Keywords
GIS LiDAR Archaeology Looting Maya
Abstract
This research examines looting activity at archaeological sites in the Maya Biosphere Reserve in Petén, Guatemala, focusing on areas both inside and outside established national park boundaries. The study covers sites occupied by the ancestral Maya from the Middle Preclassic to Terminal Classic periods (800 BC – AD 900), including El Mirador, Nakbé, and Wakná. This research uses LiDAR data and GIS analyses to identify looting clusters, comparing areas within the park to those outside, and investigates the relationship between looting activity and infrastructure such as trails, camps, and fresh water reservoirs.
Findings reveal that looting is more concentrated outside the park, named the MiradorRio-Azul National Park, suggesting that its boundaries and protective measures have helped mitigate looting. The study also highlights significant associations between looting clusters and fresh water reservoirs (aguadas) as well as trails (senderos), while no strong link was found with known camps. This may indicate that looters avoid areas with a higher presence of other people such as guards, park rangers, and community members.
By identifying looting hotspots, this research contributes to efforts aimed at preserving at-risk archaeological sites, re-provenancing looted artifacts, and potentially predicting future looting activity. This project and its conclusions could enhance the management and protection of cultural heritage in the Maya lowlands, providing valuable insights for conservation strategies.
Completion Date
2024
Semester
Fall
Committee Chair
Callaghan, Michael
Degree
Master of Arts (M.A.)
College
College of Sciences
Department
Anthropology
Degree Program
Anthropology
Format
Identifier
DP0029034
Language
English
Release Date
12-15-2024
Access Status
Thesis
STARS Citation
Sherwood, Chloe E., "Using LiDAR Data and GIS Analyses to Understand Looting Patterns in the Maya Biosphere Reserve" (2024). Graduate Thesis and Dissertation post-2024. 68.
https://stars.library.ucf.edu/etd2024/68
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