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Interactive three-dimensional geovisualization of space–time access to food
Applied Geography 43 (2013) 81e86
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Applied Geography journal homepage: www.elsevier.com/locate/apgeog
Interactive three-dimensional geovisualization of spaceetime access to food Xiang Chen a, *, Jill Clark b a b
Center for Urban and Regional Analysis and Department of Geography, The Ohio State University, Columbus, OH 43210, United States John Glenn School of Public Affairs, The Ohio State University, Columbus, OH 43210, United States
a b s t r a c t Keywords: Food deserts Spaceetime Food accessibility Opening hours Geovisualization
A majority of literature about food deserts is focused on geographic access to food retailers by a buffered distance differentiating high and low access. An overlooked facet in this representation is that food acquisition is not only geographically dictated, but it is also temporally constrained. Food retailers invariably have limited opening hours that create a temporal restriction for shoppers. In this paper, a three-dimensional (3D) construct was proposed to delineate the limited food access to a retailer location across space and over its time of operation. Food retailer data in Columbus, OH, USA were collected for examining the variation of food access on both spatial and temporal scales. This study also employed the technique of interactive 3D modeling in a geographic information system (GIS) to visualize the food environment to delimit where and when food is accessible on a daily basis. The interactive 3D geovisualization (visualization of geographic information) of spaceetime access contributed to improving the representation of food environment and exploring the inequity of food access across space and over time. The development of this geovisualization context for food science studies could assist public health professionals and government stakeholders in understanding the effect of temporal access and improving food access for regions with limited operation hours in policy formulation. 2013 Elsevier Ltd. All rights reserved.
Introduction Food deserts are areas deprived of sufficient access to nutritious, wholesome, and affordable food resulting in inequitable food access across communities (Cummins & Macintyre, 2002). Many of such areas are predominantly characterized by a high level of poverty and excessive exposure to unhealthy diets, which put local residents at risk of unforeseen health issues, such as obesity, cardiovascular disease, and Type II diabetes (Shaw, 2006). The problem of inequitable food access owes its origin to social exclusion, where low-income neighborhoods in urban areas are often excluded from easy access to fresh and healthy food retailers. This lack of accessibility limits the variety of food choices and eventually impoverishes quality of life. The connection between food deserts and social, economic, and ethnic implications have raised concerns from not only social science scholars, but also from government stakeholders. In 2008, for the first time, the U.S. Congress urged the U.S. Department of Agriculture (USDA) to initiate a study to examine the food deserts problem in the U.S. (USDA, 2009). Further, local governments are becoming interested in interventions to * Corresponding author. Tel.: þ1 6142922514. E-mail address: [email protected] (X. Chen). 0143-6228/$ e see front matter 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.apgeog.2013.05.012
increase healthy food access to low-income residents (Algert, Agrawal, & Lewis, 2006). Geographic access is considered an integral component in identifying so called food deserts. Most of the previous studies have evaluated the problem by identifying the spatial dimension of poor access (USDA, 2009). The measure of food deserts invariably starts from identifying an inventory of grocery retailers that provide fresh fruits and vegetables, or the so called “green retailers” (Wrigley, Warm, Margetts, & Whelan, 2002). Next, an acceptable distance to physically access these retailers is determined and a region is demarcated around these retailer indicating zones of good access. Consequently the areas outside of these zones have poor access and are considered food deserts. Defining food deserts from this spatial perspective stems from the observation that people tend to procure food from suppliers in their immediate vicinities (Furey, Strugnell, & McIlveen, 2001). The uneven distribution of retailer locations puts residents who lack equal access at a disadvantage of a healthy daily diet, just as Michimi and Wimberly (2010) found in metropolitan areas across the U.S. regarding fruit and vegetable consumption. This inaccessibility to food correlates to the low socioeconomic status (such as car-ownership, poverty rate, education, ethnicity, etc.) of deprived populations and further corroborates the theory of social inequity.
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An overlooked piece in this conceptualization of food deserts is the dimension of time as it relates to space. Time, a resource that can be traded for space, is of equal importance as space. As space separates an individual traveler from acquiring food supplies, time can also become a constraint impinging on the operation of food retailers as well as the mobility of individuals. When time at one’s disposal conflicts with the opening hours of stores, the food choices available to the individual become limited (Smoyer-Tomic, Spence, & Amrhein, 2006). For example, according to the Bureau of Labor Statistics, a substantial number of Americans do not work traditional Monday through Friday, 9 AM to 5 PM jobs (McMenamin, 2007). While opening and closing times vary, most chain grocery stores do not operate early in the morning or late at night, and these limited hours of operation can greatly restrict the availability of procuring nutritious food for people working non-traditional shifts. Time brings in a new dimension to the evaluation of food access problems when people’s social roles are involved (Rose & Richards, 2004). People burdened with house chores, such as cleaning and chauffeuring children, may find themselves temporally unable to access grocery stores on weekdays and may instead undertake their shopping trips on the weekend. For people who rely on bus service, busses may not run on weekends or may have limited service hours. Business people working in the city center are constrained by rigid time budgets, and the inability to undertake discretionary activities can result in their diet options dependent on unhealthy packaged food, even though they realize fresh fruits and vegetables are a necessity to their health (Shaw, 2006). Therefore, people’s mobility in accessing food is not only spatially constrained, but also temporally. The interpretation of food access should not only examine the geographic access to green retailers, but also the temporal access referring to the times when these retailers become available. In this paper, the temporal constraints of food access are considered by taking into account the opening hours of the food retailers in the urban area of Columbus, OH, USA. In order to visualize the spatiotemporal constraints that impinge on food access, a three-dimensional (3D) visualization method is developed by using interactive 3D GIS (Geographic Information System) techniques to illustrate the availability of food retailers in the city in both spatial and temporal dimensions. Not only is the uneven geographic distribution of food access identified, but also examined is the variation of access by time of day. This geovisualization of temporal access to food could facilitate a better understanding of the food deserts problem beyond the conventional geographical perspective. This enhanced understanding of food deserts on the temporal scale could shed new light on policy-making oriented toward improving the benefits of people who are not only geographically, but also temporally disadvantaged at obtaining healthy food. Visualizing temporal constraints on food access In previous research several types of barriers have been established for describing the constraints individuals may face in their everyday effort to access healthy food: geographic, economic, cultural, and informational (McEntee & Agyeman, 2010; Shaw, 2006; Short, Guthman, & Raskin, 2007). Geographic barriers, in general, refer to the spatial separation of landscape that limits one’s ability to acquire food. Often it is not only about the space itself, but is also about other physical restrictions that prevent the relocation between places, such as available modes of travel. Economic barriers refer to financial facets that limit affordability of food that can be otherwise physically accessed or consumed. Relatively high food prices can become a major economic barrier for low-income populations in buying food, and the comparison of the cost of food has
shown significant price variations between stores (Donkin, Dowler, Stevenson, & Turner, 2000). Another economic barrier beyond the cost of food items is the cost of travel, including such things as gas, car upkeep or bus fare (Hallett & McDermott, 2011). Culturallyappropriate access means shoppers can find food and a shopping environment that is acceptable to them, such as languages spoken in the store, marketing in the store etc. (Short et al., 2007). Lastly, informational barriers pertain to limited nutritional knowledge and lack of cooking skills that prevent individuals from making healthy food choices. Informational barriers were found to be associated with individuals’ lack of educational attainment and the cooking culture in their life experience (Glanz et al., 1993). The majority of literature on food deserts gives attention to examining the geographic barriers to food access. The interpretation of effective access is measured by a simple “container” approach, to a rough “buffer” approach, and lately to a “network” approach as a close estimate of geographic access (Larsen & Gilliland, 2008). Traditional measures adopted a simple “container” approach (Fig. 1(a)) by estimating the number of green retailers within a chosen geographic unit, such as county or census tract as a measure of advantage in food access. The number of the retailers was further examined in conjunction with socio-economic variables to reveal the geographic isolation of certain neighborhoods (Alwitt & Donley, 1997; Eckert & Shetty, 2011; Raja, Ma, & Yadav, 2008). Although the “container” approach is relatively easy to implement, it suffers from the modifiable areal unit problem (MAUP). MAUP refers to the arbitrary division of geographic unit could significantly influence the results (Cao & Lam, 1997; Fotheringham & Wong, 1991). In order to overcome the MAUP, a “buffer” approach (Fig. 1(b)) was adopted by creating a walkable or drivable distance/time from these retailer locations, and areas not within the buffers were metaphorically termed “deserts”, which possess a low level of accessibility (Guy & David, 2004; Hubley, 2011; Morton & Blanchard, 2007). An extension of this “buffer” approach considered the “network” approach (Fig. 1(c)) regarding that travel in a real-world scenario can only take place along the channels of road networks. The measure of nearness to a retailer should consider the network path distance or travel time as a more accurate estimate, bringing forth insights to the awareness of the irregularly shaped “deserts” (Hallett & McDermott, 2011; McEntee & Agyeman, 2010; Mulangu & Clark, 2012; Pearce, Witten, & Bartie, 2006; Russell & Heidkamp, 2011). Meanwhile, some other studies explored a hybrid approach in an attempt to examine geographic access by making use of different accessibility measures (Apparicio, Cloutier, & Shearmur, 2007; Guy, Clarke, & Eyre, 2004; Paez, Mercado, & Farber, Morency, & Roorda, 2010; Smoyer-Tomic et al., 2006). An extension of the geographic access was articulated from the perspective of time. Because geographic regions experience constant opening and closing of markets, some recent food studies considered the influence from food access to be variant over a period of time. Wrigley, Warm, and Margetts (2003) and Wrigley
Fig. 1. Three traditional measures of geographic access to food retailers: a) the container approach, b) the buffer approach, and c) the network approach.
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et al. (2002) investigated the impact of the intervention of a superstore on an economically deprived area in a British city by comparing the before/after period of the store opening, and found that residents who were previously reliant on budget stores had increased their fruit and vegetable consumption after switching to shopping at the superstore. Guy et al. (2004) compared effective access to food retailers over twenty years by exploring a gravitytyped accessibility measure, and found that the improvement in food access is more prominent in high-income areas than in lowincome areas. Larsen and Gilliland (2008) compared the level of food provision in a mid-sized Canadian city between 1961 and 2005, and found that the spatial inequity of food access between affluent regions and poor regions had greatly enlarged over the four-decade period. Recently, Widener, Metcalf, and Bar-Yam (2011) examined the opening and closing of local farmers’ markets in Buffalo, NY on a weekly basis over a year, and found that wealthier groups had the privilege of food access during the off-season of farmers’ markets over the relatively impoverished groups; and for the peak-season the conclusion was the opposite. The above comparative studies use time to examine the effects of establishing new food outlets and/or closing existing food outlets on food access. In other words, time is used as “before” and “after” to evaluate the impact of changing store locations. These studies do not examine how time is a dimension of access on a daily basis of existing stores, as the opening times and closing times of markets vary between regions as well as between private retailers and franchise supermarkets. The need to scrutinize both spatial and temporal aspects of access calls for a better construct to interpret time as a third dimension in the visualization of food access. The extension of traditional geographic access could include a perpendicular axis to represent the time a store is in effective operation. A simple example of this construct is given in Fig. 2, where S1 and S2 are spatial axes representing two geographic directions (e.g. east and north) and T is the temporal axis representing the time of 24 h. The generated pillar in Fig. 2 describes food access from the buffer-based approach based on a store i with coordinates (xi, yi). The pillar is created by extruding from the store’s opening time (toi) by its total hours of operation (tci toi), or the time window. The radius of the pillar is defined by travel velocity (vm) via transportation mode m and travel time (T) characterizing efficient time to acquiring food. The boundary of the pillar in this 3D coordinate system demarcates a spaceetime region where the store can be accessed efficiently during its time of operation. This pillar can thus be referred as a 3D spaceetime food access pillar. Similarly, this 3D construct can be applied to other approaches to modeling food access as shown in Fig. 3. Specifically, Fig. 3(a) is the container-based food access derived from synthetic values summarized from a set of stores in a region. Therefore, the
Fig. 2. A 3D spaceetime food access pillar.
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Fig. 3. Three different measures of spaceetime food access in a 3D environment: a) the container approach, b) the buffer approach, and c) the network approach.
average of the temporal variables of stores in a region can be used for describing the size and positions of the cube-shaped food access. Fig. 3(c) is the network-based approach where food access is restricted by the boundary of networks and within the time window of the store. It can be seen that when time is introduced into the measurement, the level of accessibility will not be constant as in a 2D map; rather it will vary by time of day. The accessible area can be identified by introducing a horizontal time slice to intersect the 3D spaceetime food access pillars created from stores in a region. An example of this time slice is illustrated in Fig. 6 in the case study section. By locating this time slice at time t, the overlap of the time slice and the 3D constructs yields a geographic area that represents efficient access to food retailers at a time of day. More formally, if a buffer-based approach is considered, the measure of food access in a region S at time t can be defined as AS,t, such that
AS;t ¼ W p$v2m $T 2 $di;t i˛S
where
di;t ¼
1 0
if toi t tci otherwise
In this case, di,t is a binary variable defining if store i is in effective operation at time t. The food access is measured by the area of the union of all accessible retailer areas at time t. By implementing this method to a case study region, not only areas deprived of food access can be identified, but also the time of day when the region has limited food choices can be retained. Application: visualizing spaceetime food access in Columbus, OH In order to reveal the variation of food access among different places and over a period of time, a case study was conducted in Columbus, OH, a middle-sized city located in Midwest U.S. The retail store data was acquired from the ESRI Business Analyst in terms of sourced point business data from InfoUSA. A North American Industrial Classification System (NAICS) code was used to identify green retailers that carry fresh fruits and vegetables. Specifically, supercenters (NAICS code 4529) such as Walmart and supermarkets/convenience stores (NAICS code 4529) were extracted from the study area. After this preliminary extraction, these retailers were narrowed down by eliminating stores with less than five employees. This selective criterion aims to eliminate small convenience stores that do not carry fresh produce. A total of 118 stores were selected as green retailers by this method. The opening hours of these retailers were updated by referring to their respective business webpages or by phone investigation for those without published hours. Although some stores had different opening hours
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between weekdays and weekends, or even between weekdays, only the most frequent weekday hours were used for each store. Finally, the road network was used to interpret the relative locations of the selected retailers. ESRI ArcGIS was adopted as the platform for geovisualization. Although traditional GIS technique has mainly focused on spatial mapping in two dimensions. The ArcGIS 3D Analysis extension allows visualizing geographic data in a 3D perspective due to its ability to model and render 3D objects. Fig. 4 shows the geovisualization of spaceetime food access pillars in the study area from different observation points, namely, a 45-degree view in Fig. 4(a), a top view in Fig. 4(b), and a side view in Fig. 4(c). This modeling environment is highly interactive in that the visual properties of these pillars can be altered to reflect their times of opening and closing. The created pillars represented high geographic access to the green retailers at a certain distance and during the stores’ opening hours. They were extended from the buffer-based approach of food access to adding a temporal dimension to represent their opening hours. Specifically, the radii of the pillars were ubiquitously defined by mode of walking at vm ¼ 2 miles/h, T ¼ 15 min, and thereafter for each store high access was within a 0.5 miles or 0.8 km distance, which was regarded as a reasonable distance by other food desert studies (Algert et al., 2006, USDA 2009). The height of a pillar was defined by the total hours of operation (cti coi) for a store in a 24-h period. The spaceetime food access pillars were color-coded to include additional attributes of the stores, and in this case the closing time (tci) was used. By including this additional information, regions with limited access in evening hours (red and brown pillars) could be identified. In this respect, the 3D geovisualization method not only provides information regarding food access in space and time, but is also capable of highlighting areas deprived of access in certain times of day. An extension of this interactive geovisualization considers identifying food access with respect to the total hours of operation. In order to see the pattern of stores’ hours of operation across the study area, a 3D density surface was generated to represent the spatial variation of store openings in a period of a day, as shown in Fig. 5. This 3D geovisualization method employed a non-parametric smoothing algorithm called kernel density estimation (Kwan & Lee, 2003). The intensity of the density surface was estimated by the kernel function with respect to the total hours of opening in a 24-h
Fig. 5. A top view of the 3D kernel density surface of spaceetime food access with respect to stores’ total hours of operation. Peaks indicate good access and troughs indicate poor access. Arrowed areas have good geographical access but poor temporal access to food retailers.
period. This density surface was initially generated in the format of a raster layer and then was converted to a 3D scene in ArcGIS with Z-axis being the interpolated hours of opening. The road network layer with a highlighted highway (I-270) was overlapped to locate the peaks and troughs of the density surface. It can be seen that the majority of Columbus has good food access, and the food deserts are found largely to the east of downtown and outside the south and southwest of I-270, which is a very close estimation verified by the USDA Food Access Research Atlas (USDA, 2013). However, when the duration of operation plays a role in limiting the opportunities of acquiring food, those areas (see red-arrowed areas in Fig. 5, in the web version) conventionally considered to have good food access become limited in access due to their relatively limited hours of operation. This restriction may cause residents living in these areas to experience difficulties in obtaining fresh food when their working hours overlap with store hours of operation. These areas, although geographically covered by food retailers, can be considered temporally deprived food deserts. Rather than knowing where the food deserts are, it is more interesting to know when the deserts appear in the period of a day. Fig. 6 shows a horizontal time slice intersecting the spaceetime
Fig. 4. 3D geovisualization of spaceetime food access in Columbus, OH from a) a 45-degree view, b) a top view, and c) a side view from south to north.
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Fig. 6. A time slice at 20:00 intersecting the spaceetime food access pillars in Columbus, OH.
Fig. 7. Variation of food access over the period of 24 h in Columbus, OH.
food access pillars at the time of 20:00. The overlaps of the time slice and the pillars give rise to areas that are only accessible at t ¼ 20, where the total calculated area AS,t can be regarded as the measure of food accessibility in the city. By moving the time slice from t ¼ 0 to t ¼ 24, the variation of food access on a temporal scale can be identified, as is shown in Fig. 7. Fig. 7 is a diagram generated by the total accessible area by every half an hour. It is apparent that the access is the lowest during the early times of day from 0:30 to 5:30, gradually increases to its peak at 11:00, and then starts to taper at 19:30. This temporal variation could provide profound implications on policy adjustment of store hours of operation. By limiting the study area to a certain neighborhood, this method could provide evidence for identifying time periods lacking sufficient food access, and in these temporally deprived food deserts longer openings are expected to fulfill residents’ needs for fresh groceries.
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access in defining food deserts problem, this paper could help public health professionals and government stakeholders to identify regions with limited store hours of operation and to assist in improving these temporally deprived regions for policy formulation. The application demonstrates preliminary results about the spaceetime food access problem in the study area and provides a foundation for future research. First, the formulation is based on a simple container approach to demarcate the spaceetime constrained food access regions. In the future, the network approach should be adopted to produce a more accurate accessible area around each retailer location, and in this respect the presentation of the 3D spaceetime food access becomes irregular shapes rather than clear-cut pillars, as the example seen in Fig. 3(c). Second, as is noted by the formula, the measure of food access AS,t is an areabased index determined by not only a temporal variable t being time of day but also a spatial variable S. How this spatial variable reacts to the change of time would produce a quantitative measure of the temporal inequity of food access across space. Another possibility is to include the different modes of travel in describing an efficient access to food by changing the variable of travel speed vm, and allowed travel time T. Third, food access problems are not only spatiotemporally constrained but are more importantly articulated by whether or not healthy food is affordable and modes of transportation are available to individual travelers (Donkin et al., 2000; Hallett & McDermott, 2011). An improved representation of food impoverished areas should resort to distribution of poverty rate and car-ownership. A proposed solution in the implementation will be intersecting the 3D spaceetime food access pillars with a poverty layer and a car-ownership layer to identify regions that are not only deprived of spaceetime access, but are also impinged by socio-economic disadvantage in access. Lastly, a remaining flaw of the study pertains to the elimination of individual travel behaviors, in that travelers may procure food through trip-chaining on the commute from workplace to home (Chen & Kwan, 2012), how these complex travel behaviors can be appropriately delineated in the geovisualization of 3D food environment will be an interesting facet to be explored in the future. Acknowledgements The authors wish to thank Dr. Morton O’Kelly and Adam Wehmann at Department of Geography, The Ohio State University for their valuable suggestions to this research. The authors also appreciate the anonymous reviewers for their constructive comments to improve the manuscript.
Conclusion References The problem of efficient access to healthy food has been explored from various aspects. A prevailing representation of access is by geographic measures that differentiate places by either high access or low access to food retailers. Time, a factor that determines the availability of food sources throughout the course of the day, is introduced in this paper to complement the conventional conceptualization of the geographic access to food. Time plays an important role in dictating the opening of food retailers on a daily basis by adding a third dimension to the constraints on food acquisition. The paper proposes a 3D construct, namely the spaceetime food access pillar, to visualize the limited access to a food retailer across space and over time. In addition, the case study in Columbus, OH exemplifies a possibility of employing this method in a real-world food environment. The incorporation of temporal aspect to food access is a notable contribution to rethinking the food deserts problem: daily access to fresh food is not only geographically dictated, but also temporally constrained. By including the temporal variation of food
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Applied Geography journal homepage: www.elsevier.com/locate/apgeog
Interactive three-dimensional geovisualization of spaceetime access to food Xiang Chen a, *, Jill Clark b a b
Center for Urban and Regional Analysis and Department of Geography, The Ohio State University, Columbus, OH 43210, United States John Glenn School of Public Affairs, The Ohio State University, Columbus, OH 43210, United States
a b s t r a c t Keywords: Food deserts Spaceetime Food accessibility Opening hours Geovisualization
A majority of literature about food deserts is focused on geographic access to food retailers by a buffered distance differentiating high and low access. An overlooked facet in this representation is that food acquisition is not only geographically dictated, but it is also temporally constrained. Food retailers invariably have limited opening hours that create a temporal restriction for shoppers. In this paper, a three-dimensional (3D) construct was proposed to delineate the limited food access to a retailer location across space and over its time of operation. Food retailer data in Columbus, OH, USA were collected for examining the variation of food access on both spatial and temporal scales. This study also employed the technique of interactive 3D modeling in a geographic information system (GIS) to visualize the food environment to delimit where and when food is accessible on a daily basis. The interactive 3D geovisualization (visualization of geographic information) of spaceetime access contributed to improving the representation of food environment and exploring the inequity of food access across space and over time. The development of this geovisualization context for food science studies could assist public health professionals and government stakeholders in understanding the effect of temporal access and improving food access for regions with limited operation hours in policy formulation. 2013 Elsevier Ltd. All rights reserved.
Introduction Food deserts are areas deprived of sufficient access to nutritious, wholesome, and affordable food resulting in inequitable food access across communities (Cummins & Macintyre, 2002). Many of such areas are predominantly characterized by a high level of poverty and excessive exposure to unhealthy diets, which put local residents at risk of unforeseen health issues, such as obesity, cardiovascular disease, and Type II diabetes (Shaw, 2006). The problem of inequitable food access owes its origin to social exclusion, where low-income neighborhoods in urban areas are often excluded from easy access to fresh and healthy food retailers. This lack of accessibility limits the variety of food choices and eventually impoverishes quality of life. The connection between food deserts and social, economic, and ethnic implications have raised concerns from not only social science scholars, but also from government stakeholders. In 2008, for the first time, the U.S. Congress urged the U.S. Department of Agriculture (USDA) to initiate a study to examine the food deserts problem in the U.S. (USDA, 2009). Further, local governments are becoming interested in interventions to * Corresponding author. Tel.: þ1 6142922514. E-mail address: [email protected] (X. Chen). 0143-6228/$ e see front matter 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.apgeog.2013.05.012
increase healthy food access to low-income residents (Algert, Agrawal, & Lewis, 2006). Geographic access is considered an integral component in identifying so called food deserts. Most of the previous studies have evaluated the problem by identifying the spatial dimension of poor access (USDA, 2009). The measure of food deserts invariably starts from identifying an inventory of grocery retailers that provide fresh fruits and vegetables, or the so called “green retailers” (Wrigley, Warm, Margetts, & Whelan, 2002). Next, an acceptable distance to physically access these retailers is determined and a region is demarcated around these retailer indicating zones of good access. Consequently the areas outside of these zones have poor access and are considered food deserts. Defining food deserts from this spatial perspective stems from the observation that people tend to procure food from suppliers in their immediate vicinities (Furey, Strugnell, & McIlveen, 2001). The uneven distribution of retailer locations puts residents who lack equal access at a disadvantage of a healthy daily diet, just as Michimi and Wimberly (2010) found in metropolitan areas across the U.S. regarding fruit and vegetable consumption. This inaccessibility to food correlates to the low socioeconomic status (such as car-ownership, poverty rate, education, ethnicity, etc.) of deprived populations and further corroborates the theory of social inequity.
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An overlooked piece in this conceptualization of food deserts is the dimension of time as it relates to space. Time, a resource that can be traded for space, is of equal importance as space. As space separates an individual traveler from acquiring food supplies, time can also become a constraint impinging on the operation of food retailers as well as the mobility of individuals. When time at one’s disposal conflicts with the opening hours of stores, the food choices available to the individual become limited (Smoyer-Tomic, Spence, & Amrhein, 2006). For example, according to the Bureau of Labor Statistics, a substantial number of Americans do not work traditional Monday through Friday, 9 AM to 5 PM jobs (McMenamin, 2007). While opening and closing times vary, most chain grocery stores do not operate early in the morning or late at night, and these limited hours of operation can greatly restrict the availability of procuring nutritious food for people working non-traditional shifts. Time brings in a new dimension to the evaluation of food access problems when people’s social roles are involved (Rose & Richards, 2004). People burdened with house chores, such as cleaning and chauffeuring children, may find themselves temporally unable to access grocery stores on weekdays and may instead undertake their shopping trips on the weekend. For people who rely on bus service, busses may not run on weekends or may have limited service hours. Business people working in the city center are constrained by rigid time budgets, and the inability to undertake discretionary activities can result in their diet options dependent on unhealthy packaged food, even though they realize fresh fruits and vegetables are a necessity to their health (Shaw, 2006). Therefore, people’s mobility in accessing food is not only spatially constrained, but also temporally. The interpretation of food access should not only examine the geographic access to green retailers, but also the temporal access referring to the times when these retailers become available. In this paper, the temporal constraints of food access are considered by taking into account the opening hours of the food retailers in the urban area of Columbus, OH, USA. In order to visualize the spatiotemporal constraints that impinge on food access, a three-dimensional (3D) visualization method is developed by using interactive 3D GIS (Geographic Information System) techniques to illustrate the availability of food retailers in the city in both spatial and temporal dimensions. Not only is the uneven geographic distribution of food access identified, but also examined is the variation of access by time of day. This geovisualization of temporal access to food could facilitate a better understanding of the food deserts problem beyond the conventional geographical perspective. This enhanced understanding of food deserts on the temporal scale could shed new light on policy-making oriented toward improving the benefits of people who are not only geographically, but also temporally disadvantaged at obtaining healthy food. Visualizing temporal constraints on food access In previous research several types of barriers have been established for describing the constraints individuals may face in their everyday effort to access healthy food: geographic, economic, cultural, and informational (McEntee & Agyeman, 2010; Shaw, 2006; Short, Guthman, & Raskin, 2007). Geographic barriers, in general, refer to the spatial separation of landscape that limits one’s ability to acquire food. Often it is not only about the space itself, but is also about other physical restrictions that prevent the relocation between places, such as available modes of travel. Economic barriers refer to financial facets that limit affordability of food that can be otherwise physically accessed or consumed. Relatively high food prices can become a major economic barrier for low-income populations in buying food, and the comparison of the cost of food has
shown significant price variations between stores (Donkin, Dowler, Stevenson, & Turner, 2000). Another economic barrier beyond the cost of food items is the cost of travel, including such things as gas, car upkeep or bus fare (Hallett & McDermott, 2011). Culturallyappropriate access means shoppers can find food and a shopping environment that is acceptable to them, such as languages spoken in the store, marketing in the store etc. (Short et al., 2007). Lastly, informational barriers pertain to limited nutritional knowledge and lack of cooking skills that prevent individuals from making healthy food choices. Informational barriers were found to be associated with individuals’ lack of educational attainment and the cooking culture in their life experience (Glanz et al., 1993). The majority of literature on food deserts gives attention to examining the geographic barriers to food access. The interpretation of effective access is measured by a simple “container” approach, to a rough “buffer” approach, and lately to a “network” approach as a close estimate of geographic access (Larsen & Gilliland, 2008). Traditional measures adopted a simple “container” approach (Fig. 1(a)) by estimating the number of green retailers within a chosen geographic unit, such as county or census tract as a measure of advantage in food access. The number of the retailers was further examined in conjunction with socio-economic variables to reveal the geographic isolation of certain neighborhoods (Alwitt & Donley, 1997; Eckert & Shetty, 2011; Raja, Ma, & Yadav, 2008). Although the “container” approach is relatively easy to implement, it suffers from the modifiable areal unit problem (MAUP). MAUP refers to the arbitrary division of geographic unit could significantly influence the results (Cao & Lam, 1997; Fotheringham & Wong, 1991). In order to overcome the MAUP, a “buffer” approach (Fig. 1(b)) was adopted by creating a walkable or drivable distance/time from these retailer locations, and areas not within the buffers were metaphorically termed “deserts”, which possess a low level of accessibility (Guy & David, 2004; Hubley, 2011; Morton & Blanchard, 2007). An extension of this “buffer” approach considered the “network” approach (Fig. 1(c)) regarding that travel in a real-world scenario can only take place along the channels of road networks. The measure of nearness to a retailer should consider the network path distance or travel time as a more accurate estimate, bringing forth insights to the awareness of the irregularly shaped “deserts” (Hallett & McDermott, 2011; McEntee & Agyeman, 2010; Mulangu & Clark, 2012; Pearce, Witten, & Bartie, 2006; Russell & Heidkamp, 2011). Meanwhile, some other studies explored a hybrid approach in an attempt to examine geographic access by making use of different accessibility measures (Apparicio, Cloutier, & Shearmur, 2007; Guy, Clarke, & Eyre, 2004; Paez, Mercado, & Farber, Morency, & Roorda, 2010; Smoyer-Tomic et al., 2006). An extension of the geographic access was articulated from the perspective of time. Because geographic regions experience constant opening and closing of markets, some recent food studies considered the influence from food access to be variant over a period of time. Wrigley, Warm, and Margetts (2003) and Wrigley
Fig. 1. Three traditional measures of geographic access to food retailers: a) the container approach, b) the buffer approach, and c) the network approach.
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et al. (2002) investigated the impact of the intervention of a superstore on an economically deprived area in a British city by comparing the before/after period of the store opening, and found that residents who were previously reliant on budget stores had increased their fruit and vegetable consumption after switching to shopping at the superstore. Guy et al. (2004) compared effective access to food retailers over twenty years by exploring a gravitytyped accessibility measure, and found that the improvement in food access is more prominent in high-income areas than in lowincome areas. Larsen and Gilliland (2008) compared the level of food provision in a mid-sized Canadian city between 1961 and 2005, and found that the spatial inequity of food access between affluent regions and poor regions had greatly enlarged over the four-decade period. Recently, Widener, Metcalf, and Bar-Yam (2011) examined the opening and closing of local farmers’ markets in Buffalo, NY on a weekly basis over a year, and found that wealthier groups had the privilege of food access during the off-season of farmers’ markets over the relatively impoverished groups; and for the peak-season the conclusion was the opposite. The above comparative studies use time to examine the effects of establishing new food outlets and/or closing existing food outlets on food access. In other words, time is used as “before” and “after” to evaluate the impact of changing store locations. These studies do not examine how time is a dimension of access on a daily basis of existing stores, as the opening times and closing times of markets vary between regions as well as between private retailers and franchise supermarkets. The need to scrutinize both spatial and temporal aspects of access calls for a better construct to interpret time as a third dimension in the visualization of food access. The extension of traditional geographic access could include a perpendicular axis to represent the time a store is in effective operation. A simple example of this construct is given in Fig. 2, where S1 and S2 are spatial axes representing two geographic directions (e.g. east and north) and T is the temporal axis representing the time of 24 h. The generated pillar in Fig. 2 describes food access from the buffer-based approach based on a store i with coordinates (xi, yi). The pillar is created by extruding from the store’s opening time (toi) by its total hours of operation (tci toi), or the time window. The radius of the pillar is defined by travel velocity (vm) via transportation mode m and travel time (T) characterizing efficient time to acquiring food. The boundary of the pillar in this 3D coordinate system demarcates a spaceetime region where the store can be accessed efficiently during its time of operation. This pillar can thus be referred as a 3D spaceetime food access pillar. Similarly, this 3D construct can be applied to other approaches to modeling food access as shown in Fig. 3. Specifically, Fig. 3(a) is the container-based food access derived from synthetic values summarized from a set of stores in a region. Therefore, the
Fig. 2. A 3D spaceetime food access pillar.
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Fig. 3. Three different measures of spaceetime food access in a 3D environment: a) the container approach, b) the buffer approach, and c) the network approach.
average of the temporal variables of stores in a region can be used for describing the size and positions of the cube-shaped food access. Fig. 3(c) is the network-based approach where food access is restricted by the boundary of networks and within the time window of the store. It can be seen that when time is introduced into the measurement, the level of accessibility will not be constant as in a 2D map; rather it will vary by time of day. The accessible area can be identified by introducing a horizontal time slice to intersect the 3D spaceetime food access pillars created from stores in a region. An example of this time slice is illustrated in Fig. 6 in the case study section. By locating this time slice at time t, the overlap of the time slice and the 3D constructs yields a geographic area that represents efficient access to food retailers at a time of day. More formally, if a buffer-based approach is considered, the measure of food access in a region S at time t can be defined as AS,t, such that
AS;t ¼ W p$v2m $T 2 $di;t i˛S
where
di;t ¼
1 0
if toi t tci otherwise
In this case, di,t is a binary variable defining if store i is in effective operation at time t. The food access is measured by the area of the union of all accessible retailer areas at time t. By implementing this method to a case study region, not only areas deprived of food access can be identified, but also the time of day when the region has limited food choices can be retained. Application: visualizing spaceetime food access in Columbus, OH In order to reveal the variation of food access among different places and over a period of time, a case study was conducted in Columbus, OH, a middle-sized city located in Midwest U.S. The retail store data was acquired from the ESRI Business Analyst in terms of sourced point business data from InfoUSA. A North American Industrial Classification System (NAICS) code was used to identify green retailers that carry fresh fruits and vegetables. Specifically, supercenters (NAICS code 4529) such as Walmart and supermarkets/convenience stores (NAICS code 4529) were extracted from the study area. After this preliminary extraction, these retailers were narrowed down by eliminating stores with less than five employees. This selective criterion aims to eliminate small convenience stores that do not carry fresh produce. A total of 118 stores were selected as green retailers by this method. The opening hours of these retailers were updated by referring to their respective business webpages or by phone investigation for those without published hours. Although some stores had different opening hours
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between weekdays and weekends, or even between weekdays, only the most frequent weekday hours were used for each store. Finally, the road network was used to interpret the relative locations of the selected retailers. ESRI ArcGIS was adopted as the platform for geovisualization. Although traditional GIS technique has mainly focused on spatial mapping in two dimensions. The ArcGIS 3D Analysis extension allows visualizing geographic data in a 3D perspective due to its ability to model and render 3D objects. Fig. 4 shows the geovisualization of spaceetime food access pillars in the study area from different observation points, namely, a 45-degree view in Fig. 4(a), a top view in Fig. 4(b), and a side view in Fig. 4(c). This modeling environment is highly interactive in that the visual properties of these pillars can be altered to reflect their times of opening and closing. The created pillars represented high geographic access to the green retailers at a certain distance and during the stores’ opening hours. They were extended from the buffer-based approach of food access to adding a temporal dimension to represent their opening hours. Specifically, the radii of the pillars were ubiquitously defined by mode of walking at vm ¼ 2 miles/h, T ¼ 15 min, and thereafter for each store high access was within a 0.5 miles or 0.8 km distance, which was regarded as a reasonable distance by other food desert studies (Algert et al., 2006, USDA 2009). The height of a pillar was defined by the total hours of operation (cti coi) for a store in a 24-h period. The spaceetime food access pillars were color-coded to include additional attributes of the stores, and in this case the closing time (tci) was used. By including this additional information, regions with limited access in evening hours (red and brown pillars) could be identified. In this respect, the 3D geovisualization method not only provides information regarding food access in space and time, but is also capable of highlighting areas deprived of access in certain times of day. An extension of this interactive geovisualization considers identifying food access with respect to the total hours of operation. In order to see the pattern of stores’ hours of operation across the study area, a 3D density surface was generated to represent the spatial variation of store openings in a period of a day, as shown in Fig. 5. This 3D geovisualization method employed a non-parametric smoothing algorithm called kernel density estimation (Kwan & Lee, 2003). The intensity of the density surface was estimated by the kernel function with respect to the total hours of opening in a 24-h
Fig. 5. A top view of the 3D kernel density surface of spaceetime food access with respect to stores’ total hours of operation. Peaks indicate good access and troughs indicate poor access. Arrowed areas have good geographical access but poor temporal access to food retailers.
period. This density surface was initially generated in the format of a raster layer and then was converted to a 3D scene in ArcGIS with Z-axis being the interpolated hours of opening. The road network layer with a highlighted highway (I-270) was overlapped to locate the peaks and troughs of the density surface. It can be seen that the majority of Columbus has good food access, and the food deserts are found largely to the east of downtown and outside the south and southwest of I-270, which is a very close estimation verified by the USDA Food Access Research Atlas (USDA, 2013). However, when the duration of operation plays a role in limiting the opportunities of acquiring food, those areas (see red-arrowed areas in Fig. 5, in the web version) conventionally considered to have good food access become limited in access due to their relatively limited hours of operation. This restriction may cause residents living in these areas to experience difficulties in obtaining fresh food when their working hours overlap with store hours of operation. These areas, although geographically covered by food retailers, can be considered temporally deprived food deserts. Rather than knowing where the food deserts are, it is more interesting to know when the deserts appear in the period of a day. Fig. 6 shows a horizontal time slice intersecting the spaceetime
Fig. 4. 3D geovisualization of spaceetime food access in Columbus, OH from a) a 45-degree view, b) a top view, and c) a side view from south to north.
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Fig. 6. A time slice at 20:00 intersecting the spaceetime food access pillars in Columbus, OH.
Fig. 7. Variation of food access over the period of 24 h in Columbus, OH.
food access pillars at the time of 20:00. The overlaps of the time slice and the pillars give rise to areas that are only accessible at t ¼ 20, where the total calculated area AS,t can be regarded as the measure of food accessibility in the city. By moving the time slice from t ¼ 0 to t ¼ 24, the variation of food access on a temporal scale can be identified, as is shown in Fig. 7. Fig. 7 is a diagram generated by the total accessible area by every half an hour. It is apparent that the access is the lowest during the early times of day from 0:30 to 5:30, gradually increases to its peak at 11:00, and then starts to taper at 19:30. This temporal variation could provide profound implications on policy adjustment of store hours of operation. By limiting the study area to a certain neighborhood, this method could provide evidence for identifying time periods lacking sufficient food access, and in these temporally deprived food deserts longer openings are expected to fulfill residents’ needs for fresh groceries.
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access in defining food deserts problem, this paper could help public health professionals and government stakeholders to identify regions with limited store hours of operation and to assist in improving these temporally deprived regions for policy formulation. The application demonstrates preliminary results about the spaceetime food access problem in the study area and provides a foundation for future research. First, the formulation is based on a simple container approach to demarcate the spaceetime constrained food access regions. In the future, the network approach should be adopted to produce a more accurate accessible area around each retailer location, and in this respect the presentation of the 3D spaceetime food access becomes irregular shapes rather than clear-cut pillars, as the example seen in Fig. 3(c). Second, as is noted by the formula, the measure of food access AS,t is an areabased index determined by not only a temporal variable t being time of day but also a spatial variable S. How this spatial variable reacts to the change of time would produce a quantitative measure of the temporal inequity of food access across space. Another possibility is to include the different modes of travel in describing an efficient access to food by changing the variable of travel speed vm, and allowed travel time T. Third, food access problems are not only spatiotemporally constrained but are more importantly articulated by whether or not healthy food is affordable and modes of transportation are available to individual travelers (Donkin et al., 2000; Hallett & McDermott, 2011). An improved representation of food impoverished areas should resort to distribution of poverty rate and car-ownership. A proposed solution in the implementation will be intersecting the 3D spaceetime food access pillars with a poverty layer and a car-ownership layer to identify regions that are not only deprived of spaceetime access, but are also impinged by socio-economic disadvantage in access. Lastly, a remaining flaw of the study pertains to the elimination of individual travel behaviors, in that travelers may procure food through trip-chaining on the commute from workplace to home (Chen & Kwan, 2012), how these complex travel behaviors can be appropriately delineated in the geovisualization of 3D food environment will be an interesting facet to be explored in the future. Acknowledgements The authors wish to thank Dr. Morton O’Kelly and Adam Wehmann at Department of Geography, The Ohio State University for their valuable suggestions to this research. The authors also appreciate the anonymous reviewers for their constructive comments to improve the manuscript.
Conclusion References The problem of efficient access to healthy food has been explored from various aspects. A prevailing representation of access is by geographic measures that differentiate places by either high access or low access to food retailers. Time, a factor that determines the availability of food sources throughout the course of the day, is introduced in this paper to complement the conventional conceptualization of the geographic access to food. Time plays an important role in dictating the opening of food retailers on a daily basis by adding a third dimension to the constraints on food acquisition. The paper proposes a 3D construct, namely the spaceetime food access pillar, to visualize the limited access to a food retailer across space and over time. In addition, the case study in Columbus, OH exemplifies a possibility of employing this method in a real-world food environment. The incorporation of temporal aspect to food access is a notable contribution to rethinking the food deserts problem: daily access to fresh food is not only geographically dictated, but also temporally constrained. By including the temporal variation of food
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