Date of Completion

8-23-2016

Embargo Period

8-23-2016

Keywords

land use, agriculture, urban sprawl, social capital, farm preservation

Major Advisor

Dr. Jeffrey Osleeb

Associate Advisor

Dr. Ken Foote

Associate Advisor

Dr. Carol Atkinson-Palombo

Field of Study

Geography

Degree

Doctor of Philosophy

Open Access

Open Access

Abstract

Urbanization is a complex process of converting urban fringe and rural land to urban land uses and has caused various impacts on ecosystem structure, function, and dynamics. Estimates of the agricultural land converted annually to low density non-agricultural uses vary from between 800,000 to more than 3 million acres nationwide—a rate of five times the rate of population growth, and in the process, fragmented the agricultural land base. Much of the land lost is prime or unique farmland, disproportionately located near cities. Classical land use theory asserts that a study of market forces and land value, defined in terms of inherent productivity and/or distance from urban centers, can explain this change.

This study is important in advancing geographic research on land use change in urban fringe areas, methodologically and theoretically. Data utilized were parcel-scale and remotely-sensed spatial data for a complete Michigan county in an attempt to better test the effects of economic and non-economic factors on land use change in a statistical model. An initial pilot study helped identify potential factor relationships in the research.

The research presented makes several advances over previous land use studies by combining several methods for modeling land use change. First, it uses non-economic variables based on land attachment and social capital, as well as traditional economic variables to explain

land use change. Second, it develops a continuous parcel data set using existing ownership records. This better represents the decision-making unit at farm scale with respect to farm retention. Third, it combines modeling techniques, including ordinary least squares Geographic Weighted Regression (GWR), to analyze and visualize factors influencing land use in the rural fringe reduce residual spatial autocorrelation. Other spatial analyses were used to identify factor concentrations, patterns of rural networking, and clustering related to social capital.

Results show that prime farmland is significantly related to farm conversion and that the important social capital variable related to farm preservation participation also accounts, to a certain degree, for the change in land use for the study area. Strength of relationship and factor patterning factors related to land use change were successfully identified. Additionally, this research has illustrated the need to explore means to include non-economic variables in future research on the causes of urban sprawl and loss of farmland.

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