Modeling Land Use Pattern Change Analysis in the Northern Great Plains: A Novel Approach

The issue of land use/cover (LCLU) change has become a critical field of investigation for economists. This research is designed to present the underlying causes of land use change due to macroeconomic factors and economic growth in Northern Great Plains (NGP) area. This paper introduces a holistic approach that incorporates spatial econometric modeling and geo-spatial modeling to examine the relation between areas of land use change and level of economic activity. The economic component of this study consider panel data sets (both time series and cross section) and the primary sources of data are National Resources Inventory (land use classes), bureau of economic analysis (GDP per capita data), and U.S. census (population density data). A spatial econometric model (Fixed Effect Model) is used to better understand the relationships between areas in land uses and macroeconomic factors influencing change in land use pattern during 1992-2007 time period. The U.S. Geological Survey (USGS) National Land Cover Database (NLCD) is also used here for land use mapping and modeling. The geo-spatial component of this research estimates first-order Markov chain Monte Carlo simulation(MCMC) to calculate transitional probabilities for explaining spatial and temporal patterns of land conversion. The cross sectional analysis reveal the inverse relationship between area of land uses and level of economic activity, as measured by GDP per capita. Also, the fixed effect model indicates the same inverse relation between economic growth and land use change. Key findings also indicate high conversion of urban land and population growth rates have led to an increasingly fragmented land use pattern in the area. Markov chain simulation results for the region also illustrate a change in land use pattern and forest to non-forest conversion over a sixteen year time period.