Deep Learning Reveals Extent of Archaic Native American Shell-Ring Building Practices

In the mid-Holocene (5000 - 3000 cal B.P.), Native American groups constructed shell rings, a type of circular midden feature, in coastal areas of the American Southeast. These deposits provide important insights into Native American socioeconomic organization but are also quite rare: only about 50 such rings have been documented to date. Recent work using automated LiDAR analysis demonstrates that many more shell rings likely exist than are currently recorded in state archaeological databases. Here, we use deep learning, a form of machine intelligence, to detect shell ring deposits and identify their geographic range in LiDAR data from South Carolina. We corroborate our results using synthetic aperture radar (SAR), multispectral data, and a random forest analysis. We conclude that a greater number of shell rings exist which expand further north than currently documented, suggesting a more widespread and common practice of ring-type midden building in this area during the mid-Holocene.

Citation

Davis, Dylan; Caspari, Gino; Carl Lipo, ; Matthew Sanger, (2021). Deep Learning Reveals Extent of Archaic Native American Shell-Ring Building Practices [Data set]. Scholarsphere. https://doi.org/10.26207/ry6k-q463

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Work Title Deep Learning Reveals Extent of Archaic Native American Shell-Ring Building Practices
Access
Open Access
Creators
  1. Dylan Davis
  2. Gino Caspari
  3. Carl Lipo
  4. Matthew Sanger
Keyword
  1. deep learning
  2. Settlement patterns
  3. shell rings
  4. object detection
  5. Southeastern United States
License CC BY 4.0 (Attribution)
Work Type Dataset
Publication Date 2021
DOI doi:10.26207/ry6k-q463
Geographic Area
  1. North America
  2. South Carolina
Deposited February 15, 2021

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Version 1
published

  • Created
  • Added Creator Dylan Davis
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  • Added SC_RF_S12-0000000000-0000006400.tif.zip
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    Publication Date
    • 2021
    License
    • https://creativecommons.org/licenses/by/4.0/
  • Added Georgetown_SC_LIDAR.zip
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  • Added Creator Gino Caspari
  • Added Creator Carl Lipo
  • Added Creator Matthew Sanger
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