Abstract

The Indigenous people of Florida terraformed the region's relatively flat landscape into monumental vantage points for residence, burial, and displays of regional power. Known as mound structures today, these long-abandoned sites are now obscured by dense vegetation and thick tree canopies making their rediscovery difficult. Using Light Detection and Ranging (LiDAR) technology these lost sites can be located remotely for protection and study. In this research, LiDAR is used to locate Indigenous mound sites along the St. Johns River within the Ocala National Forest. Using free an open source geographic information systems (GIS) and similar software, LiDAR point cloud data is processed and visualized into digital elevation models (DEMs). This supports manual feature extraction (MFE) in service of locating potential sites. MFE is the identification of features by visual interpretation (Quintas et. al. 2017:364). This form of desktop survey reduces physical labor requirements with traditional methods of site location (e.g., field survey) by providing exact location data of possible sites prior to fieldwork. The central purpose of this project is the identification of Indigenous mound sites within the project study area for the purposes of identification, verification, and protection. This includes identifying previously unrecorded and documented sites in order to validate the usefulness of manual feature extraction of potential features and sites from LiDAR data within the densely vegetative area of interest. The project successfully identified two previously unknown sites and provided critical information for updating information associated with an additional four known mound sites. All data contributed to new or updated archaeological records with the Florida Master Site File and the US Forest Service database. This research took place during 2020 and 2021, and all University of Central Florida and federal policies and guidelines associated with COVID were followed.

Notes

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Graduation Date

2021

Semester

Fall

Advisor

Gonzalez-Tennant, Edward

Degree

Master of Arts (M.A.)

College

College of Sciences

Department

Anthropology

Degree Program

Anthropology

Format

application/pdf

Identifier

CFE0008811

Language

English

Release Date

December 2021

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

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