estimates were used to define contrasting study areas. Two census tracts in Los Angeles were selected for the study area using these criteria: (1) an affluent area near La Cañada; and (2) a less affluent area in South Los Angeles. This thesis explores the quality and completeness of three data sets for census tracts with contrasting socio-economic conditions in order to identify whether or not problems exist with traditional methods and data. Furthermore, this thesis compares the data from census tracts with contrasting socio-economic conditions in order to determine whether or not the data varies based on the community served. The results of this thesis indicate that VGI does not represent a significant addition to commercial data because so few of the businesses are represented in the VGI data set. Moreover, the use of NAICS codes to classify businesses proved to be problematic. Specifically, numerous businesses that were classified as super markets or grocery stores were in fact smaller than convenience stores and sold fewer items.
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