Spatial, Temporal and Hierarchical Variability of the Factors Driving Urban Growth: A Case Study of the Treasure Valley of Idaho, USA
Urban landscape is a system of hierarchically nested spatial structures or land patches with their distinct dynamics and causal factors. The lower level structures evolve together to give out different forms, patterns and extents during the process of urbanization. An understanding of driving factors of these hierarchical structures has important implications for future land use planning and urban management. Adopting an innovative framework of urban patch hierarchy, this study investigates the drivers and spatiotemporal variability of their explanatory power at urban and intra-urban patch levels, with Treasure Valley of Idaho, USA as a case of study. We calibrated global and local logistic regression models against a set of 18 spatialized variables. Results show that growth drivers and their impact vary both across the study site and along the cycles of urbanization at different levels of urban landscape. Urban agglomeration factors including the proximity to urbanized area had the highest impact on new development, urban growth forms and land uses. Factors were less stable at the lower level because of their subtle interconnectedness with local structures. The study further revealed an existence of distinct patterns of association among the growth forms, land use types, and the included factors. Specific growth forms and land use classes demonstrated identical temporal patterns with certain driving factors.
KeywordsUrban growth Local logistic regression Growth drivers Spatial patterns Urban growth forms, hierarchical approach
‘The project described was supported by NSF award number IIA-1301792 from the NSF Idaho EPSCoR Program and by the National Science Foundation.’
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