基于蚁群智能算法的建设用地空间优化研究——以锦州一葫芦岛沿海地区为例

利用遥感影像快速准确地提取多种生态环境方面的基础信息，应用数学概念中的多准则多目标评价原理，采用GIS空间分析技术对锦州一葫芦岛沿海地区的建设用地进行适宜性评价．之后，使用基于蚁群智能算法的元胞自动机（ACO-CA）模型在适宜性评价的基础上进行建设用地的位置选取，从而实现建设用地的空间优化．优化结果与辽宁沿海经济带开发建设规划及土地利用等相关规划的内容基本吻合，与各城市的空间发展战略基本一致．该方法使停留在理论探讨上的空间优化问题在方法论上有了补充，该优化结果有利于从开发建设的根源上控制和减少人类活动对生态系统的不利影响，促进锦州一葫芦岛沿海地区的城市建设与生态建设协调发展．

Spatial Optimization Research on Construction Land Based on Ant Colony Algorithm -- A Case Study of Jinzhou-Huludao Coastal Area

Using remote sensing images to quickly and accurately extract the basic information of a variety of ecological environment, with multi-criteria multi-objective evaluation principle of mathematics concept, GIS spatial analysis techniques were used to make suitability evaluation of Jinzhou-Huludao coastal area. Then, used ACO-CA model was adopted to do construction land location selection based on suitability evaluation, so as to achieve spatial optimization of construction land. Optimization results are basically consistent with Liaoning Coastal Economic Zone Development and Construction Planning and other relevant with the urban spatial development strategy. plannings. The optimization results are also consistent This method complements the methodology for space optimization, which stays in the theoretical discussion. The optimization results benefit from the development and construction of the root causes of human activities on the control and reduction of the adverse effects on the ecosystem, and promote urban construction and ecological construction of the coordinated development of Jinzhou-Huludao coastal area.