Date of Award

8-2012

Document Type

Thesis

Degree Name

Master of Engineering (ME)

Legacy Department

Environmental Engineering and Science

Advisor

Lee, Cindy

Committee Member

Brame , Scott

Committee Member

Ladner , David

Committee Member

Schlautman , Mark

Abstract

There have been many changes in land management policies of the National Forest system over the past 100 years. Changes in policy related to law, population growth and economics directly cause changes in land cover. Global land cover changes are occurring at such a pace and magnitude that they are affecting Earth system functioning (Lambin et al., 2001). The analysis of land cover changes plays a key role in understanding several environmental phenomena, resulting in a need for objective and comparable land cover maps (Gennaretti et al., 2011). Advances in remote sensing and Geographic Information Systems (GIS) have modernized land-use analysis but this technology has traditionally ignored historical black and white aerial photography (Kadmon & Harari-Kremer, 1998). The objectives of this thesis are to show that remote sensing and GIS can provide clear evidence of the consequences of major changes in land use polices using historical aerial images. The goal is to develop new techniques that will allow the use of these images and will widen the usefulness of GIS for environmental scientists interested in land cover change over the last 50-100 years. The research applies object base image analysis (OBIA) to four study sites that display physical evidence of different management strategies using the images collected over a 70 year time span. This project presents a semi-automatic object oriented method that will allow the analysis of landscape change by comparing historical aerial photographs with 2010 orthoimagery. The OBIA method provides many advantages over traditional classification methods by creating a standardized rule set that provides efficient segmentation, classification and creation of land cover maps for a large dataset of 29 diverse images.

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