A geo-big data approach to intra-urban food deserts: Transit-varying accessibility, social inequalities, and implications for urban planning

Abstract Urban studies attempt to identify the geographic areas with restricted access to healthy and affordable foods (defined as food deserts in the literature). While prior publications have reported the socioeconomic disparities in healthy food accessibility, little evidence has been released from developing countries, especially in China. This paper proposes a geo-big data approach to measuring transit-varying healthy food accessibility and applies it to identify the food deserts within Shenzhen, China. In particular, we develop a crawling tool to harvest the daily travel time from each community (8117) to each healthy food store (102) from the Baidu Map under four transport modes (walking, public transit, private car, and bicycle) during 17:30–20:30 in June 2016. Based on the travel time calculations, we develop four travel time indicators to measure the healthy food accessibility: the minimum, the maximum, the weighted average, and the standard deviation. Results show that the four accessibility indicators generate different estimations and the nearest service (minimum time) alone fails to reflect the multidimensional nature of healthy food accessibility. The communities within Shenzhen present quite different typology with respect to healthy food accessibility under different transport modes. Multilevel additive regression is further applied to examine the associations between healthy food accessibility and nested socioeconomic characteristics at two geographic levels (community and district). We discover that the associations are divergent with transport modes and with geographic levels. More specifically, significant social equalities in healthy food accessibility are identified via walking, public transit, and bicycle in Shenzhen. Based on the associations, we finally map the food deserts and propose corresponding planning strategies. The methods demonstrated in this study should offer deeper spatial insights into intra-urban foodscapes and provide more nuanced understanding of food deserts in urban settings of developing countries.

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