Date of Award
May 2021
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Historic Preservation
Committee Member
Jon B Marcoux
Committee Member
Martha Zierden
Committee Member
Katherine Pemberton
Committee Member
Laurel Bartlett
Abstract
Some of colonial Charleston’s most significant landscapes are rural savannas. While it is often overlooked, the colonial cattle industry centered in South Carolina’s Lowcountry savannas played a large role in the early economy. Ultimately, the cattle trade provided many of the resources that made Charleston one of the wealthiest cities in colonial America. Today, the preservation of the physical landscapes associated with the cattle industry is more important than ever as issues like climate change and urban growth and development threaten to destroy these historic landscapes.
The purpose of this thesis is to test the applicability of modeling techniques as it relates to the historic cattle industry in colonial South Carolina and determine if modeling can accurately predict sites of colonial cattle grazing relating to the time period from 1670-1750. Using predictive modeling and GIS, this thesis analyzes the environmental criteria within a known area of colonial cattle grazing in order to create a predictive model. While the environmental data sets used to populate the model are from modern surveys, many environmental changes require long periods of time for drastic changes to occur; thus results of the model show the statewide distribution of ideal colonial cattle grazing habitat. Specific results of the model suggest that the most ideal habitat for cattle raising is concentrated along the coastal zone of South Carolina, predominantly in the Sea Islands and Santee Delta regions. This is largely due to the natural geomorphology of these regions and the abundance of proffered fodder for cattle.
Recommended Citation
Thomas, John Benjamen, "Colonial South Carolina Cowpens and Savannas: Analyzing the Distribution of Colonial Cattle Grazing Sites Using GIS and Predictive Modeling" (2021). All Theses. 3519.
https://tigerprints.clemson.edu/all_theses/3519