Abstract
In the late 19th century, explorers identified graffiti etched in stucco walls of residences, palaces, and temples in the Maya Lowlands. By the mid-20th century, scholars acknowledged that the ancient Maya produced these incised images. Today, archaeologists struggle with documenting these instances of graffiti with precision and accuracy, often relying solely on to-scale line drawings to best represent the graffitied image they see before them. These images can be complex, multilayered, and difficult to see so identifying the sequence of creation of the incisions can be challenging. Reflectance Transformation Imaging (RTI) is a method that uses a moving light source and photography in order to visualize, interact with, and analyze a three-dimensional object in a two-dimensional image. Performed on a series of 20 unique graffiti from the Maya archaeological site of Holtun, RTI showed promise as a viable technique for documenting and preserving graffiti as cultural heritage and for providing new information about an enigmatic aspect of Maya archaeology. Additionally, RTI is compared to other common methods used to document incised graffiti in the Maya lowland area including to-scale line drawing, tracing, photogrammetry, and scanning to show the new and unique information and data that can be gathered from this method. Finally, RTI is a low-cost, low-maintenance alternative data-gathering method for highly remote archaeological projects where other technology is difficult to obtain and use in the field setting.
Notes
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Graduation Date
2018
Semester
Spring
Advisor
Kovacevich, Brigitte
Degree
Master of Arts (M.A.)
College
College of Sciences
Department
Anthropology
Degree Program
Anthropology
Format
application/pdf
Identifier
CFE0007005
URL
http://purl.fcla.edu/fcla/etd/CFE0007005
Language
English
Release Date
May 2018
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
STARS Citation
Gill, Rachel, "Reflectance Transformation Imaging: Documenting Graffiti in the Maya Lowlands" (2018). Electronic Theses and Dissertations. 5762.
https://stars.library.ucf.edu/etd/5762