[1]贺城墙,王盼成,曾永年*.长株潭都市圈城市空间演化情景预测及其耕地影响分析[J].山地学报,2023,(5):689-700.[doi:10.16089/j.cnki.1008-2786.000780]
 HE Chengqiang,WANG Pancheng,et al.Scenario Prediction of Urban Spatial Evolution and Its Impact on Arable Land in Chang-Zhu-Tan Metropolitan Region, China[J].Mountain Research,2023,(5):689-700.[doi:10.16089/j.cnki.1008-2786.000780]
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长株潭都市圈城市空间演化情景预测及其耕地影响分析
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2023年第5期
页码:
689-700
栏目:
山区发展
出版日期:
2023-11-15

文章信息/Info

Title:
Scenario Prediction of Urban Spatial Evolution and Its Impact on Arable Land in Chang-Zhu-Tan Metropolitan Region, China
文章编号:
1008-2786-(2023)5-689-12
作者:
贺城墙12王盼成12曾永年12*
(1.中南大学 地球科学与信息物理学院,长沙 410083; 2.中南大学 空间信息技术与可持续发展研究中心,长沙 410083)
Author(s):
HE Chengqiang1 2 WANG Pancheng1 2 ZENG Yongnian1 2
(1. School of Geoscience and Info-physics, Central South University, Changsha 410083, China; 2. Central for Geomatics and Sustainable Development Research, Central South University, Changsha 410083, China)
关键词:
城市空间演化 情景模拟 耕地变化 长株潭都市圈
Keywords:
urban space expansion scenario simulation arable land change the Chang-Zhu-Tan metropolitan region
分类号:
F291.1; F205
DOI:
10.16089/j.cnki.1008-2786.000780
文献标志码:
A
摘要:
长江经济带建设是新时期中国经济社会发展的重大战略之一。城市群国土空间的合理规划与科学管理对长江经济带健康、可持续发展具有重要的意义。位居长江中游的长株潭都市圈经历了快速的城镇化过程,城市扩展对区域资源与环境产生了深刻的影响,但目前该区域国土空间格局及变化预测的研究不足,城市空间扩展对耕地保护的影响尚不明确。本文基于极限学习的城市扩展元胞自动机模型,在自然增长、规划发展、生态优先三种城市发展情景下,模拟预测了2030年长株潭都市圈城市空间格局,分析了城市空间演化对耕地面积及其空间分布的影响。研究结果表明:(1)在自然增长、规划发展、生态优先三种城市发展情景下,2030年长株潭都市圈建设用地将分别达到1295.08、1166.44、1104.78 km2。在三种城市发展情境下,长株潭都市圈建设用地均以边缘增长为主,向外扩展延伸,城市一体化趋势显著;(2)在自然增长、规划发展、生态优先三种情景下,2030年长株潭都市圈耕地将分别减少到2088.30、2134.94、2199.45 km2。城市建设用地的扩展导致区域耕地面积的减少,从粮食安全与可持续发展的角度,生态优先的发展模式是未来长株潭都市圈优选的发展模式。研究结论可为长株潭都市圈城市空间规划与管理提供科学依据,为长江经济带城市生态安全和可持续发展提供参考。
Abstract:
The construction of the Yangtze River Economic Belt is one of the major strategies for China's economic and social development in the new period. The rational planning and scientific management of land space of urban agglomerations are of great significance to a healthy and sustainable development in the Yangtze River Economic Belt.
Located in the middle reaches of the Yangtze River, the Chang-Zhu-Tan metropolitan region has experienced rapid urbanization, and urban expansion has had a profound impact on regional resources and the environment; however, there was insufficient knowledge of the spatial pattern of land-use in the region, nor any prediction of urban spatial pattern changes, and the impact of urban spatial expansion on the protection of arable land was yet unclear.
In this study, it predicted the urban spatial pattern of the Chang-Zhu-Tan metropolitan region in 2030 using a cellular automata model of urban expansion evolved from extreme learning machine model. It analyzed the impacts of urban spatial evolution on the arable land area and its spatial distribution under three scenarios of urban expansion, namely, natural growth, planned development, and ecological priority.
It found that(1)under the three scenarios of natural growth, planned development, and ecological priority, the urban construction land in the Chang-Zhu-Tan metropolitan region would reach 1295.08 km2, 1166.44 km2, 1104.78 km2 respectively in 2030, respectively. Specifically, from 2010 to 2030, land occupied by urban construction would goes to a corresponding increase by 597.54 km2, 2134.94 km2 and 448.16 km2 in the three scenarios. The construction land in the region would be dominated by marginal growth, extending outward, with a significant trend of urban integration.(2)Under the three scenarios of natural growth, planned development, and ecological priority, the arable land in the region would be 2088.30 km2, 2134.94 km2 and 2199.45 km2 respectively in 2030. The expansion of urban construction land leads to the reduction in regional arable land. From the perspective of food security and sustainable development, the ecological priority development mode is the preferred development scenario for the region in future.
The research conclusions can provide a scientific basis for urban spatial planning and management of the Chang-Zhu-Tan metropolitan region, and provide a reference for the ecological safety and sustainable development of the cities in the Yangtze River Economic Belt.

参考文献/References:

[1] 周成虎. “长江经济带”专辑序言[J]. 地理科学进展, 2015, 34(11): 1335.[ZHOU Chenghu. The preface to the special edition of “Yangtze River Economic Belt” [J]. Progress in Geography, 2015, 34(11): 1335]
[2] 贺大为, 金贵, 王新生, 等. 长江经济带国土空间开发与保护路径优化[J]. 生态学报, 2023, 43(14): 5776-5787.[HE Dawei, JIN Gui, WANG Xinsheng, et al. Optimization of development and protection pattern of territorial space in the Yangtze River Economic Belt [J]. Acta Ecologica Sinica, 2023, 43(14): 5776-5787] DOI: 10.5846/stxb202206141698
[3] 习明明. 长江中游城市群: 中国经济增长的第四级[J]. 区域经济评论, 2013(4): 131-133.[XI Mingming. City clusters in the middle reaches of the Yangtze River: The fourth level of China's economic growth [J]. Regional Economic Review, 2013(4): 131-133] DOI: 10.14017/j.cnki.2095-5766.2013.04.023
[4] 周国华, 陈炉, 唐承丽, 等. 长株潭城市群研究进展与展望[J]. 经济地理,2018, 38(6): 52-61.[ZHOU Guohua, CHEN Lu, TANG Chengli, et al. Research progress and prospects on Changsha-Zhuzhou-Xiangtanurban agglomeration [J]. Economic Geography, 2018, 38(6): 52-61] DOI: 10.15957/j.cnki.jjdl.2018.06.007
[5] 李仙, 潘玉龙. 习近平总书记关于粮食安全重要论述探析[J]. 农村·农业·农民(A版), 2023(5): 19-23.[LI Xian, PAN Yulong.Analysis of important discussions on food security by General Secretary XI Jinping [J]. Rural Agriculture Farmers(Version A), 2023(5): 19-23]
[6] 杨尚钊, 张宏胜, 李超芹, 等. 我国粮食安全的现状、问题及对策[J]. 粮食问题研究, 2023(1): 14-17. [YANG Shangzhao, ZHANG Hongsheng, LI Chaoqin, et al.The current situation, problems and countermeasures of food security in China [J]. Research on Food Issues, 2023(1): 14-17]
[7] 张雅杰, 金海. 长江中游地区城市建设用地利用效率及驱动机理研究[J]. 资源科学, 2015, 37(7): 1384-1393.[ZHANG Yajie, JIN Hai. Research on efficiency of urban construction landand the drive mechanism in the Mid-Yangtze River [J]. Resources Science, 2015, 37(7): 1384-1393]
[8] 朱媛媛, 张瑞, 顾江, 等. “双碳”目标下长江中游城市群生态福利绩效演变及驱动机制研究[J]. 地理科学进展, 2022, 41(12): 2231-2243.[ZHU Yuanyuan, ZHANG Rui, GU Jiang, et al. Spatiotemporal evolution and driving mechanism of ecological well-being performancein the urban agglomeration of the middle reaches of the Yangtze River under the carbon peaking and carbon neutrality goals [J]. Progress in Geography, 2022, 41(12): 2231-2243] DOI: 10.18306/dlkxjz.2022.12.004
[9] 胡昕利, 易扬, 康宏樟, 等. 近25年长江中游地区土地利用时空变化格局与驱动因素[J]. 生态学报, 2019, 39(6): 1877-1886.[HU Xili, YI Yang, KANG Hongzhang, et al. Temporal and spatial variation of land use and the driving factors in the middle reaches of the Yangtze River in the past 25 years [J]. Acta Ecologica Sinica, 2019, 39(6): 1877-1886] DOI: 10. 5846/stxb201809302138
[10] 王海军, 任经纬, 张彬, 等. 利用广义加性模型解析长江中游城市群城镇用地扩展驱动力[J]. 长江流域资源与环境, 2021, 30(1): 32-43.[WANG Haijun, REN Jingwei, ZHANG Bin, et al. Analysis of driving forces of urban land expansion in urban agglomeration in the middle reaches of the Yangtze River based on general additive [J]. Resources and Environment in the Yangtze Basin, 2021, 30(1): 32-43] DOI: 10.11870/cjlyzyyhj202101004
[11] 瞿诗进, 胡守庚, 童陆亿,等. 长江中游经济带城镇建设用地转型的时空特征[J]. 资源科学, 2017, 39(2): 240-251.[QU Shijin, HU Shougeng, TONG Luyi, et al. Temporal and spatial characteristics of urban construction land transformation in the middle Yangtze River Economic Belt [J]. Resources Science, 2017, 39(2): 240-251] DOI: 10.18402/resci.2017.02.07
[12] 徐磊, 董捷, 陈恩. 基于“三生”功能的长江中游城市群国土空间利用协调特征[J]. 水土保持研究, 2018, 25(2): 254-263. [XU Lei, DONG Jie, CHEN En.Coordination features of geographical space utilization in urban agglomeration in the middle reaches of the Yangtze River based on ‘production-living-ecological' function [J]. Research of Soil and Water Conservation, 2018, 25(2): 254-263] DOI: 10.13869/j.cnki.rswc.2018.02.037
[13] 朱翔, 王晖, 吴宜进, 等. 基于Google Earth Engine的长江中游城市群城镇化与生态环境耦合协调研究[J]. 长江流域资源与环境, 2022, 31(12): 2707-2717.[ZHU Xiang, WANG Hui, WU Yijin, et al. Research on the coupling coordination degree of urbanization and eco-environment of the urban agglomeration in the middle reaches of the Yangtze River based on Google Earth Engine [J]. Resources and Environment in the Yangtze Basin, 2022, 31(12): 2707-2717] DOI: 10.11870/cjlyzyyhj202212014
[14]马振玲, 曾永年, 闫利. 长株潭城市群核心区域土地利用/覆盖变化驱动机制定量研究[J]. 测绘通报, 2012(10): 41-44.[MA Zhenling, ZENG Yongnian, YAN Li. Quantitative study on driving mechanism of land use and land cover change in Changsha-Zhuzhou-Xiangtan urban agglomerations [J]. Bulletin of Surveying and Mapping, 2012(10): 41-44]
[15] 唐常春, 李亚平. 多中心城市群土地利用/覆被变化地学信息图谱研究——以长株潭城市群为例[J]. 地理研究, 2020, 39(11): 2626-2641.[TANG Changchun, LI Yaping. Geo-information tupu process of land use/cover change in polycentric urban agglomeration: A case study of Changsha-Zhuzhou-Xiangtan urban agglomeration [J]. Geographical Research, 2020, 39(11): 2626-2641] DOI: 10.11821/dlyj020200207
[16]易凤佳, 李仁东, 常变蓉, 等. 长株潭地区建设用地扩张遥感时空特征分析[J].国土资源遥感, 2015, 27(2): 160-166. [YI Fengjia, LI Rendong, CHANG Bianrong, et al. Spatial-temporal features of construction land expansion in Changzhutan(Changsha-Zhuzhou-Xiangtan)area based on remote sensing [J]. Remote Sensing for Land and Resources, 2015, 27(2): 160-166] DOI: 10.6046/gtzyyg.2015.02.25
[17] 欧阳晓, 朱翔, 贺清云. 城市群城市用地扩张时空特征及驱动机制研究—以长株潭城市群为例[J].长江流域资源与环境, 2020, 29(6): 1298-1309.[OUYANG Xiao, ZHU Xiang, HE Qingyun. Study of spatio-temporal pattern and driving mechanism of urban land expansion in urban agglomeration: A case study of the Changsha-Zhuzhou-Xiangtan urban agglomeration [J]. Resources and Environment in the Yangtze Basin, 2020, 29(6): 1298-1309] DOI: 10.11870/cjlyzyyhj202006005
[18] 彭海泉, 邹艳红. 基于STIRPAT模型的长株潭城市建设用地扩展驱动因素分析[J]. 测绘与空间地理信息, 2018, 41(6): 159-162.[PENG Haiquan, ZOU Yanhong. Analysis of driving forces of construction land expansion for Changsha-Zhuzhou-Xiangtan based on STIRPAT model [J]. Geomatics and Spatial Information Technology, 2018, 41(6): 159-162]
[19] 王乐, 朱红梅, 李沅澍. 基于DEA的长株潭城市群用地扩展的经济效益研究[J]. 国土与自然资源研究, 2013(2): 14-16.[WANG Le, ZHU Hongmei, LI Yuanshu. Research on the economic benefits of land expansion of Changzhutan Urban Agglomeration based on DEA [J]. Territory and Natural Resources Study, 2013(2): 14-16] DOI: 10.16202/j.cnki.tnrs.2013.02.028
[20] 熊鹰, 陈云, 李静芝, 等. 基于土地集约利用的长株潭城市群建设用地供需仿真模拟[J]. 地理学报, 2018, 73(3): 562-577.[XIONG Ying, CHEN Yun, LI Jingzhi, et al. Analog simulation of urban construction land supply and demand based on land intensive use [J]. Acta Geographica Sinica, 2018, 73(3): 562-577] DOI: 10.11821/dlxb201803013
[21] 陈永林, 谢炳庚, 钟典, 等. 基于微粒群-马尔科夫复合模型的生态空间预测模拟——以长株潭城市群为例[J]. 生态学报, 2018, 38(1): 55-64. [CHEN Yonglin, XIE Binggeng, ZHONG Dian, et al. Predictive simulation of ecological space based on a particle swarm optimization-Markov composite model: A case study for Chang-Zhu-Tan urban agglomerations [J].Acta Ecologica Sinica, 2018, 38(1): 55-64] DOI: 10.5846/stxb201612082530
[22] 朱政, 朱翔. 长株潭城市群农业用地损失的动态模拟研究[J]. 长江流域资源与环境, 2019, 28(5): 1142-1153. [ZHU Zheng, ZHU Xiang.Dynamic simulation analysis on the loss of agricultural land of Changsha-Zhuzhou-Xiangtan urban agglomeration [J]. Resources and Environment in the Yangtze Basin, 2019, 28(5): 1142-1153] DOI: 10.11870/cjlyzyyhj201905014
[23] 周成虎, 孙战利, 谢一春. 地理元胞自动机研究[M]. 北京: 科学出版社, 1999: 134-135.[ZHOU Chenghu, SUN Zhanli, XIE Yichun. Research on geographic cellular automata [M]. Beijing: Science Press, 1999: 134-135]
[24] 黎夏, 叶嘉安, 刘小平. 地理模拟系统: 元胞自动机与多智能体[M]. 北京: 科学出版社, 2007: 273-274.[LI Xia, YE Jiaan, LIU Xiaoping. Geographic simulation system: Cellular automata and multiagent [M]. Beijing: Science Press, 2007: 273-274]
[25] 黎夏, 刘小平, 李少英. 智能式GIS与空间优化[M]. 北京: 科学出版社, 2010: 123-126, 186-187.[LI Xia, LIU Xiaoping, LI Shaoying. Intelligent GIS and spatial optimization [M]. Beijing: Science Press, 2010: 123-126, 186-187]
[26] 刘耀林, 仝照民, 刘岁, 等. 土地利用优化配置建模研究进展与展望[J]. 武汉大学学报·信息科学版, 2022, 47(10): 1598-1614.[LIU Yaolin, TONG Zhaomin, LIU Sui, et al. Progress and prospects of research on optimal land-use allocation modeling [J]. Geomatics and Information Science of Wuhan University, 2022, 47(10): 1598-1614] DOI: 10.13203/j.whugis20220603
[27] 李媛洁, 叶长盛, 黄小兰. 基于CLUE-S 模型的南昌市“三生”空间时空演变及情景模拟研究[J]. 水土保持研究, 2021, 28(5): 325-332.[LI Yuanjie, YE Changsheng, HUANG Xiaolan. Temporal-spatial evolution and scenario simulation of production-living-ecological space in Nanchang based on CLUE-S model [J]. Research of Soil and Water Conservation, 2021, 28(5): 325-332] DOI: 10.13869/j.cnki.rswc.2021.05.037
[28] 吴桂平, 曾永年, 冯学智, 等. CLUE-S 模型的改进与土地利用变化动态模拟: 以张家界市永定区为例[J]. 地理研究, 2010, 29(3): 460-470.[WU Guiping, ZENG Yongnian, FENG Xuezhi, et al. Dynamic simulation of land use change based on the improved CLUE-S model: A case study of Yongding county, Zhangjiajie [J]. Geographical Research, 2010, 29(3): 460-470]
[29] GANTUMUR B, WU Falin,VANDANSAMBUU B, et al. Spatiotemporal dynamics of urban expansion and its simulation using CA-ANN model in Ulaanbaatar, Mongolia [J]. Geocarto International, 2022, 37(2): 494-509. DOI: 10.1080/10106049.2020.1723714
[30] WU Fulong. Calibration of stochastic cellular automata: The application to rural-urban land conversions [J]. International Journal of Geographical Information Science, 2002, 16(8): 795-818. DOI: 10.1080/13658810210157769
[31] 杨青生, 黎夏. 基于支持向量机的元胞自动机及土地利用变化模拟[J]. 遥感学报, 2006, 10(6): 836-846.[YANG Qingsheng, LI Xia. Cellular automata for simulating land use changes based on Support Vector Machine [J]. Journal of Remote Sensing, 2006,10(6): 836-846]
[32] 陈逸敏, 黎夏. 机器学习在城市空间演化模拟中的应用与新趋势[J]. 武汉大学学报·信息科学版, 2020, 45(12): 1884-1889.[CHEN Yimin, LI Xia. Applications and new trends of machine learning in urban simulation research [J]. Geomatics and Information Science of Wuhan University, 2020, 45(12): 1884-1889] DOI: 10.13203/j.whugis20200423
[33] 张亦汉, 刘小平, 陈广亮, 等. 基于最大熵的CA模型及其城市扩张模拟[J]. 中国科学: 地球科学, 2020, 50(3): 339-352. [ZHANG Yihan, LIU Xiaoping, CHEN Guangliang, et al. Simulation of urban expansion based on cellular automata and maximum entropy model [J]. Science China Earth Sciences, 2020, 50(3): 339-352] DOI: 10.1360/SSTe-2019-0110
[34]卞子金. 基于极限学习机的高分辨率遥感图像分类算法研究[D]. 沈阳: 辽宁师范大学, 2015: 6-8.[BIAN Zijin. The study of high resolution remote sensing image classification based on extreme learning machine[D]. Shenyang: Liaoning Normal University, 2015: 6-8.
[35] 王鹤, 曾永年. 城市扩展极限学习机模型[J]. 测绘学报, 2018, 47(12): 1680-1690.[WANG He, ZENG Yongnian.Urban expansion model based on extreme learning machine[J]. Acta Geodaeticaet Cartographica Sinica, 2018, 47(12): 1680-1690] DOI: 10.11947/j.AGCS.2018.20170586

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备注/Memo

备注/Memo:
收稿日期(Received date): 2023-03-26; 改回日期(Accepted date): 2023-09-20
基金项目(Foundation item): 国家自然科学基金(42171364)[National Natural Science Foundation of China(42171364)]
作者简介(Biography): 贺城墙(1996-),男,湖南娄底人,硕士研究生,主要研究方向:城市及区域环境模拟与GIS应用。[HE Chengqiang(1996-),male, born in Loudi, Hunan province, M.Sc. candidate, research on environmental modeling and GIS application] E-mail: 778978421@qq.com
*通讯作者(Corresponding author): 曾永年(1959-),男,博士,教授,主要研究方向:遥感与地理信息系统及其环境变化。[ZENG Yongnian(1959-), male, Ph.D., professor, research on remote sensing and GIS application in environment] E-mail: ynzeng@csu.edu.cn
更新日期/Last Update: 2023-09-30