Date of Award

Spring 2020

Degree Type

Masters Thesis

Degree Name

Master of Arts (MA)

School

Social Science and Global Studies

Committee Chair

Marie Danforth

Committee Chair School

Social Science and Global Studies

Committee Member 2

B. Katie Smith

Committee Member 2 School

Social Science and Global Studies

Committee Member 3

Bridget Hayden

Committee Member 3 School

Social Science and Global Studies

Abstract

Methods in biological anthropology have made tremendous leaps in recent years and with the increasing rise in technology there is no reason to suspect that this trend will be decreasing. Particularly methods in 3D digitization have not only increased but have also become more accessible in bioarchaeology. One method, photogrammetry, offers bioarcheologists a unique opportunity to easily collect and process cranial metric and non-metric data that can be used to quantify biological relatedness. While these advances are expected to continue, it is ignorant to assume that they represent a fail proof solution. A critical examination is necessary to quantify the accuracy of these techniques in comparison to traditional methodologies. Data on 24 metric and 25 non-metric traits was collected from the physical and digitized crania of 27 individuals to determine the accuracy, precision, and level of identifiability of these traits on photogrammetric models. Percent error, standard deviation, and average level of identifiability was calculated to determine the reliability of photogrammetry in biodistance research. All percent error rates, with the exception of inter orbital breadth, fell beneath an accepted 2% margin, in addition the standard deviation of digital measurements was less than that of physical measurements. However, a number of environmental and technical factors, most notably lighting and processing power, influenced the success of photogrammetric models. Photogrammetry offers bioarchaeologists a new way to collect data while simultaneously increasing collection access and preserving remains for future generations of researchers.

ORCID ID

0000-0002-0077-6373

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