Heidi Stucker
Intro to GIS
Prof. Barbara Parmenter
November 2013
Assignment 6
Multi-level Food Retail Opportunities:
Improving food access in Boston’s most underserved neighborhoods through
grocery store development, small food market improvements, and mobile
produce market stop expansion.
(Note: I may or may not include the components in grey.)
1) Project description:
My project focuses on identifying areas in Boston where there are geographic
impediments to residents accessing full service grocery stores. Looking at the
underserved areas, I explore the opportunities for three interventions to
improving healthy food options - grocery store development, small-mid size
food market improvement, and mobile produce market service expansion - that
require varying degrees of time and resources to implement, and have varying
degrees of impact.
Food deserts are typically defined by the lack of access to full service grocery
stores. For my project, I am also delineating underserved areas by their lack of
supermarkets, but rather than identify supermarket development as the sole
intervention to improving food options, I explore a range of interventions for
consideration for immediate, intermediate and longterm improvement to the
food environment.
Project Goal:
The goal of this project is to explore and identify various solutions to improving
food access in Boston’s most underserved neighborhoods.
Project Questions:
a) What areas in Boston have insufficient service by full service food markets?
b) Where are there opportunities for development of new markets in these
areas?
c) Where are there opportunities for improvement of existing markets in these
areas?
d) Where are there opportunities for immediate intervention by mobile
produce markets?
e) How might transportation services be improved to increase access to healthy
food outlets?
2) Literature:
Eckert, J., & Shetty, S. (2011). Food systems, planning and quantifying accesss: Using
GIS to plan for food retail. Applied Geography, 31, 1216-1223.
doi:10.1016/j.apgeog.2011.01.011
This article measures food accessibility in Toledo, Ohio by using data on a)
grocery stores and markets, b) resident addresses c) Census block outlines,
and d) Census 2000 demographic data (pertaining to poverty levels,
race/ethnicity, educational attainment, and automobile access). Access was
measured using 1) Network Analyst closest facility tool to calculate the
distance to from households to the nearest grocery store and then 2) an
equation to measure the average block group accessibility (sum of distances
between residential units and retailers / # of residential units = mean
distance to food retailers for block group). Results were 3) spatially joined to
the block group outlines to determine the average degree of access. The
block groups on average =>1 or =>2 miles from a grocery store was then
layered with demographic data to identify areas that may have or develop
accessibility issues.
While calculating an average measurement of food access for block groups is
useful in that it can be compared to Census demographic data, the average
seems imprecise. I might be interested in evaluating access using similar
measurements, but I am also interested in looking at more precise
measurement approaches. In thinking about my project, I’ve been interested
mostly in identifying opportunities to develop new or improve existing food
retail in areas of greatest need; inspired by the suggestions in this article
about improving transportation systems (car sharing, taxi vouchers), I will
also consider how I can evaluate opportunities to improve transportation
options.
Cui, C., Wang, J., Pu, W., Ma, J., and Chen, G., (2012). GIS-based method of delimiting
trade area for retail chains. International Journal of Geographical Information
Science 26, 1863-1879. http://dx.doi.org/10.1080/13658816.2012.661058
Wang, et. al. present a very precise method of delimiting a retail trade area the “spatial extent around a store (a contiguous area or polygon) that
contains the majority of the customers or potential
customers…(2012),” – that measures elements including stores,
customer location, street network, as well as travel time,
transportation mode, traffic lights, road grade and traffic rules. The
article reviews a number of methods by other researchers used to
delineate trade area that give cruder, general results and most often
use the Euclidean distance as a measure.
I was particularly interested in the article’s methods of including both
pedestrian an auto measurements and delineation of trade area using
travel time, not distance. While I am not interested in delineating trade
areas of existing food retail using the complex methods (stop light
timing, street grade) presented in this paper, it will be helpful in
thinking through measuring trade areas using travel time for cars and
people on foot.
Roig-Tierno, N., Baviera-Puig, A., Buitrago-Vera, J., and Mas-Verdu, F. (2013). The
retail site location decision process using GIS and the analytical hierarchy
process. Applied Geography, 50, 191-198.
http://dx.doi.org/10.1016/j.apgeog.2013.03.005
This article takes a multi-step approach to identifying the best site for
development of new retail. Tierno, et. al. first suggest a multi-step process to
identifying various sites, then suggest a list of criteria to determine the best
site. The first and second steps evaluate geodemand (measuring the number
and concentration of residents on a city block level) and geocompetition (the
extent to which other stores already capture the market). The third step
combines geodemand and geocompetition layers (via kernel density), to
measure potential sites. Then subjective criteria (determined through
surveys by industry professionals) is used to determine which of the
potential sites is the best site for development.
Some of the methods presented in this article will be helpful for my project.
For example, the article presents a different way of determining the trade
area (that evaluates a ratio of sales floor square footage : travel distance),
and it combines data layers using kernel density, something I’m interested in
considering. Something I find interesting about the method for measuring
geodemand, however, is that this is a measurement of population density, but
does not evaluate income.
ArLand Land Use Economics (2008). Elyria-Swansea Grocery Store Market Analysis.
Retrieved from http://www.denvergov.org/Portals/646/documents
/Elyria_SwanseaGroceryMarketStudy.PDF.
This report presents a grocery store market analysis for a neighborhood in
Denver, Colorado. The report includes analysis of potential development
within a particular trade area, market demand (derived from current and
projected populations), desirable characteristics for grocery stores,
competition from other stores, and possible sites for grocery store
development.
This will be a valuable report to reference for my project, especially with
regard to tracking the anticipated change over time (population/income
projections) and measuring grocery store demand (the report uses an
equation for measuring the percentage of income spent at grocery stores).
Also, while some of the methods used in other articles I’ve referenced here
are far too complex for the scope of this project and beyond my GIS abilities,
the methods laid out in this report’s analysis are comprehensive, logical and
within the scope of what I might consider for my project.
Trust, The Food. (2010). Food for Every Child: The Need for More Supermarkets in
Philadelphia. Retrieved from http://www.mphaweb.org/documents/
FoodforEveryChild_Massachusetts.pdf
This report by The Food Trust identifies areas in Massachusetts and Boston
that are in need of improved healthy food options. The report produces data
layers on income, health and food access using kernel density, then combines
the layers to identify the areas that are the lowest-income, with the highest
rates of diet-related illnesses and the furthest from supermarket trade areas.
This report inspired my GIS project, and while I intended on building upon
the findings by evaluating healthy food retail opportunities in the areas
identified in this report as most underserved and in greatest need of
intervention, I am instead intending on using my own methods to identify
areas of greatest need. The reason for doing my own analysis is two-fold: 1)
the Census data used in the report was from 2000 – I intend to use Census
data from 2010, and 2) the report uses diet-related deaths as a part of
identifying areas of great need – while there is a measured correlation
between presence of supermarkets and improved health, I think it’s a stretch
to use diet-related deaths as a way to justify improved healthy food options.
Other helpful non-GIS literature:
Sideoff, D. (2012) Getting to Grocery: Tools for Attracting Healthy Food Retail to
Underserved Neighborhoods. ChangeLab Solutions. Retrieved from
http://changelabsolutions.org/sites/default/files/documents/Getting_to_Gr
ocery_FINAL_20120514.pdf.
Treuhaft, S., & Karpyn, A. (2010) The Grocery Gap: Who Has Access to Healthy Food
and Why it Matters. Policy Link & The Food Trust. Retrieved from
http://thefoodtrust.org/uploads/media_items/grocerygap.original.pdf
USDA (2009) The Economics of Supermarket and Grocery Store Location. In Ver
Ploeg. et. al. (Eds.), Access to Affordable and Nutritous Food – Measuring and
Understanding Food Deserts and Their Consequences: Report to Congress.
(83-90).
3) Data layers: (Data Set name, description, data source agency, URL-if applicable, and
key attributes you will use)
Determining areas with insufficient service by full service food markets:
Grocery Stores Table:
Description: Grocery stores using NAICS code 445110
Data Source Agency: Reference USA
URL: https://www.referenceusa.com/
Key attributes: square footage, revenue, number of employees (all
potential proxies for full service grocery store)
Census2010TIGERROADS_ARC
Description: Streets and roads shapefile
Data Source Agency: MassGIS
Key attributes: Figure out how to get mph for street segments. I will
calculate length and identify walk time and drive time for each
segment
OR
EOTROADS_ARC
Description: Streets and roads shapefile
Data Source Agency: MassGIS
Key attributes: Includes “class” for all street and road segments, and
“speed limit” for some segments. Interested in deriving speed limit for
all street segments, and considering how I might do this referring to
the street segment “class” number.
OpenSpace_Poly
Description: Open space and parks shapefile
Data Source Agency: MassGIS
Key attributes: use open space boundaries as borders of trade areas
where applicable
Hydro25K_Poly
Description: hydrographic features shapefile
Data Source Agency: MassGIS
Key attributes: use open space boundaries as borders of trade areas
where applicable
(MBTABUSROUTES_ARC)
Description: Bus routes
Data Source Agency: MassGIS
Key attributes: Yet undecided if I’ll use this data layer. Interested in
exploring measuring travel time with buses to grocery stores to
delineate trade area. Will inquire about how feasible this is.
(MBTABUSSTOPS_PT)
Description: Bus stops
Data Source Agency: MassGIS
Key attributes: Yet undecided if I’ll use this data layer. Interested in
exploring measuring travel time with buses to grocery stores to
delineate trade area. Will inquire about how feasible this is.
Determining potential areas for development of new full service food markets
In areas with limited access, measure grocery demand
Census2010BlockGroups_Poly:
Description: Block Group shapefile
Data Source Agency: MassGIS
Key attributes: will reduce the block groups used to the areas with
limited access to full service food markets.
Household Units:
Description: Household Units Table
Data Source Agency: American Fact Finder, Census 2010
URL: http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml
Key attributes: narrowed to area with limited access
Average Household Income:
Description: Average Household Income Table
Data Source Agency: American Fact Finder, Census 2010
URL: http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml
Key attributes: narrowed to area with limited access
In areas with limited access, identify potential locations for grocery development
BUILDINGFP_POLY
Description: footprint of buildings more than 150 square feet in
Boston Metro area
Data Source Agency: MassGIS
Key attributes: Will add field to attribute table measuring square
footage of buildings.
FY09_Parcel_Join
Description: Boston Parcel Shapefile
Data Source: Boston Assessor
Key attributes: street address, owner, land use (commercial), parcel
type (324 = supermarkets)
Determining opportunities for improving existing markets
Small-Mid Size Market Table
Description: This will be a data set of small- to mid-size markets that
sell a limited range of grocery items. These will include convenience
stores that have a smaller square footage that typical grocery stores.
Data Source Agency: Reference USA
URL: https://www.referenceusa.com/
Key attributes: I’ll consider square footage, revenue and number of
employees and street proximity to determine which markets to
include/exclude.
Determining opportunities for expanding mobile produce market service
Mobile Produce Market Table
Description: This will be a data set of the stops made by Fresh Truck, a
mobile produce market in Boston. It will include location, service day
and service timeframe.
Data Source Agency: The Fresh Truck website
URL: http://thefreshtruck.org/
Key attributes: location, service days, service times
Determining opportunities for improving transportation to full service food markets.
Census2010TIGERROADS_ARC
Description: Streets and roads shapefile
Data Source Agency: MassGIS
Key attributes: Figure out how to get mph for street segments. I will
calculate length and identify walk time and drive time for each
segment.
OR
EOTROADS_ARC
Description: Streets and roads shapefile
Data Source Agency: MassGIS
Key attributes: Includes “class” for all street and road segments, and
“speed limit” for some segments. Interested in deriving speed limit for
all street segments, and considering how I might do this referring to
the street segment “class” number.
(MBTABUSROUTES_ARC)
Description: Bus routes
Data Source Agency: MassGIS
Key attributes: Yet undecided if I’ll use this data layer. Interested in
exploring measuring travel time with buses to grocery stores to
delineate trade area. Will inquire about how feasible this is.
(MBTABUSSTOPS_PT)
Description: Bus stops
Data Source Agency: MassGIS
Key attributes: Yet undecided if I’ll use this data layer. Interested in
exploring measuring travel time with buses to grocery stores to
delineate trade area. Will inquire about how feasible this is.
4) Data creation process, and/or analysis steps that you expect to perform
Determining areas with insufficient service by full service food markets
1. Grocery Store Table
a. Prepare data: decide which food markets to include and exclude based
on the Reference USA search for NAICS 445110 (supermarkets)
b. Geocode data
2. Project streets data (either Census2010TIGERROADS_ARC or
EOTROADS_ARC)
a. Using Network Analyst’s Service Area tool, identify walk time service
area for each supermarket
b. Using Network Analyst’s Service Area tool, identify drive time service
area for each supermarket
3. Project bus route and stops layers (MBTABUSROUTES_ARC and
MBTABUSSTOPS_PT)
a. Determine if it is feasible to identify bus ride time service area for
each supermarket
b. If feasible, use Network Analyst’s Service area tool to identify bus ride
service area.
Results should produce a map with three service areas for each supermarket
by walk time, drive time and bus ride time. The outermost boundaries will be
used to determine areas with sufficient grocery store service. The areas
outside of these rings will represent the areas with insufficient service by full
service food markets.
Determining potential areas for development of new full service food markets
Measure grocery demand
1. Download Household Unit data for Boston, block group level
a. Derive the household unit count within limited service area
2. Download Household Income data for Boston, block group level
a. Derive the average household income within limited service area
3. Determine Aggregate Income for Boston, block group level
a. Multiply household units by average household income for limited
service area
4. Download Consumer Expenditure Survey data
a. Identify Boston-specific or national average percentage of income
spent on food at home
b. Multiply food at home percentage by aggregate Income to derive food
spending total estimate for limited service area
5. Identify percentage of food at home spending that might be captured by
development of a new market (Peg Barringer notes that it’s likely a new
market would capture about 60% of the total estimated spending.)
6. Determine how much square footage of grocery store space the limited
service area could support
a. Find data that estimates average grocery sales per square foot (Peg
Barringer notes that $400/$450 per square foot is a common
estimate.)
Identify potential locations for grocery development
7. Join FY09_Parcel_Join and BUILDINGFP_POLY
8. Using “Select by Attribute,” isolate commercial properties
9. Using “Select by Attribute,” isolate buildings that have a footprint square
footage equal to or less than the square footage the limited service area could
support
10. Using “Select by Attribute,” isolate the parcels that have a “Yr_Built” value of
“0”.
a. Compare the results to orthoimagery to verify these are vacant
parcels.
11. Review the results and determine which parcels and buildings might be
suitable for new grocery store development.
12. Calculate service area of these prospective grocery store sites based on the
criteria and formula used previously to determine service area for the
existing supermarkets
Results will be used to produce a map that shows the existing buildings or
vacant parcels that could accommodate grocery store development in the area
with limited grocery store service; each possible location will have an
accompanying, estimated trade area.
Determining opportunities for improving existing markets
1. Small-Mid Size Market Table
1) Decide which food markets to include and exclude based on the
Reference USA search. May want to include some of those markets
filtered from the original Grocery Stores Table (445110) and include
other food markets: convenience stores (445120), Fruit & Vegetable
Markets (445230), Meat Markets (445210), Fish & Seafood Markets
(445220), Food (Health) Supplement Stores (446191), and all other
specialty food stores (445299).
2) Filter results for the limited service area
3) Geocode data
4) Determine which markets are most promising for expanding and
improving their offerings to meet more of the food needs of the limited
service area. To do this, use market square footage, estimated sales
revenue and number of employees, street proximity.
Results will be used to display a map of existing food markets that would be
promising candidates for improvement and expansion efforts.
Determining opportunities for expanding mobile produce market service
2. Mobile Produce Market Table
1) Prepare data for The Fresh Truck
2) Geocode data
3) Looking at the current area of service by The Fresh Truck, and identify
opportunities to expand service in the area with limited full service food
outlets.
Results will be displayed in a map showing proposed sites for expanded
service by mobile produce markets.
Determining opportunities for improving transportation to full service food markets
3. MBTABUSROUTES_ARC and MBTABUSSTOPS_PT
1) If I am able to figure out bus ride time, I could identify where, along a
travel route there might be inefficiencies in the bus transit system, and
where there might be opportunities to develop interventions, such as
improved schedule notifications
5) The products you hope to include on your poster (maps, tables)
Maps:
1) Map of sufficient food retail area, showing existing supermarkets with
walk time trade area, drive time trade area and bus ride time trade area.
2) Map of limited food retail area, showing the polygons of the areas outside
of the sufficient food retail area.
3) Map showing buildings or vacant parcels in the limited food retail area
that could accommodate grocery store development, with respective,
estimated trade areas.
4) Map of existing food markets that would be promising candidates for
improvement and expansion efforts.
5) Map showing proposed sites for expanded service by mobile produce
markets.
Tables:
1) Grocery store demand in the area with limited food retail