Modeling park development through regional land use change simulation

Provision of recreational open space is a major factor in determining resident quality of life in cities. However, urban growth and land use change models typically omit park location and allocation issues when simulating changing urban environments. This paper introduces a method for exploring the spatial allocation of urban parks (public, recreational open spaces) given differing municipal and county investment decisions. Park planning literature has established level of service metrics as rough indicators of provision of public park amenities that are useful guides for future park investment decisions within a given jurisdiction. In this study, we create a dynamic-demand location model that simulates political feedback from population growth and LOS metrics to allocate new parklands (similar to 0.5 ha <= neighborhood parks <= similar to 4 ha) in multi-jurisdictional urbanizing regions. We frame parks as a new development type that augments residential development currently driving a version of the Regional Urban Growth (RUG) urban simulation model, an open source, raster-based simulation platform. Our approach allows planners and researchers to explore urban patterns and distributive outcomes associated with different local open space requirements and investment choices. We illustrate this approach under scenarios for the rapidly growing, three-county Raleigh-Durham-Chapel Hill region of North Carolina, USA. We test varying delays in park planning, purchase, and construction, varying maximum park sizes, and the effects of increased investment levels in two jurisdictions within our study area. This model suggests that the most important aspect of successful park planning is the length of the lag time between residential and park development. Perhaps the most successful park planning strategy is to plan parks along with residential areas. (C) 2012 Elsevier Ltd. All rights reserved.