Land use optimization for a rapidly urbanizing city with regard to local climate change : Shenzhen as a case study/ created by
Material type:
- text
- unmediated
- volume
- 07339488
- HT169 JOU
Item type | Current library | Call number | Vol info | Status | Notes | Date due | Barcode | |
---|---|---|---|---|---|---|---|---|
![]() |
Main Library - Special Collections | HT169 JOU (Browse shelf(Opens below)) | Vol. 141, no.1 (pages 05014007-1-12) | Not for loan | For in house use only |
Browsing Main Library shelves, Shelving location: - Special Collections Close shelf browser (Hides shelf browser)
Land use and land use change have been proven to be leading causes of local climate change. In cities that undergo rapid urbanization, the urban heat island (UHI) can generate serious problems for the urban living environment. An appropriate overall land use plan can mitigate the detrimental effects of an UHI because it can reduce its development. However, land use decisions are driven by social and economic factors that cannot be made on the basis of moderating an UHI alone. To make a sound land use plan for Shenzhen in 2020, a rapidly urbanizing city in China suffering from UHI due to its fast land development, a genetic algorithm-based multiobjective optimization (MOO) approach was develped that addresses the objectives for future land use. The MOO provides a set of Pareto solutions and then the decision maker or planner can choose from the set of solutions. Recognizing the definite development of certain nonurban land for the local economy, three objectives were considered: (1) minimizing the increase of surface temperature, (2) minimizing the incompatibility between land uses, and (3) minimizing the cost of land use changes from the status quo. To quantify the effects of land use patterns on the UHI in Shenzhen, a self-organizing maps (SOM) method and linear regression model were used to establish the interactive relation. The relation thus obtained was then used in the MOO to help evaluate the effects of alternative land use patterns on the development of the UHI. Four scenarios were examined. The first scenario took all three objectives into account, and one optimal plan was selected randomly from the Pareto set as the first scenario, whereas the other three scenarios considered one objective each. Results showed that MOO can make tradeoffs among the conflicting objectives, indicating that the optimized land use plans can minimize the increasing UHI effects and at the same time attempt to achieve other objectives in the process of land development.
There are no comments on this title.