Migrate

DeGAUSS is evolving: we are moving from one separately maintained image per task to the actively developed addr and geomarker R packages and toolchains.

Existing DeGAUSS images and their versioned tags will remain available for reproducibility; previously published versions of images will not be changed. Over time, new maintenance releases for each DeGAUSS image will print a short transition notice when run to direct users to the image-specific section on this page:

NOTICE: This DeGAUSS image is in maintenance mode.

Future development has moved to the addr and geomarker packages and containers.
The current command will continue to run, but consider migrating for new projects:

https://degauss.org/migrate/geocoder

DeGAUSS images in maintenance mode will remain available for existing and reproducible workflows and may receive critical correctness or security fixes, but will not receive new features or routine method/data updates.

geocoder

addr was designed to perform geocoding using a method of street-range based interpolation very similarly to DeGAUSS. Read more details about the geocoding procedure and results at: https://geomarker.io/addr/reference/geocode.html The container designed around addr for this specific workflow (addr_geocoder) also takes an input file (CSV or parquet) with an address column, and returns geocoded coordinates and information about match quality and precision.

DeGAUSS command:

docker run --rm -v $PWD:/tmp ghcr.io/degauss-org/geocoder:3.4.1 my_address_file.csv

equivalent addr command:

docker run --rm -v "$PWD:/tmp" ghcr.io/geomarker-io/addr_geocoder:v2.0.0-taf-v2-2025 \
  --input /tmp/my_address_file.csv

Geocoding with the addr tools cleans address text by default and parses address components using the usaddress library. Geocoding with detailed options for cleaning address text, parsing address components, and matching address components are available directly in R using the geocode() function.