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作 者:王海鹰 秦奋[1,2] 张新长[3] 张传才[4] 李培君[1]
机构地区:[1]河南大学环境与规划学院,河南开封475001 [2]黄河中下游数字地理技术教育部重点实验室,河南开封475001 [3]中山大学地理科学与规划学院,广东广州510275 [4]安徽理工大学测绘学院,安徽淮南232001
出 处:《地理科学》2017年第3期426-436,共11页Scientia Geographica Sinica
基 金:国家自然科学基金青年项目(41401457);国家自然科学基金重点项目(41431178);国家科技支撑计划项目(2013BAC05B01);河南省高等学校重点科研项目计划(15A170003)资助~~
摘 要: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。Urban ecological land plan in cities is an important foundation and premises for the protection of ur- ban 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, intensive- ness and compactness of ecological land, and urban spatial development. This article will propose Urban Eco- logical 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 compact- ness and the index of nearest neighbor distance in the process of establishing plan objectives function. Further- more 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 Opti- mization 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 dis- tance 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 sci- entific support and reference to
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