基于地理模型与优化的城市扩张与生态保护二元空间协调优化

协调城市扩张与生态敏感区保护之间的矛盾是当前我国新型城镇化建设中的一项重要任务,但基于传统供需平衡模式或历史惯性驱动模拟的城市规划布局可能导致一系列潜在的生态环境问题。根据城市发展具有历史惯性驱动和空间规划引导的双重特性,提出将地理模拟与优化(Geographical Simulation and Optimization Systems,简写为GeoSOS)等复杂GIS空间分析技术引入规划决策分析。通过利用最小累积阻力模型获取生态敏感区保护压力格局,并利用元胞自动机模型进行城市扩张模拟,分析城市惯性扩张模式对生态敏感区的潜在影响;然后根据生态敏感区保护和城市空间扩张的协调性发展目标进行生态适宜性评价,进而利用蚁群智能空间优化配置模型产生一种优化的城市空间布局方案。研究以我国珠江三角洲地区的广州市为案例,详细分析了基于GeoSOS的城市扩张与生态保护的协调决策过程。结果表明,整合了城市发展惯性与生态敏感区保护双重目标的空间优化布局方案,比单纯基于地理模拟进行规划布局更符合生态型城市建设需求,研究所提出的城市与生态二元空间协调分析框架可为城市规划提供可靠的定量决策支撑。

coupling geographical simulation and spatial optimization for harmonious pattern analysis by considering urban sprawling and ecological conservation

In recent years, ecological systems such as forests, farmlands, and wetlands have witnessed an alarming rate of encroachment owing to indiscriminate urban development. This has resulted in the emergence of serious environmental and ecological issues such as air pollution, heat island formation, and groundwater contamination. Therefore, rational urban growth is becoming an increasingly important focus area for decision makers. Urban land planning is one of the most important means for inducing rational urban growth. However, most urban planning scenarios are based on only historical sprawl trends or traditional supply-demand balance; hence, they tend to ignore potential ecological and environmental issues. Consequently, optimal urban growth patterns that consider ecological conservation are attracting considerable interest from researchers and administrative decision makers. The conservation of ecologically sensitive areas plays a key role in environmental protection. Thus, harmonizing urban sprawling with the conservation of ecologically sensitive areas can be viewed as a binary compatibility planning problem. Here, we employ a geographical simulation and optimization system (GeoSOS) to apply complex spatial techniques to the analysis of the conflict between urban development and ecological protection. Current urban planning strategies and historical development rules are both considered to generate ecologically harmonious urban growth patterns, with the objective of providing a feasible decision-making framework for urban planning. The main procedures can be described as follows: First, ecologically sensitive areas such as rivers and mountains are marked out on the basis of actual development demands. Next, the spatial conservation priority for ecologically sensitive areas is calculated using the minimum cumulative resistance (MCR) model. Second, urban sprawl patterns are simulated on the basis of historical rules using the cellular automata (CA) model. The conflict between urban development and the conservation of ecologically sensitive areas is then identified according to the simulation results; potential ecological issues are also considered for urban planning. Third, a trade-off between urban development and ecological protection is considered when re-evaluating ecological suitability for urban sprawling; then, an ecologically harmonious pattern is accordingly generated using the ant colony optimization (ACO) model. Guangzhou City, located in the Pearl River Delta, China, is selected for a case study to validate the feasibility of the proposed analysis framework. Remote sensing images collected in the years 2000, 2005, and 2010 are used to obtain urban land information and to identify ecologically sensitive areas. Topographical and socio-economic data as well as transportation networks are used to analyze the locational conditions for urban development. In addition, a schematic map of land use in 2005 and current urban planning documents are used as important reference materials. The harmonious planning procedure supported by GeoSOS is described and verified in detail. An optimal urban growth pattern that considers ecological protection is generated using the ACO model, and it is compared with the simulation pattern obtained using the CA model. Results indicate that the former is a closer approximation of actual urban development than the latter and results in less environmental degradation. Spatial optimization techniques can be also used as efficient auxiliary tools for decision-making. The binary compatibility framework based on GeoSOS can serve as an additional technical reference for urban planning.