Find EPA walkability values for pre-geocoded addresses

Start with an address-to-GEOID lookup

Keep addresses and GEOIDs as character vectors. In particular, a GEOID must not be converted to a number because leading zeroes are meaningful.

addresses <- dplyr::tibble(
  address_id = c("address_1", "address_2", "address_3"),
  address = c(
    "Pre-geocoded address in Baltimore County, MD",
    "Pre-geocoded address in Baltimore County, MD",
    "Pre-geocoded address in Baltimore City, MD"
  ),
  geoid = c("240054519002", "240054026041", "245102303002")
)

addresses
#> # A tibble: 3 × 3
#>   address_id address                                      geoid       
#>   <chr>      <chr>                                        <chr>       
#> 1 address_1  Pre-geocoded address in Baltimore County, MD 240054519002
#> 2 address_2  Pre-geocoded address in Baltimore County, MD 240054026041
#> 3 address_3  Pre-geocoded address in Baltimore City, MD   245102303002

The GEOIDs in this example are Census 2010 block-group identifiers, which is the geography used by the EPA layer queried by acti_epa_walkability(). When a source instead provides state, county, tract, and block identifiers, acti_fips12() can construct the block-group GEOID:

acti_fips12(state = 24, county = 510, tract = 60400, block = 2002)
#> [1] "245100604002"

Query the EPA layer

Pass the unique GEOIDs to acti_epa_walkability(). Setting geometry = FALSE keeps the request small when only the index attributes are needed. This call uses the live EPA ArcGIS service, so it is left unevaluated when the vignette is built.

walkability <- acti_epa_walkability(
  unique(addresses$geoid),
  geometry = FALSE
)

walkability

The returned data include GEOID10, NatWalkInd, and, when the index is available, cat_walk_index. cat_walk_index is a four-level categorization created from the EPA national walkability index breaks. The EPA service may also return other layer attributes.

Attach values back to addresses

Join on the two character GEOID fields. Keeping all address rows retains multiple addresses within the same block group.

address_walkability <- dplyr::left_join(
  addresses,
  walkability,
  by = c("geoid" = "GEOID10")
)

dplyr::select(
  address_walkability,
  address_id, address, geoid, NatWalkInd, cat_walk_index
)

Geocoding is a separate step and Census vintage matters

This package deliberately consumes GEOIDs rather than geocoding street addresses. Prepare and quality-check the address-to-GEOID crosswalk upstream, then use the workflow above. For projects that need a Census-geocoder client, censusxy is one option: it calls the U.S. Census Bureau Geocoding Tools and is designed to batch unique addresses. Its repository notes that it is no longer under active development as of early 2025, so check its current status and validate matches before using it in a production workflow.

censusxy does not return columns named GEOID10 or GEOID20. With return = "geographies", it returns Census geography components such as cxy_state_id, cxy_county_id, cxy_tract_id, and cxy_block_id; its vintage argument determines the Census geography vintage. A block-group GEOID can then be constructed from those components with acti_fips12(). Do not run the following code as part of this package’s workflow: it is an illustration of a possible upstream geocoding step and requires censusxy.

geocoded <- censusxy::cxy_geocode(
  address_data,
  street = "street",
  city = "city",
  state = "state",
  zip = "zip",
  return = "geographies",
  vintage = "Census2010_Current"
)

geocoded$geoid <- acti_fips12(
  geocoded$cxy_state_id,
  geocoded$cxy_county_id,
  geocoded$cxy_tract_id,
  geocoded$cxy_block_id
)

Here, the 10 and 20 suffixes mean Census boundary vintage, not GEOID length: both a 2010 and a 2020 block-group identifier contain 12 digits. The EPA Walkability Index layer is based on Census 2010 block groups, and this package intentionally queries and joins its non-null, 12-character GEOID10 field. The same layer also exposes a nullable GEOID20 field, but its alias describes a “Census block group 12-digit FIPS code (2018)” and its declared length is 50. Those contradictory labels do not establish a reliable Census 2020 key. Consequently, GEOID20 is not used by this package. The Census Geocoder currently offers the Census2010_Current geography vintage for its current benchmark; otherwise, a 2020-vintage result should be converted with an appropriate Census crosswalk before it is joined to this EPA release. Never treat similarly shaped 12-digit identifiers from different vintages as interchangeable.

Other approaches include calling the Census Geocoder API directly, using a local or commercial geocoder, or obtaining GEOIDs from a trusted data provider. Regardless of the method, confirm that the result is a 12-character Census 2010 block-group GEOID before passing it to acti_epa_walkability().

Requesting other EPA attributes or a study area

The EPA service exposes more than the overall NatWalkInd score. Of particular interest are the four inputs used to create it: D2A_EPHHM (employment and household density), D2B_E8MIXA (employment and household mix), D3b (street-intersection density), and D4a (distance to the nearest transit stop). The matching *_Ranked fields provide their national ranks. Population, household, worker, land-area, and metropolitan-area fields are also useful for describing or screening the returned block groups.

All arcgislayers::arc_select() arguments can be passed through acti_epa_walkability(). For example, use fields to limit the attributes downloaded, or filter_geom and predicate to select block groups that intersect a study-area geometry. Do not call acti_epa_walkability(NULL) without a spatial filter: it requests the entire national layer.

study_area_walkability <- acti_epa_walkability(
  geoid = NULL,
  geometry = FALSE,
  filter_geom = study_area,
  predicate = "intersects",
  fields = c("GEOID10", "NatWalkInd", "D2A_EPHHM", "D2B_E8MIXA", "D3b", "D4a")
)