The use of rapid digital documentation technologies remains in its infancy, although it promises to change the course of future archaeological work. With rising sea levels, the natural deterioration of historic sites and structures, and the lack of proper funding for historic and cultural sites, more of these sites are at risk of destruction. With the implementation of rapid digital documentation methods, researchers can address risks associated with data loss. To date, only a handful of cultural resource management (CRM) firms use these technologies, citing the lack of use as too expensive or difficult to learn. Using rapid digital documentation methods including, three-dimensional (henceforth 3D) modeling, photogrammetry, Geospatial Information Systems (GIS), and HABS/HAER documentation, this project assessed the overall utility of rapid digital documentation in supporting cultural heritage work. This research also explored a new method for HABS/HAER creation that cuts fieldwork time down to two to three days at the most. This research proved that these rapid digital documentation technologies could be helpful to federal agencies, CRM firms, and low-budget archaeological investigations. This project also compared two software used for photogrammetry, Agisoft Metashape and Meshroom, at the site to see the cost/benefit of conducting both methods of 3D modeling on an archaeological and historic site. This comparison determined that Metashape was the better program and worth the expense. This research was illuminated through a case study of the Juniper Springs Recreation Area within the Ocala National Forest and focused on applying these rapid digital documentation methods on a Civilian Conservation Corps (CCC) site prime for a National Register of Historic Places (NRHP) nomination.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2790 |
| Date | 15 August 2023 |
| Creators | Nalewaik, Alexander |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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