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Integrated Approach to Investigating Historic Cemeteries
Remote Sensing (2020)
  • Christine Downs, University of South Florida
  • Jaime Rogers, University of South Florida
  • Lori Collins, University of South Florida
  • Travis Doering
Ground-penetrating radar (GPR) and terrestrial laser scanning (TLS) surveys were conducted at a historic cemetery at Cape Canaveral Air Force Station, Florida, U.S., in order to confirm the presence of burials corresponding to grave markers and detect potential unmarked burials. Noise in the GPR data from surface features and subtle terrain differences must be addressed to determine the extent of anomalies of interest. We use singular value decomposition (SVD) to isolate and remove energy from GPR data. SVD allows one to remove unwanted signals that traditional processing techniques cannot. With SVD filtering, we resolve an anomaly adjacent to confirmed burials otherwise overprinted by unwanted signal. The migration of SVD-filtered data produces more distinct, spatially constrained point reflectors. Ground elevation is derived from georeferenced TLS data and compared to that from airborne laser scanning (ALS) to highlight subtle terrain that can assist data interpretation. TLS elevations show a subtle modern mound over the burial plot where ALS elevations show a depression. The targets of interest are approximately 20–30 cm higher in elevation if a topographic correction is performed using TLS versus ALS. In archaeological applications, a notable change is often recorded at the sub-meter scale. The combined approach presented here better resolves geophysical response of buried features and their positions in the ground relative to each other.
  • ground-penetrating radar; terrestrial laser scanning; digital elevation models; cemeteries; topographic correction; singular value decomposition
Publication Date
August 20, 2020
Citation Information
Christine Downs, Jaime Rogers, Lori Collins and Travis Doering. "Integrated Approach to Investigating Historic Cemeteries" Remote Sensing Vol. 12 Iss. 17 (2020) ISSN: 2072-4292
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