基于蚁群优化算法的城市生态用地空间规划模型

城市生态用地规划是城市生态系统保护的重要基础和前提。针对传统空间规划方法的不足,提出基于蚁群优化算法的城市生态用地空间规划模型。研究对蚁群优化算法的空间禁忌策略、选择策略进行改进,考虑了城市生态用地的生态效益和空间集约性,在规划目标函数中引入生态适宜性、空间紧凑度和最邻近距离指数,并设计最邻近距离指数的栅格计算方法。以广州市为例,分别模拟城市生态用地占广州市面积15%,30%和50%情景下的生态用地规划方案,取得了较好的效果。研究表明：基于蚁群优化算法的城市生态用地空间规划模型能够合理的对城市生态用地的空间布局进行配置,明显提高了城市生态用地生态效益和空间集约性。

The Spatial Planning Model of Urban Ecological Land Based on Ant Colony Optimization Algorithm

Urban ecological land plan in cities is an important foundation and premises for the protection of urban ecosystem. Rational planning and protection of the land for ecological use is an effective way to address ecological environment problem. In addition, they are also of strategic importance to safeguard the health and balance of ecosystem, and to establish ecological security pattern and spatial extension in cities. Ecological land plan does not only require the guarantee of index area and target amount, it also involves the insurance of a series of spatial objectives and limitation such as maximization of ecological interests, the integrity, intensiveness and compactness of ecological land, and urban spatial development. This article will propose Urban Ecological Land Plan Model (UELPM) based on Ant Colony Optimization. The article makes improvements in the taboo strategy, site selection mechanism. Additionally, it introduces the ecological suitability, spatial compactness and the index of nearest neighbor distance in the process of establishing plan objectives function. Furthermore it designs Trellis Algorithm of the nearest neighbor distance index. For instance, Guangzhou simulates its ecological land plan in different situation when ecological land takes up 15%, 30% and 50% of the city’s total area, which has achieved satisfying result. According to the research, UELPM which based on Ant Colony Optimization can not only set up objectives function and spatial limitations in line with different plan destinations and requirements, but also reasonably allocate the spatial distribution of ecological land. Compared to the scheme of plan ecological control line, the average suitability, spatial compactness and the nearest neighbor distance index are greatly improved in accordance with the spatial simulation result. In addition, all other indexes are superior to the traditional method like plan ecological control line. Therefore, it is meaningful to provide scientific support and reference to urban ecological land use and it also can find itself broad application prospect.