| 纳入动态数据的改进FLUS模型在城市增长边界划定中的应用 |
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| 引用本文： | 王志远,张考,丁志鹏,伍随意,黄春华.纳入动态数据的改进FLUS模型在城市增长边界划定中的应用[J].地球信息科学,2020,22(12):2326-2337. |
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| 作者姓名： | 王志远 张考 丁志鹏 伍随意 黄春华 |
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| 作者单位： | 1.中南大学建筑与艺术学院,长沙 4100832.南华大学建筑学院,衡阳 4210013.湖南省健康城市营造工程技术研究中心,衡阳 4210014.南华大学土木工程学院,衡阳 421001 |
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| 基金项目： | 国家自然科学基金项目(51478470);湖南省社会科学基金项目(18YBQ106);湖南省教育厅科学研究项目(19B480) |
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| 摘 要： | 城市增长边界是管控城市建设用地无序扩张的有效手段,科学合理划定城市增长边界是当前研究关注的重要课题。本研究试图引入百度动态交通时间和POI数据改进FLUS模型,以长沙市中心城区为例,采用2000、2010和2018年3期土地利用数据对比验证改进FLUS模型模拟精度,并利用改进FLUS模型设置2种情景,模拟2030年长沙市中心城区土地利用变化,结合用地适宜性评价划定城市增长边界。结果显示：① 纳入动态数据的改进FLUS模型模拟2010年和2018年土地利用相比原模型KAPPA系数提高了2.90%和2.74%,总体精度提高了1.79%和1.83%,表明改进模型具有更高模拟精度;② 利用改进FLUS模型模拟的2030年长沙市中心城区土地利用变化,基准情景和生态保护情景建设用地规模分别为930.06 km2和881.36 km2,均以耕地转为建设用地比例最大;③ 长沙市中心城区刚性增长边界范围为1479.59 km2,占中心城区总面积的37.38%,边界内包含了芙蓉区、天心区、雨花区、岳麓区和开福区的大部分区域;④ 基准情景和生态保护情景下,长沙市中心城区弹性增长边界面积分别为799.35 km2和742.92 km2,建设用地扩张空间主要为长沙县和望城区,结果与2010版长沙市城市总体规划拓展方向一致。纳入动态数据的改进FLUS模型多情景模拟划定城市增长边界,能更高精度的为规划决策提供科学依据。
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| 关 键 词： | 城市增长边界 改进FLUS模型 动态数据 精度验证 土地利用变化 情景模拟 用地适宜性评价 长沙中心城区 |
| 收稿时间： | 2020-07-15 |
Delineation of Urban Growth Boundary based on Improved FLUS Model Considering Dynamic Data |
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| WANG Zhiyuan,ZHANG Kao,DING Zhipeng,WU Suiyi,HUANG Chunhua.Delineation of Urban Growth Boundary based on Improved FLUS Model Considering Dynamic Data[J].Geo-information Science,2020,22(12):2326-2337. |
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| Authors: | WANG Zhiyuan ZHANG Kao DING Zhipeng WU Suiyi HUANG Chunhua |
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| Institution: | 1. School of Architecture and Art, Central South University, Changsha 410083, China2. School of Architecture, University of South China, Hengyang 421001, China3. Hunan Healthy City Construction Engineering Technology Research Center, Hengyang 421001, China4. School of Civil Engineering, University of South China, Hengyang 421001, China |
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| Abstract: | Measuring the urban growth boundary is important to control the disorderly expansion of urban constructed land. How to define the urban growth boundary scientifically is a hot topic of current researches. This study attempts to introduce Baidu dynamic traffic data and POI data to improve the FLUS model to simulate land use changes. Taking the central of Changsha city as an example, the simulation accuracy of the improved FLUS model is first verified by comparing with the land use data of 2000, 2010, and 2018. Then, the land use of central Changsha in 2030 is simulated based on two scenarios using the improved FLUS model. The urban growth boundary is finally defined based on land suitability evaluation. The results show that: (1) Compared with the original FLUS model, the kappa coefficient of the improved FLUS model with dynamic data increases by 2.90% and 2.74% in 2010 and 2018, respectively, and the overall accuracy increases by 1.79% and 1.83%, respectively, which indicates a higher simulation accuracy of the improved model; (2) Based on the simulated land use of central Changsha in 2030, the area of constructed land is 930.06 km2 and 881.36 km2 respectively in benchmark scenario and ecological protection scenario. The largest proportion of land converted to construction land is cultivated land; (3) The area within the rigid growth boundary of central Changsha is 1479.59 km2, accounting for 37.38% of the total area of the central city. These areas include Furong District, Tianxin District, Yuhua District, Yuelu District, and Kaifu District; (4) The area within the elastic growth boundary of central Changsha is 799.35 km2 and 742.92 km2 under the benchmark scenario and ecological protection scenario, respectively. The expanded construction mainly occurs in Changsha County and Wangcheng District, which is consistent with the development direction of 2010 Changsha urban master plan. The improved FLUS model with dynamic data can simulate the urban growth boundary in multiple scenarios, which provides a scientific basis for future planning decision. |
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| Keywords: | urban growth boundary improved FLUS model dynamic data accuracy verification land use change scenario simulation land suitability evaluation Changsha central city |
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