Satellites and Suburbs: A High-resolution Model of Open-space Conversion
AbstractThis study examines the determinants of urbanized area across a 10,000-mile square swath in central North Carolina, an area undergoing extensive conversion of forest and agricultural land.We model the temporal and spatial dimensions of these landscape changes using a database that links five satellite images spanning 1976–2001 to a suite of socioeconomic, ecological and GIScreated explanatory variables. By specifying the complementary log-log derivation of the proportional hazards model, we employ a methodology for modeling a continuous time process – the conversion of land to impervious surface – using discrete-time satellite data. Spatial effects are captured by several variables derived from the imagery that measure the landscape configuration surrounding a pixel. Empirical results confirm the significance of several determinants of urbanization identified elsewhere in the literature, including proximity to roads and population density, but also suggest that the parameterization of these variables is biased when the influence of landscape configuration is unaccounted for. We conclude that the inclusion of spatial pattern metrics significantly improves both the explanatory and predictive power of the estimated model of urbanization.
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Bibliographic InfoPaper provided by Rheinisch-Westfälisches Institut für Wirtschaftsforschung in its series RWI Discussion Papers with number 0050.
Length: 28 pages
Date of creation: Oct 2006
Date of revision:
Find related papers by JEL classification:
- R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-09 (All new papers)
- NEP-GEO-2007-04-09 (Economic Geography)
- NEP-URE-2007-04-09 (Urban & Real Estate Economics)
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25261, University Library of Munich, Germany.
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