Graduate Thesis Or Dissertation

 

Predictive locational modeling of late Pleistocene archaeological sites on the southern Oregon Coast using a Geographic Information System (GIS) Public Deposited

Downloadable Content

Download PDF
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/g158bm97q

Descriptions

Attribute NameValues
Creator
Abstract
  • The search for archaeological materials dating to 15,000 yr BP along the southern Oregon coast is a formidable task. Using ethnographic, theoretical, and archaeological data, landscape resources which would have influenced land-use and occupation location decisions in the past are highlighted. Additionally, environmental data pertaining to the late Pleistocene is examined to determine what landscape features may have been used by human groups 15,000 years ago and to determine how these landscape features may have changed since that time. These landscape resource features are included in the modeling project as independent variables. The dependent variable in this modeling project is relative probability that an area will contain archaeological materials dating to the time period of interest. Two predictive locational models are created to facilitate the search process. These models mathematically combine the independent variables using two separate approaches. The hierarchical decision rule model approach assumes that decision makers in the past would have viewed landscape features sequentially rather than simultaneously. The additive, or weighted-value, approach assumes that a number of conditional preference aspects were evaluated simultaneously and that different environmental variables had varying amounts of influence on the locational choices of prehistoric peoples. Integration of the data and mathematical model structures into a Geographic Information System (GIS) allows for spatial analysis of the landscape and the prediction of locations most likely to contain evidence of human activity dating to 15,000 years ago. The process involved with variable integration into the GIS is delineated and results of the modeling procedures are presented in spatial, map-based formats.
License
Resource Type
Date Available
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Non-Academic Affiliation
Subject
Rights Statement
Publisher
Peer Reviewed
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome, 256 Grayscale) using Capture Perfect 3.0.82 on a Canon DR-9080C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces

Relationships

Parents:

This work has no parents.

In Collection:

Items