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Food Desert Identification: Going Beyond Geospatial Analysis

Vincenza Ferrara argues for "Measuring Food Deserts via GIS-Based Multicriteria Decision Making" (2017), written by Hassan Mohammadian Mosammam, Mozaffar Sarrafi, Jamileh Tavakoli Nia, and Ali Mohammadian Mosammam.

Published onDec 11, 2018
Food Desert Identification: Going Beyond Geospatial Analysis

Hassan Mohammadian Mosammam, Mozaffar Sarrafi, Jamileh Tavakoli Nia, and Ali Mohammadian Mosammam, “Measuring Food Deserts via GIS-Based Multicriteria Decision Making: The Case of Tehran,” The Professional Geographer 69, no. 3 (2017): 455–71.

In addressing the problem of food deserts, many researchers and organizations have focused on the “spatially unjust nature of food access issues.”[1] This attention to spatiality is predicated on the idea that, if we are able to measure food deserts, we will better understand food accessibility issues and have better information for urban planners and policy makers. To identify and measure food deserts, spatial analysis has typically looked at distance to large retail stores, together with several other relatively quantifiable indicators, such as poverty, income level, race, ethnicity, literacy level, and age. Scholars have often used Euclidean distance (the distance from a point to the closest chosen destination, based on a straight line) or more advanced measurements, such as network analysis (the shortest route), to measure travel distance or time. More recently, the advent of Geographic Information Systems (GIS) software has led to the development of even more sophisticated measurement methodologies.[2]

Although these tools are useful, a group of geographers, urban planners, and statistical analysts at Tehran’s Shahid Beheshti University and the University of Zanjan have shown that there is still a methodological gap in the literature regarding food desert identification. Thus far, scholars have often ignored residents’ opinions regarding the barriers they encounter in acquiring healthy and affordable food. In “Measuring Food Deserts via GIS-Based Multicriteria Decision Making: The Case of Tehran,” researchers Hassan Mohammadian Mosammam, Mozaffar Sarrafi, Jamileh Tavakoli Nia, and Ali Mohammadian Mosammam argue that, by pairing community perspectives on food accessibility status with geospatial data, we may gain a more comprehensive knowledge on food desert issues. This approach could help reframe the scope of planning interventions to better meet residents’ real needs.

With the aim of analyzing food deserts in Tehran, the authors—while still maintaining a geographical focus—developed a customized mixed methodology that combines people’s views with the geographical data: here, political ecology, spatial analysis, and food studies merge. As a first step, the research team analyzed the distance to retail food stores and public transportation stations, combining this information with population density and other environmental indicators. Using street network analysis, they then created one-mile and half-mile buffers around large food stores to determine their direct accessibility and to calculate network distances. Secondary data was also collected from the community councils of Tehran, local voluntary and participatory bodies.

Given that every neighborhood has its own specific characteristics and that the major barriers to food access might be place-specific, the research team carried out questionnaire surveys for each neighborhood council. These surveys asked members to determine the relative importance of the individual and environmental factors introduced by the researcher and to score them on a scale from 1 to 9. These opinions were then analyzed to rank the relative importance of each indicator per neighborhood, together with each factor’s weight (Figure 1).

Factors and indicators in food accessibility per neighborhood. Image credit: Hassan Mohammadian Mosammam, Mozaffar Sarrafi, Jamileh Tavakoli Nia, and Ali Mohammadian Mosammam

By overlaying the weights of these factors in each neighborhood with the geographic measures calculated in the first step of the research, the authors created a final accessibility map of Tehran (Figure 2).

By overlaying the weights of these factors in each neighborhood with the geographic measures calculated in the first step of the research, the authors created a final accessibility map of Tehran (Figure 2).

Compared to approaches that privilege only the objective analysis of geospatial data, these researchers have developed a more explicitly participatory methodology that provides a richer understanding of the factors shaping food access. Their study reveals noticeable disparities in food access in Tehran, where more than 26.6 percent of the population lives in low or very low food accessibility areas. More importantly, their results show that individual factors (i.e. income level and employment rate) are more significant than environmental factors (i.e. distance to food stores) in determining food accessibility.

Improving food access for marginalized communities requires a comprehensive and integrated approach that evaluates what people really need in specific localities. Hassan Mohammadian Mosammam, Mozaffar Sarrafi, Jamileh Tavakoli Nia, and Ali Mohammadian Mosammam provide a model for the consideration of all influencing factors (environmental and individual) in measuring healthy food accessibility. Other scholars designing multidisciplinary methodologies would do well to follow their lead.


Biography

Vincenza Ferrara is a small-scale farmer in Sicily, where she works with ancient olive trees, running a farm according to the principles of agroecology. Having graduated in Global Environmental History at Uppsala University with minors in Historical Ecology and Geographic Information Systems, her scientific interests are related to the transdisciplinary investigation of the long-term dynamics of social ecological systems. More specifically, she focuses on biocultural refugia in rural marginalized areas through the combination of spatial analysis techniques and the Traditional Ecological Knowledge of local communities.

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