grand-canyon-geology

Geologic map of the Grand Canyon and vicinity

http://rclark.github.io/grand-canyon-geology/

This map represents a spectacular set of data generated by George Billingsley and others at the USGS. The geologic data aggregated here was pulled from the following USGS publications:

• Geologic map of the Mount Trumbull 30 x 60 quadrangle
• Geologic map of the Grand Canyon 30' x 60' quadrangle
• Geologic map of the Valle 30' x 60' quadrangle
• Geologic Map of the Cameron 30' x 60' Quadrangle
• Geologic Map of the Peach Springs 30' x 60' Quadrangle
• Geologic map of the Tuba City 30' x 60' quadrangle

"I just hiked my ass off in the canyon gathering the field data."

George Billingsley, 2013

Compiled data

unit-definitions.csv: A table of unit names and descriptions for each unit depicted on the map. This file is included in the Git repository, and pull requests are welcome if you have suggestions for improvement!

geopolys.geojson: GeoJSON representation of the polygons that represent various geologic units on the map. This is a ~400MB file, too big for distribution via Git, so it is not included in this repository.

geolines.geojson: GeoJSON representation of the lines that represent contacts and faults on the map. This is a ~260MB file, too big for distribution via Git, so it is not included in this repository.

Getting the data

I'm happy to share the GeoJSON files. You can download them by running a script in this repository. You can do whatever you'd like to do with them.

You can get the data files from the following URLs:

https://grand-canyon-geology.s3.amazonaws.com/geopolys.geojson
https://grand-canyon-geology.s3.amazonaws.com/geolines.geojson

To download them for use in this repo, you must already have Node.js installed. The script will download the data files into the data folder in your local clone of the repository.

❯ git clone https://github.com/rclark/grand-canyon-geology
❯ cd grand-canyon-geology
❯ npm ci
❯ npm run get-data

Suggestions?

I've made some rudimentary attempts to homogenize and clean up the datasets produced by the above publications. These compiled data are all available for free.

These data could be better! I welcome advice / suggestions in the issue tracker. Generally, I'm not willing to adjust the locations of contacts or faults, but I am very willing to accept advice for better unit descriptions or correlation of units across publication boundaries.