Edward Henry
Colorado State University-Fort Collins, CO·Social Science
How did one of the earliest cities in what is now the United States grow so fast? Current models suggest that in little more than a century it drew many immigrants from across the Midcontinent and became the leading center in all of North America.
- Fields
Social Science
Earth & Environmental Science
- Topics
archaeology
urbanism
early cities
- Grants
- 1 known grant, through Aug 2027
What they work on
- Map the buried landscape of an early North American city across more than 5.5 square kilometers, using high-resolution magnetometry that detects buried features without excavation.
- Reconstruct the city's growth and organization by analyzing magnetometer data with GIS and geospatial methods, comparing it with early urban formation elsewhere in the world.
- Build a public digital atlas through the Digital Archaeological Record and a web portal, in consultation with Tribal Historic Preservation Officers who share stewardship of the data.
More about the research
It was the largest precolonial community in the US. Even after decades of fieldwork, basic facts about its growth and layout remain unclear. Answering these questions requires large-scale spatial data on the city's early development.
Why it matters
A complete underground map of this early city will show how Indigenous peoples formed the largest precolonial community in the US. It will also allow comparison with early cities worldwide. The data could guide planning and preservation at a site visited by about 250,000 people each year, and support tribal stewardship of their ancestral homeland.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Casey Barrier
Bryn Mawr College, PA·Social Science
Conduct a high-resolution magnetometry survey of more than 5.5 square kilometers of a precolonial Indigenous city to map buried features across nearly the entire site.
Aaron Maxwell
West Virginia University, WV·Earth & Environmental Science·Early-career
Develop convolutional neural network methods for semantic and instance segmentation to extract geomorphic features from LiDAR point clouds and terrain derivatives such as hillshades.
Daniel Miller Runfola
William & Mary, VA·Social Science
Automate processing of administrative boundary data for the geoBoundaries platform, including georeferencing printed maps from library archives so historical borders can be placed on modern coordinates.
The school
Colorado State University-Fort Collins: 23 labs on PI Pages, $466M a year on research, 276 research doctorates a year.
Reach out
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