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Using LiDAR and Relative Elevation Modeling (REM) to Identify and Analyze Archaeologically Sensitive Alluvial Landforms

Author(s): Shane Sparks ; Daniel Stratten ; Elder James Tait ; Crilly Ritz ; Grant Novak

Year: 2015

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Alluvial landforms are highly sensitive areas, with the potential to contain both surface exposed and buried archaeological deposits, but systematic analysis and identification of these landforms has proved problematic in the past. Although large alluvial terraces can be identified visually on topographic maps, high resolution LiDAR, and Digital Elevation Models; smaller, subtler terraces, and other complex alluvial landforms can be problematic due to stream gradient issues and resulting elevation differences along a stream alignment. On a recent project on the Lower Stillaguamish River in western Washington, we employed a new restoration and habitat modeling tool, relative elevation modeling (REM), to eliminate the gradient issue and enhance terrace rises through LiDAR slope analysis. The results have provided pronounced and enhanced visibility of subtle features, and show promise to providing adequate data to assign relative dating for sites associated with different terrace elevations on the same watercourse.

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Using LiDAR and Relative Elevation Modeling (REM) to Identify and Analyze Archaeologically Sensitive Alluvial Landforms. Shane Sparks, Elder James Tait, Daniel Stratten, Grant Novak, Crilly Ritz. Presented at The 80th Annual Meeting of the Society for American Archaeology, San Francisco, California. 2015 ( tDAR id: 397986)


Spatial Coverage

min long: -169.717; min lat: 42.553 ; max long: -122.607; max lat: 71.301 ;

Arizona State University The Andrew W. Mellon Foundation National Science Foundation National Endowment for the Humanities Society for American Archaeology Archaeological Institute of America