, , ,

1171 | 241 | Urban Growth Boundaries Optimization Under Low-Carbon Development: Combining Multi-Objective Programming and Patch Cellular Automata Models | Jingye Li 1, Jean-Michel Guldmann 2*, Jian Gong 3, Hao Su 4

Urban Growth Boundaries (UGBs) are a tool to control urban sprawl. However, the way to optimize future urban land uses and fix their boundaries is not clear. This paper presents a new framework to delimit UGBs while accounting for ecological, economic, and carbon storage benefits. Aggregate land-use constraints are included in a multi-objective optimization algorithm to capture non-inferior solutions on the Pareto Surface (PS) under different objective scenarios. A patch-level cellular automata simulation model is then used to spatially allocate these land uses, followed by a new two-step adjustment method to delineate the UGBs. This modeling is applied to Wuhan, China. The results show that: (1) One district (Caidian) will have a strong economic growth under low-carbon development. (2) The maximization of carbon storage reduces losses in ecological benefits, suggesting that carbon storage be considered in urban growth planning. (3) The combined model framework and two-step boundary adjustment method can help urban planners define different UGB scenarios and make science-based policy decisions.

Jingye Li 1, Jean-Michel Guldmann 2*, Jian Gong 3, Hao Su 4
1 Department of Land Resource Management, Hohai University, Nanjing 210098, China; 2 Department of City and Regional Planning, The Ohio State University; 3 Department of Land Resource Management, China University of Geosciences, Wuhan, 430074, China; 4 Department of Land Management, Ocean University of China, Qingdao, 266100, China


 
ID Abstract: 241