j40-cejst-2/data/data-pipeline/data_pipeline/etl/sources/dot_travel_composite
Matt Bowen 876655d2b2
Add tests for all non-census sources (#1899)
* Refactor CDC life-expectancy (1554)

* Update to new tract list (#1554)

* Adjust for tests (#1848)

* Add tests for cdc_places (#1848)

* Add EJScreen tests (#1848)

* Add tests for HUD housing (#1848)

* Add tests for GeoCorr (#1848)

* Add persistent poverty tests (#1848)

* Update for sources without zips, for new validation (#1848)

* Update tests for new multi-CSV but (#1848)

Lucas updated the CDC life expectancy data to handle a bug where two
states are missing from the US Overall download. Since virtually none of
our other ETL classes download multiple CSVs directly like this, it
required a pretty invasive new mocking strategy.

* Add basic tests for nature deprived (#1848)

* Add wildfire tests (#1848)

* Add flood risk tests (#1848)

* Add DOT travel tests (#1848)

* Add historic redlining tests (#1848)

* Add tests for ME and WI (#1848)

* Update now that validation exists (#1848)

* Adjust for validation (#1848)

* Add health insurance back to cdc places (#1848)

Ooops

* Update tests with new field (#1848)

* Test for blank tract removal (#1848)

* Add tracts for clipping behavior

* Test clipping and zfill behavior (#1848)

* Fix bad test assumption (#1848)

* Simplify class, add test for tract padding (#1848)

* Fix percentage inversion, update tests (#1848)

Looking through the transformations, I noticed that we were subtracting
a percentage that is usually between 0-100 from 1 instead of 100, and so
were endind up with some surprising results. Confirmed with lucasmbrown-usds

* Add note about first street data (#1848)
2022-09-19 15:17:00 -04:00
..
__init__.py Adding DOT composite to travel score (#1820) 2022-08-16 14:44:39 -04:00
etl.py Add tests for all non-census sources (#1899) 2022-09-19 15:17:00 -04:00
README.md Adding DOT composite to travel score (#1820) 2022-08-16 14:44:39 -04:00

DOT travel barriers

The below description is taken from DOT directly:

Consistent with OMBs Interim Guidance for the Justice40 Initiative, DOTs interim definition of DACs includes (a) certain qualifying census tracts, (b) any Tribal land, or (c) any territory or possession of the United States. DOT has provided a mapping tool to assist applicants in identifying whether a project is located in a Disadvantaged Community, available at Transportation Disadvantaged Census Tracts (arcgis.com). A shapefile of the geospatial data is available Transportation Disadvantaged Census Tracts shapefile (version 2 .0, posted 5/10/22).

The DOT interim definition for DACs was developed by an internal and external collaborative research process (see recordings from November 2021 public meetings). It includes data for 22 indicators collected at the census tract level and grouped into six (6) categories of transportation disadvantage. The numbers in parenthesis show how many indicators fall in that category:

  • Transportation access disadvantage identifies communities and places that spend more, and take longer, to get where they need to go. (4)
  • Health disadvantage identifies communities based on variables associated with adverse health outcomes, disability, as well as environmental exposures. (3)
  • Environmental disadvantage identifies communities with disproportionately high levels of certain air pollutants and high potential presence of lead-based paint in housing units. (6)
  • Economic disadvantage identifies areas and populations with high poverty, low wealth, lack of local jobs, low homeownership, low educational attainment, and high inequality. (7) Resilience disadvantage identifies communities vulnerable to hazards caused by climate change. (1)
  • Equity disadvantage identifies communities with a with a high percentile of persons (age 5+) who speak English "less than well." (1)

The CEJST uses only Transportation Access Disadvantage.