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The Whistling Elk Subsurface Imaging Project

 

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This project represents one of the early successes of using multiple geophysical methods at an archaeological site to capitalize on the synergy of information from several sources. With funding from the National Center for Preservation Technology and Training, National Park Service (awarded in 1997), Dr. Kenneth L. Kvamme focused on the fortified prehistoric settlement of Whistling Elk (South Dakota) because of its excellent response to all geophysical methods tested in the summer of 1998.

Whistling Elk is a large prehistoric village (ca. AD 1300s) located on the north bank of the Missouri River in central South Dakota. The village is buried about one meter below the present surface, and little was known about it prior to this project.

The main goal of this project was to explore the potential of integrating several remote sensing data types collected over the same space using a variety of the latest GIS and image processing tools. Kvamme and his team used four different geophysical methods: electrical resistance, induced electrical conductivity, magnetometry, and ground-penetrating radar (GPR).   

The individual datasets show various details related to subsurface archaeological features, but when combined reveal a remarkably complete map-like image of the buried village remains including two fortification ditches with bastion loops and numerous houses distributed throughout their interiors. Data were combined in GIS and also through the innovative use of color compositing, where each layer is tinted a different primary color and, when added together portray all three layers in one image. The various geophysical layers provide important clues about the nature of these features including, in many instances, their depth and the presence or absence of burning.  These data provided key evidence supporting an idea that the village was attacked in prehistory!

The great success of this project inspired a larger effort led by Dr. Kvamme and co-PI Dr. W. Fredrick Limp, where the use of these and other remotely sensed data collected at four different archaeological sites were used to develop additional methods for integration and fusion of multi-sensor data (see Multi-Sensor Data Fusion for Historic Resource Identification).