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基于景观安全格局的城镇建设用地扩张多情景模拟研究——以扬州市为例 被引量:5

Multi-scenario Simulation of Urban Construction Land Expansion Based on Landscape Security Pattern——A Case of Yangzhou City
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摘要 城镇建设用地多情景模拟有利于实现土地资源优化配置,保障区域可持续发展。本文以扬州市为例,以2005年、2013年土地利用变更数据为训练数据,借助景观安全格局与ANN-CA模型模拟城镇建设用地扩张趋势,并利用城镇建设用地转移矩阵与景观格局指数分析2013—2020年城镇建设用地模拟结果。研究结果表明:(1)不同情景下的城镇建设用地模拟扩张占用其他景观规模不同,但均占用农村居民点规模最多,其中,惯性发展情景下,模拟新增城镇建设用地以布局在低景观安全格局为主,占用耕地、水域、林地规模较高;基本保障情景下,模拟新增的城镇建设用地主要布局在中景观安全格局区域,较惯性发展情景占用耕地规模增加,占用水域、林地规模减少;与惯性发展情景、基本保障情景相比,最优保护情景下占用耕地规模略高但集中于高景观安全格局区,新增占用水域规模、林地规模降低。(2)不同情景下的景观格局也存在差异,惯性发展情景下,景观格局变化一定程度有利于促进城镇化发展,但不利于耕地机械化生产,影响林地、水域生态服务功能;基本保障情景下,景观格局变化一定程度上有利于城乡社会经济发展,对非人工景观的破坏程度较惯性发展情景降低;最优保护情景下,景观格局变化更有利于区域社会、经济及生态发展。(3)惯性发展情景下,应适当规划生态基础设施,严格划定永久性基本农田;基本保障情景下,应充分发挥景观安全格局的生态底线功能,引导城镇建设用地合理开发与布局;最优保护情景下,可通过存量建设用地挖潜等措施提高土地集约利用水平。 Multi-scenario simulating the expansion of urban construction land is beneficial to the realization of the optimal allocation of land resources and the sustainable development of the region. Taking Yangzhou City as an example, taking the land use change datum of 2005 and 2013 year as training datum, this paper simulates the expansion trend of urban construction land based on ANN-CA model, analyzes the advantages and disadvantages of each simulated scenario by using land transfer matrix for urban construction and landscape pattern index of 2013—2020 year. The results indicate: 1) The scales of other landscape occupied by the expansion of urban construction are different in different scenarios, but rural settlement is occupied most in each scenario. In the inertial development scenario, the new urban construction land is mainly clustered in the region with low landscape security pattern, and occupies more arable land, waters and woodland. In the basic security scenario, the new urban construction land is mainly distributed in the region with middle landscape security pattern. Compared to the inertial development scenario, it occupies more arable land but less waters and woodland. The optimal protection scenario occupies more arable land but less waters and woodland compared with the inertial development scenario and the basic security scenario, but mainly concentrates in the region with high landscape security pattern. 2) Landscape patterns are different in the three scenarios. In the inertial development scenario, landscape pattern change is conducive to the development of urbanization, but adverse to the mechanized production of arable land and the ecological service functions of woodland and waters. In the basic security scenario, landscape pattern change is beneficial to the social and economic development of urban and rural areas to a certain extent, and damages less to waters and woodland than the inertial development scenario. In the optimal protection scenario, landscape pattern change is more conducive to the regional social, economic and ecological development. 3) In the inertial development scenario, the ecological infrastructure should be planned properly and the permanent basic farmland should be delimited strictly. In the basic security scenario, the government should give full play to the ecological bottom line function of the landscape security pattern and guide the rational development and layout of the urban construction land. In optimal protection scenario, the government should improve the level of intensive land use by exploitering the stock construction land and so on.
作者 孟霖 郭杰 欧名豪 李昆鹏 MENG Lin;GUO Jie;OU Minghao;Li Kunpeng(College of Land Management,Nanjing Agricultural University,Nanjing 210095,China;Center of Urbanrural Joint Development and Land Management lnnovation,Nanjing 210095,China;State and Local Joint Engineering Research Center of Rural Land Resources Utilization and Consolidation,Nanjing 210095,China;Shunting Community Committee of Darning Lake Street,Jinan 250011,China)
出处 《土壤》 CAS CSCD 北大核心 2018年第5期1032-1040,共9页 Soils
基金 国家自然科学基金项目(71774086 71774085) 江苏高校哲学社会科学优秀创新团队项目(2015ZSTD004) 江苏省普通高校学术学位研究生创新计划项目(KYLX15_0540)资助
关键词 城镇建设用地 景观安全格局 ANN-CA模型 多情景预测 Urban construction land Landscape security pattern ANN-CA model Multi-scenario simulation
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