Incorporating active transportation modes in large scale urban modeling to inform sustainable urban development. (January 2022)

• Record Type: Journal Article
• Authors: Cong, Cong; Kwak, Yoonshin; Deal, Brian
• Is Part Of: Computers, environment and urban systems. Volume 91(2022)
• Publication Date: 2022-01
• Subjects: Land use model -- Active transportation modes -- Sustainable development -- Multi-modal -- Urban growth simulation; City planning -- Data processing -- Periodicals; Regional planning -- Data processing -- Periodicals; 303.4834
• DOI: 10.1016/j.compenvurbsys.2021.101726
• Languages: English
• ISSNs: 0198-9715

Abstract

Abstract: Extended suburbanization is a common planning challenge in growing cities and regions. Evaluating potential areas for denser use before the region expands on the urban fringe informs sustainability-driven planning interventions. Land use/land cover (LULC) models are useful tools for planners to prioritize areas of high development potential. However, current models that have not effectively integrated non-auto transportation modes can overestimate the influence of car travel while underestimating the influence of walking or biking accessibility. The result can increase the likelihood of prioritizing suburban development along highways. In this study, we propose to incorporate active transportation modes (walking and biking) and public transportation in large scale urban modeling to explore the relationship between urban growth patterns and human behavior across geographic scales. We consider how a multi-modal methodology informs urban growth simulation and use a scenario-based analysis to evaluate the effects of travel modes on land use development probability. We underscore the oftentimes missed opportunities for infill development in the existing urban areas, as opposed to the opportunities of occupying areas of environmental benefits for large single-family housing and low-density commercial development in the suburbs. Highlights: Multiple travel modes are integrated with large-scale urban growth models. Development potentials driven by non-auto travel inform location-based urban management strategies. An innovative two-step raster-based travel time calculation is conducted.