Applied ML Systems · Capstone brief
DS-07 · Who can actually reach a grocery store?
Using road networks and transit, how different does access look when measured by travel time — and for whom does the answer change most?
The question
Food access is usually measured as straight-line distance to a supermarket. Using road networks and transit, how different does access look when measured by travel time — and for whom does the answer change most?
Data
USDA Food Access Research Atlas (https://www.ers.usda.gov/data-products/food-access-research-atlas/). OpenStreetMap road network and retail POIs (https://www.openstreetmap.org/). Census ACS vehicle availability and income (https://www.census.gov/data/developers/data-sets/acs-5year.html). GRTC GTFS for transit travel time (https://www.transit.land/feeds/f-grtc~va).
Expected failure modes
OSM retail tagging is inconsistent — dollar stores, corner stores, and full supermarkets are not reliably distinguished, and that distinction is the entire analysis. Straight-line and network distance diverge most exactly where rivers and highways are, which is where it matters. Transit travel time depends on time of day.
Done looks like
A comparison of straight-line, driving, and transit-based access for Richmond-area tracts, with the store classification rules written down, and a named set of tracts whose classification flips depending on method.
Five C's
CT: recognizing the measure defines the finding. CR: building a store classifier from inconsistent tags. CO: independent double-coding of a store sample to measure agreement. CM: a map a planner could use. CZ: "food desert" designations affect funding — the definition is a political object.
Mentor role
An urban planner, GIS analyst, or public-health professional reviews classification rules at Checkpoint 1 and the map at Checkpoint 2. School-supervised.
Rubric calibration
R1: compares methods rather than asserting one. R2: store coding rules documented and inter-rater agreement reported. R3: straight-line as the baseline method. R4: identifies where methods disagree, and why. R5: map is legible and honest about uncertainty. R6: addresses how the label affects real funding.
Two ways this goes wrong
(a) Every OSM node tagged shop=convenience counts as a
grocery store and half the food deserts disappear. (b) The student computes transit time
at 9am Tuesday only, and reports access that does not exist for a night-shift worker.
Source moved or something unclear? Send feedback on this brief. Mentors are advisory; the school supervises. These briefs do not produce verified computer-science credit.