GROUND-PENETRATING RADAR CHARACTERIZATION OF GRAVES AND THE CORRELATION OF GEOPHYSICAL SIGNATURES, SEDIMENT TYPE, AND AGE OF INTERMENT

Ground-Penetrating Radar (GPR) is an excellent method for non-invasively identifying stratigraphic discrepancies, and is an invaluable tool in archaeological prospecting for unmarked grave sites. To the Cultural Resource Management (CRM) field GPR is especially valuable in this sense for its efficiency, resolution, and repeatability. On many projects geophysical anomalies consistent with grave shafts are ground-truthed through mechanical stripping or hand excavation, however continued progress in the identification of grave shafts on GPR profiles is important. For this reason an independent research project was initiated to specifically address grave-related GPR issues. The assessment and comparison of grave shaft geophysical stratigraphy in multiple sedimentary environments was of paramount importance. Additionally, the question was raised regarding whether grave shaft geophysical signatures retain their characteristics through time, or become muted over the course of centuries. For example, would a researcher expect older graves to be harder to identify than younger graves in the same sediment type? Also, is a grave of any age unlikely to be identified in poorly stratified sediments? With these and other questions in mind multiple known cemeteries were surveyed with a cart-mounted 250 MHz GPR in Maine, Pennsylvania, and Delaware. Cemeteries on glacial, fluvial, and marine sediments were investigated. A GPS unit with sub-meter accuracy was employed to collect start and end points of GPR lines, and to mark the location and age of graves along each line. GPR line locations were chosen to maximize the range of grave ages along each line, and multiple lines were collected at each cemetery. The GPS points were loaded into ArcGIS and a high-resolution image of each GPR profile was georeferenced to its respective start and end points. With the points labeled it was possible to identify known grave locations and their ages with high precision. Preliminary results of a robust dataset will be presented.