title: The effects of environmental and socioeconomic factors on land-use changes: a study of Alberta, Canada.
abstract: Various environmental and socioeconomic issues have been attributed to land-use changes, and therefore, the underlying mechanisms merit investigation and quantification. This study assesses a comprehensive series of land-use conversions that were implemented over a recent 12-year period in the province of Alberta, Canada, where rapid economic and population growth has occurred. Spatial autocorrelation models are applied to identify the comprehensive effects of environmental and socioeconomic factors in each conversion case. The empirical results show that the impacts of key environmental and socioeconomic factors varied in intensity depending on the type of land-use conversion involved. Overall, land suitability for agricultural uses, road density, elevation, and population growth were found to be significant predictors of land-use changes. High land suitability, low elevation, and moderate road density were associated with land conversion for agricultural purposes.
authors.affiliation: Department of Renewable Resources, University of Alberta, Edmonton, AB, T6G 2H1, Canada. xruan1@ualberta.ca.
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Ruan
authors.affiliation: Department of Resource Economics and Environmental Sociology, University of Alberta, Edmonton, AB, T6G 2H1, Canada.
authors.forename: Feng
authors.initials: F
authors.lastname: Qiu
authors.affiliation: Department of Renewable Resources, University of Alberta, Edmonton, AB, T6G 2H1, Canada.
authors.forename: Miles
authors.initials: M
authors.lastname: Dyck
mesh_terms: D000383:Agriculture / Q000458:organization & administration*; D000416:Alberta; D004784:Environmental Monitoring / Q000191:economics / Q000379:methods*; D008962:Models, Theoretical; D011158:Population Growth; D012959:Socioeconomic Factors; D062206:Spatial Analysis
keywords: Land suitability; Land-use conversion; Population growth; Road density; Spatial regression model