Map and analyze food access

Access to fresh food is a fundamental indicator of long-term health and well-being. Food deserts are places with low or severely restricted availability of nutritious, affordable food. On a systemic scale, food systems intersect with issues involving equity, raising vital questions about who has access to fresh food and where patterns of access or restriction exist within communities.

Working with data from the Open Data DC Hub and ArcGIS Living Atlas of the World, you'll use spatial analysis tools to visualize food deserts in Washington, D.C.

This tutorial was last tested on August 18, 2026.

Requirements

• ArcGIS organizational account with a Publisher, Facilitator, or Administrator role (see options for software access)
• 44 credits

Map and analyze food access

Open the map

Using spatial analysis tools in Map Viewer, you'll identify places that potentially have greater access to food based on being within walking distance of a grocery store in Washington, D.C. The results of your analysis will show gaps in food access, revealing areas that are potential food deserts.

First, you'll open an existing web map and save a copy.

1. Open the DC Grocery Stores web map.

   The map appears in Map Viewer.

   

   The map has four layers and a basemap. These layers come from Open Data DC, a collection of apps, maps, dashboards, and data layers for the District of Columbia.

   Note:

   Many municipalities offer similar repositories of geospatial data that are free and open for use by the public. If you want to apply this workflow to your local community, search for and explore a data hub with layers specific to your study area.

   The map contains the following layers:

   • The DC Ward Boundaries layer shows the eight wards that make up the District of Columbia. These ward boundaries are used for representation, planning, and decision-making. Each ward contains a diverse collection of neighborhoods and is represented by a different elected council member.
   • The DC Detailed Ward Boundaries layer does not include areas within the wards where people do not live. Using this layer to determine potential food desert areas will be more accurate and better aligned with lived experiences in the city. It is considered best practice to consider local characteristics that might affect the accuracy of your analysis. This layer was created by merging several layers from the Open Data DC Hub, including military bases, parks, water bodies, and wetlands. This merged layer was erased from the DC Ward Boundaries layer, resulting in a layer that only includes habitable sections of each ward.
   • The Grocery Store Locations layer shows the locations of grocery stores and healthy corner stores. The healthy corner stores data comes from the DC Central Kitchen's (DCCK) Healthy Corners program, which includes corner stores that sell fresh, nutritious produce. For this analysis, these two types of stores have been combined to provide a greater distribution of facilities across the study area.
   • The DC Boundary layer contains the boundary of Washington, D.C.

   You'll save a copy of the map to your own ArcGIS organizational account to work with for the rest of the tutorial. To save a copy, you'll first sign in to your ArcGIS organizational account.

2. On the ribbon, click Sign In. Sign in using your ArcGIS organizational account.

   Note:

   If you don't have an organizational account, see options for software access.

3. On the Contents (dark) toolbar, click Save and open and choose Save as.

   

4. In the Save map window, for Title, type Food Deserts in Washington, D.C. Click Save.

Generate walking areas

One key barrier to food access is distance. Many under-resourced communities rely on walking and public transit to access grocery stores. To understand where there may be a lack of grocery stores, you'll use the Generate Travel Areas tool to create a feature layer showing areas that are within a 10-minute walking distance of grocery store locations across the city. This tool is one of the proximity tools used to analyze map data based on how close or far away another feature is.

1. In the Layers pane, confirm the Grocery Store Locations layer is selected.

   

   The blue bar on the layer indicates that the layer is selected.

   Note:

   If the layer is not selected, click it to select it.

2. On the Settings (light) toolbar, click Analysis.

   

3. In the Analysis pane, click Tools.

   

4. Expand Use proximity and click Generate Travel Areas.

   

   The Generate Travel Areas tool pane appears. In this pane, you can set the parameters for the tool. Required parameters are marked with a red dot.

5. For Input layer, click Layer. In the Select layer window, click Grocery Store Locations.

   The layer is added as the input layer.

   

   Next, you'll set the walking time for the analysis. You want to find areas within a 10-minute walk of a grocery store.

6. Under the Analysis settings section, for Travel mode, choose Walking Time.
7. For Cutoffs, type 10 and click Add. Confirm that Cutoff units is set to Minutes.
8. For Travel direction, choose Toward input locations. For Arrival time, confirm that Time unspecified is chosen.

   

   Next, you'll indicate how you want overlapping travel areas to be handled. You'll choose to merge any overlapping areas into one feature.

9. For Overlap policy, choose Dissolve.

   

   Next, you'll indicate whether you want travel areas to be generated as one continuous polygon or to include holes on streets that are not reachable but are fully surrounded by reachable streets. You'll choose to include holes.

10. Check the box next to Generate detailed polygons.

    

11. In the Result layers section, for Output name, type Travel Time 10 Minutes and add your name or initials.

    

    Note:

    You cannot create two layers in an ArcGIS organization with the same name. Adding your initials to a layer name ensures that other people in your organization can also complete this tutorial. Once a layer has been created, you can rename it in the map to remove your initials, which will not affect the name of the underlying data layer.

    Running an analysis tool consumes credits. Credits are the currency used across ArcGIS Online. They are consumed during specific transactions, such as performing analytics, storing features, and geocoding. Before running an analysis, it's a good idea to check how many credits will be consumed.

12. Click Estimate credits.

    

    When running analysis tools, the credit cost is typically calculated by multiplying the number of features by the credit cost of the tool. This analysis will consume 42.5 credits.

    Note:

    You can learn how many remaining credits are in your ArcGIS Online account if your organization administrator has enabled you to view that information. If it is enabled, at the top of the page, click your username and choose My settings. On the My settings page, click Credits to see how many remaining credits are in your account. If it is not enabled, contact your organizational account administrator. To learn more about credits, see Understand credits. If you do not have enough credits to run this tool, you can use the Travel time 10 Minutes (Tutorials) layer to continue the tutorial. To add this layer to your map, in the Layers pane, click Add. Search ArcGIS Online for Travel time 10 Minutes owner:Esri_Tutorials and click the Add button for the appropriate layer.

13. Click Run.

    It may take a few minutes for the tool to run. When it finishes, the new layer is added to the Layers pane and drawn on the map. The purple areas show the 10-minute walking areas around each grocery store location.

    

Determine potential food deserts

There are several factors that can be used to identify food deserts, ranging from affordability of goods to having vehicle access. The Hunger Heat Map from the Capital Area Food Bank presents one approach to mapping food access in the D.C. metropolitan area and was used to inform this workflow. When structuring an analysis such as this, it is essential that you understand the local dynamics of your study area, including the demographic makeup, infrastructure, and policies (both historical and present) that may influence patterns of inequity.

To simplify this analysis, you'll consider gaps in proximity to grocery stores as an indicator of potential food deserts. A gap doesn't necessarily mean that people living there don't have access and a lack of a gap doesn't always mean that access is abundant. You might live within a five-minute walk of a grocery store, but if you work during its operating hours or the products are unaffordable, access to fresh food may be low or nonexistent.

Next, you'll identify potential gaps in food access by finding the places that are outside of the 10-minute walking area layer. Using the Overlay Layers tool, you'll overlay and erase the 10-minute walking areas from the geographic boundaries that divide the city into eight wards.

1. After the tool finishes running and the new layer has been added to the map, in the Analysis pane, click Back.

   

2. Expand the Manage data section and click Overlay Layers.

   

3. In the Overlay Layers tool pane, for Input features, click Layer and choose DC Detailed Ward Boundaries.
4. For Overlay features, choose Travel Time 10 minutes.

   

5. In the Overlay settings section, for Overlay type, choose Erase.

   

   When you set the overlay type to erase, the tool will take the overlay features and remove, or erase, them from the input features, leaving you with a layer showing areas that are not within a 10-minute walk of grocery stores.

6. In the Result layer section, for Output name, type Potential Food Deserts and add your name or initials.

   Note:

   It will require 0.009 credits to run this tool.

7. Click Run.

   After the tool finishes running, the new layer is added to the Layers pane and drawn on the map. You no longer need the original walk-time layer, so you'll remove it.

8. In the Layers pane, for the Travel Time 10 minutes layer, click the Options button and choose Remove.

   

   The remaining overlay layer represents potential food deserts, defined in this case as areas outside of a 10-minute walking radius of a grocery store.

   

   Note:

   Optionally, you can add layers for Metro stations and Emergency food providers to better understand some more of the many variables that affect food availability and access for the D.C area. See the Add layers from a URL documentation for information on how to add these layers to the map.

9. On the Contents toolbar, click Save and open and choose Save.

For this tutorial, you only considered one aspect of what contributes to food deserts—walking distance. In reality, there are many complex and cumulative factors that contribute to what makes an area a food desert. This might include historic land use practices that resulted in decades of disinvestment, inadequate public transit systems, and income inequality causing healthy foods to be less affordable. When conducting an equity analysis, it is important to consider the unique characteristics of the city or jurisdiction you are investigating and to tailor your analysis to reflect the experiences of those who are experiencing the inequalities.

You can find more tutorials in the tutorial gallery.

Acknowledgements

• DC Boundary and DC Ward Boundaries from Open Data DC.
• DC Detailed Ward Boundaries created using data from the DC Parks, National Parks, Wetlands, Waterbodies, Military Bases, and DC Ward Boundaries from Open Data DC.
• Grocery Store Locations created from Grocery Store Locations and Healthy Corner Stores data from Open Data DC.
• Human Geography Map sources: Esri, TomTom, Garmin, FAO, NOAA, USGS, OpenStreetMap contributors, and the GIS User Community
• Card image by nrd from Unsplash