Date of Award

Spring 5-1-2006

Document Type

Thesis

Degree Name

Master of Arts (MA)

Department

Geography, Geology, and Anthropology

First Advisor

Jay D. Gatrell

Second Advisor

Steven K. Pontius

Third Advisor

Ryan R. Jensen

Abstract

The exploration of urban-environmental changes and how those transformations co-vary with observed socio-economic realities is currently a major research initiative in geography. To that end, this thesis develops an urban-environmental assessment regime that examines how environmental change co-varies with observed socio-economic conditions. Research has demonstrated existing linkages between observed conditions in regard to socio-economic status (SES) and a particular greenness index, as represented by, normal difference vegetation index (NDVI). However, a gap within the literature has been identified concerning the current methodologies that propose to predict SES using remotely sensed data. Therefore, this thesis addresses this gap within the related literature, providing a solution that can subsequently be generalized to urban systems distinct from the study area-Evansville, IN. Further, this project explores the observed relationship between socio-economics (e.g. race, class, and income) and observed urbanenvironmental change. Spatially-dependent socioeconomic differences within many cities are evident. However, not so clearly visible are the social inequities that co-vary with the urban forest and greenness more generally. This research examines the average amount of greenness present at the block group level. Statistical analysis is performed to determine the significance of covariance between NDVI and indicators of urban quality of life (UQL), namely, socioeconomic characteristics of the Evansville, IN study area. Geographically weighted regression (GWR) and ordinary least squares (OLS) regression are used to determine the significance of discovered covariance among population density, mean NDVI, minimum NDVI, standard deviation for NDVI, range of NDVI, and for an interaction term defined by the mean NDVI multiplied by the population density of each block group. Six socioeconomic variables are used as proxies for UQL. Finally, the thesis uses GIS to visualize the spatial dynamics of observed greenness and socio- economic covariance.

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