地理学报 ›› 2021, Vol. 76 ›› Issue (12): 3012-3024.doi: 10.11821/dlxb202112010
收稿日期:
2021-03-15
修回日期:
2021-10-18
出版日期:
2021-12-25
发布日期:
2022-02-25
通讯作者:
邓羽(1985-), 男, 湖北人, 博士, 副研究员, 主要从事城市发展与空间管治研究。E-mail: dengy@igsnrr.ac.cn作者简介:
王海军(1972-), 男, 陕西凤翔人, 博士, 教授, 主要从事地理模拟、国土空间规划和土地资源评价研究。E-mail: landgiswhj@163.com
基金资助:
WANG Haijun1,2(), WU Yue1, DENG Yu3(
), XU Shan4
Received:
2021-03-15
Revised:
2021-10-18
Published:
2021-12-25
Online:
2022-02-25
Supported by:
摘要:
城市群是具有网络关系与层级性的区域空间,一直是中国推进城镇化与区域协调发展的主体单元。本文综合考虑城市群的网络与层级性特征,运用城市流刻画城际网络交互作用,采用分层广义线性模型(HGLM)揭示城市群分层驱动机制。同时,选取长江中游城市群开展实证研究,通过与元胞自动机(CA)耦合,构建HGLM-CA模型模拟城市群空间扩展。将模拟结果与Logistic-CA模型、BBO-CA模型进行比对,据此评析HGLM-CA模型的优劣与改进方向。实证结果表明:城市群空间扩展是多层驱动因素共同作用的结果,城市流不仅会推动城市群空间扩展,而且对元胞层因素起到重要的调节作用,使之具有城际分异性;HGLM-CA模型相比Logistic-CA模型模拟精度更高,说明顾及城市流与层级性的城市群空间扩展模拟结果更为精准;与智能模型BBO-CA相比,HGLM-CA模型模拟精度较低,但其便于从层级性角度把握城市群空间扩展机制。
王海军, 武悦, 邓羽, 徐姗. 基于城市流和层级性的城市群扩展模型构建[J]. 地理学报, 2021, 76(12): 3012-3024.
WANG Haijun, WU Yue, DENG Yu, XU Shan. Model construction of urban agglomeration expansion simulation considering urban flow and hierarchical characteristics[J]. Acta Geographica Sinica, 2021, 76(12): 3012-3024.
表1
主要数据来源与处理
数据名称 | 数据说明 | 数据来源 |
---|---|---|
土地利用数据 | 城市区域不透水面数据,利用不透水表面映射算法和GEE得到,分辨率为30 m×30 m,将不透水面视为城市用地,其他为非城市用地,重采样为90 m×90 m | 由清华大学宫鹏等[ |
道路数据 | 包括铁路、高速公路、国道在内的shp格式数据 | 中国科学院资源环境科学与数据中心( |
DEM数据 | 基于最新的SRTM V4.1数据经整理拼接生成,分辨率为90 m×90 m | 中国科学院资源环境科学与数据中心( |
城市流数据 | 根据统计年鉴数据与时空地理大数据,分别构建经济流、人口流、交通流、信息流模型[ | 见参考文献[ |
表3
HGLM变量参数识别结果
系数 | P值 | 系数 | P值 | ||
---|---|---|---|---|---|
截距: | 控制变量: | ||||
level 1截距β0 | 高程 | ||||
截距γ00 | -1.429 | 0.000 | 截距γ40 | -0.592 | 0.000 |
城市流γ01 | 0.947 | 0.000 | 坡度 | ||
自变量: | 截距γ50 | -1.764 | 0.000 | ||
距市中心距离β1 | 距水域距离 | ||||
截距γ10 | -3.261 | 0.000 | 截距γ60 | 0.313 | 0.315 |
城市流γ11 | -8.176 | 0.000 | 距国道距离 | ||
距区县中心距离β2 | 截距γ70 | -0.486 | 0.111 | ||
截距γ20 | -1.899 | 0.001 | 距高速距离 | ||
城市流γ21 | -1.790 | 0.206 | 截距γ80 | -0.297 | 0.391 |
距铁路距离β3 | |||||
截距γ30 | -1.338 | 0.048 | |||
城市流γ31 | 4.752 | 0.021 |
表4
2017年长江中游城市群空间扩展模型模拟精度对比
HGLM-CA | Logistic-CA | BBO-CA | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
OA | Kappa | FoM | OA | Kappa | FoM | OA | Kappa | FoM | ||||
整体精度 | 城市群 | 0.99436 | 0.79872 | 0.18085 | 0.99427 | 0.79574 | 0.17374 | 0.99455 | 0.80567 | 0.19779 | ||
分区精度 | 武汉市 | 0.95525 | 0.78844 | 0.14126 | 0.93924 | 0.74020 | 0.18817 | 0.94952 | 0.77246 | 0.18303 | ||
黄石市 | 0.97859 | 0.81788 | 0.17746 | 0.98138 | 0.83651 | 0.16789 | 0.98146 | 0.83816 | 0.18391 | |||
宜昌市 | 0.99445 | 0.78486 | 0.20519 | 0.99461 | 0.78646 | 0.18571 | 0.99448 | 0.78702 | 0.21576 | |||
襄阳市 | 0.99498 | 0.82902 | 0.15516 | 0.99514 | 0.82517 | 0.03963 | 0.99475 | 0.82610 | 0.19173 | |||
鄂州市 | 0.94591 | 0.69046 | 0.14923 | 0.95070 | 0.70959 | 0.15293 | 0.96023 | 0.75093 | 0.16121 | |||
荆门市 | 0.99516 | 0.82205 | 0.11262 | 0.99563 | 0.83010 | 0.01952 | 0.99485 | 0.81586 | 0.14256 | |||
孝感市 | 0.98711 | 0.77240 | 0.17225 | 0.98773 | 0.77889 | 0.16251 | 0.98763 | 0.77942 | 0.17561 | |||
荆州市 | 0.99185 | 0.78990 | 0.15924 | 0.99196 | 0.79076 | 0.14808 | 0.99238 | 0.80328 | 0.18866 | |||
黄冈市 | 0.99170 | 0.76696 | 0.15049 | 0.99208 | 0.77326 | 0.14080 | 0.99192 | 0.77603 | 0.18343 | |||
咸宁市 | 0.99392 | 0.82252 | 0.12214 | 0.99464 | 0.83704 | 0.08533 | 0.99347 | 0.81337 | 0.13292 | |||
仙桃市 | 0.99208 | 0.83366 | 0.00041 | 0.99204 | 0.83445 | 0.02894 | 0.99065 | 0.82169 | 0.16428 | |||
潜江市 | 0.98856 | 0.81205 | 0.04288 | 0.98857 | 0.81206 | 0.04001 | 0.98702 | 0.80615 | 0.18890 | |||
天门市 | 0.99343 | 0.79276 | 0.01163 | 0.99346 | 0.79249 | 0.00210 | 0.99301 | 0.80157 | 0.19527 | |||
长沙市 | 0.97542 | 0.79792 | 0.19991 | 0.97230 | 0.78174 | 0.21561 | 0.97574 | 0.80148 | 0.21485 | |||
株洲市 | 0.98999 | 0.77736 | 0.18150 | 0.99006 | 0.77920 | 0.18720 | 0.99081 | 0.79106 | 0.18815 | |||
湘潭市 | 0.97724 | 0.75437 | 0.21572 | 0.97718 | 0.75427 | 0.21746 | 0.98161 | 0.78615 | 0.20658 | |||
衡阳市 | 0.99068 | 0.77667 | 0.20602 | 0.99089 | 0.78041 | 0.20796 | 0.99141 | 0.78814 | 0.20171 | |||
岳阳市 | 0.99359 | 0.81224 | 0.14242 | 0.99422 | 0.82528 | 0.12560 | 0.99355 | 0.81314 | 0.16095 | |||
常德市 | 0.99417 | 0.78845 | 0.17407 | 0.99461 | 0.79653 | 0.14288 | 0.99435 | 0.79537 | 0.19085 | |||
益阳市 | 0.99511 | 0.78612 | 0.18180 | 0.99544 | 0.79554 | 0.17560 | 0.99578 | 0.80790 | 0.18663 | |||
娄底市 | 0.99284 | 0.80869 | 0.19307 | 0.99392 | 0.82569 | 0.13254 | 0.99350 | 0.82162 | 0.19003 | |||
南昌市 | 0.96873 | 0.79236 | 0.25293 | 0.96683 | 0.78406 | 0.25614 | 0.97187 | 0.80732 | 0.25144 | |||
景德镇 | 0.98913 | 0.79545 | 0.27337 | 0.98991 | 0.80425 | 0.26468 | 0.99082 | 0.81581 | 0.25770 | |||
萍乡市 | 0.98945 | 0.79041 | 0.17084 | 0.99075 | 0.79585 | 0.01749 | 0.98967 | 0.79303 | 0.16650 | |||
九江市 | 0.99296 | 0.80933 | 0.21376 | 0.99308 | 0.81093 | 0.20696 | 0.99303 | 0.81233 | 0.22926 | |||
新余市 | 0.98812 | 0.85138 | 0.27223 | 0.99066 | 0.86902 | 0.09938 | 0.98876 | 0.85730 | 0.26929 | |||
鹰潭市 | 0.98118 | 0.73188 | 0.23667 | 0.98301 | 0.74787 | 0.23628 | 0.98613 | 0.77889 | 0.23856 | |||
吉安市 | 0.99532 | 0.77351 | 0.20956 | 0.99562 | 0.78092 | 0.19306 | 0.99591 | 0.79410 | 0.21761 | |||
宜春市 | 0.99310 | 0.81064 | 0.12226 | 0.99302 | 0.80679 | 0.09893 | 0.99240 | 0.80345 | 0.18943 | |||
抚州市 | 0.99558 | 0.80872 | 0.17760 | 0.99598 | 0.81430 | 0.09066 | 0.99566 | 0.81252 | 0.19129 | |||
上饶市 | 0.99397 | 0.79382 | 0.16224 | 0.99446 | 0.80489 | 0.14914 | 0.99459 | 0.81160 | 0.18193 |
[1] | Wang Haijun, Xia Chang, Liu Xiaoping, et al. Theoretical and methodological perspectives of fine-scale urban expansion cellular automata for the large regions. Geography and Geo-Information Science, 2016, 32(5): 1-8. |
[王海军, 夏畅, 刘小平, 等. 大尺度和精细化城市扩展CA的理论与方法探讨. 地理与地理信息科学, 2016, 32(5): 1-8.] | |
[2] |
Fang Chuanglin. Progress and the future direction of research into urban agglomeration in China. Acta Geographica Sinica, 2014, 69(8): 1130-1144.
doi: 10.11821/dlxb201408009 |
[方创琳. 中国城市群研究取得的重要进展与未来发展方向. 地理学报, 2014, 69(8): 1130-1144.] | |
[3] | Zhang Yongsheng. Promoting China's green urbanization based on ecological civilization. China Population, Resources and Environment, 2020, 30(10): 19-27. |
[张永生. 基于生态文明推进中国绿色城镇化转型. 中国人口·资源与环境, 2020, 30(10): 19-27.] | |
[4] |
Wu H, Li Z, Clarke K C, et al. Examining the sensitivity of spatial scale in cellular automata Markov chain simulation of land use change. International Journal of Geographical Information Science, 2019, 33(5): 1040-1061.
doi: 10.1080/13658816.2019.1568441 |
[5] |
Tobler W R. A computer movie simulating urban growth in the Detroit region. Economic Geography, 1970, 46(Suppl.1): 234-240.
doi: 10.2307/143141 |
[6] |
Couclelis H. Cellular worlds: A framework for modeling micro-macro dynamics. Environment and Planning A: Economy and Space, 1985, 17(5): 585-596.
doi: 10.1068/a170585 |
[7] |
Couclelis H. Macrostructure and microbehavior in a metropolitan area. Environment and Planning B: Planning and Design, 1989, 16(2): 141-154.
doi: 10.1068/b160141 |
[8] |
Luijten J C. A systematic method for generating land use patterns using stochastic rules and basic landscape characteristics: Results for a Colombian hillside watershed. Agriculture, Ecosystems & Environment, 2003, 95(2-3): 427-441.
doi: 10.1016/S0167-8809(02)00219-0 |
[9] |
Wu F L, Yeh A G O. Changing spatial distribution and determinants of land development in Chinese cities in the transition from a centrally planned economy to a socialist market economy: A case study of Guangzhou. Urban Studies, 1997, 34(11): 1851-1879.
doi: 10.1080/0042098975286 |
[10] | Yang Qingsheng, Li Xia. Integration of multi-agent systems with cellular automata for simulating urban land expansion. Scientia Geographica Sinica, 2007, 27(4): 542-548. |
[杨青生, 黎夏. 多智能体与元胞自动机结合及城市用地扩张模拟. 地理科学, 2007, 27(4): 542-548.] | |
[11] | Li Xia, Ye Jiaan. Neural-network-based cellular automata for realistic and idealized urban simulation. Acta Geographica Sinica, 2002, 57(2): 159-166. |
[黎夏, 叶嘉安. 基于神经网络的单元自动机CA及真实和优化的城市模拟. 地理学报, 2002, 57(2): 159-166.] | |
[12] | Xie Zhiwen, Wang Haijun, Zhang Bin, et al. Urban expansion cellular automata model based on multi-structures convolutional neural networks. Acta Geodaetica et Cartographica Sinica, 2020, 49(3): 375-385. |
[谢志文, 王海军, 张彬, 等. 城市扩展元胞自动机多结构卷积神经网络模型. 测绘学报, 2020, 49(3): 375-385.] | |
[13] |
Wang H J, Zhang B, Xia C, et al. Using a maximum entropy model to optimize the stochastic component of urban cellular automata models. International Journal of Geographical Information Science, 2020, 34(5): 924-946.
doi: 10.1080/13658816.2019.1687898 |
[14] |
Zhang B, Wang H J, He S W, et al. Analyzing the effects of stochastic perturbation and fuzzy distance transformation on Wuhan urban growth simulation. Transactions in GIS, 2020, 24(6): 1779-1798.
doi: 10.1111/tgis.v24.6 |
[15] | Wang Haijun, Xia Chang, Zhang Anqi, et al. Calibrating urban expansion cellular automata using biogeography-based optimization. Geomatics and Information Science of Wuhan University, 2017, 42(9): 1323-1329. |
[王海军, 夏畅, 张安琪, 等. 利用生物地理学优化算法获取城市扩展元胞自动机模型参数. 武汉大学学报(信息科学版), 2017, 42(9): 1323-1329.] | |
[16] |
Wu Kang, Fang Chuanglin, Zhao Miaoxi. The spatial organization and structure complexity of Chinese intercity networks. Geographical Research, 2015, 34(4): 711-728.
doi: 10.11821/dlyj201504010 |
[吴康, 方创琳, 赵渺希. 中国城市网络的空间组织及其复杂性结构特征. 地理研究, 2015, 34(4): 711-728.] | |
[17] |
Zhang Kaihuang, Qian Qinglan, Yang Qingsheng. An analysis of multilevel variables influencing China's land urbanization process. Acta Geographica Sinica, 2020, 75(1): 179-193.
doi: 10.11821/dlxb202001013 |
[张凯煌, 千庆兰, 杨青生. 中国城市土地城镇化多层级影响因素分析. 地理学报, 2020, 75(1): 179-193.] | |
[18] | He Jianhua, Shi Xuan, Gong Jian, et al. Modeling the spatial expansion of urban agglomeration considering their spatial interaction: A case study of Wuhan metropolitan area. Geomatics and Information Science of Wuhan University, 2016, 41(4): 462-467. |
[何建华, 施璇, 龚健, 等. 顾及空间交互作用的城市群联动空间增长模拟: 以武汉都市区为例. 武汉大学学报(信息科学版), 2016, 41(4): 462-467.] | |
[19] | He Li, Liu Yaolin. Simulating urban cooperative expansion in the metropolitan region based on improved CA model: A case study of Wuhan Urban Agglomeration, China. Journal of Central China Normal University, 2017, 51(2): 224-230. |
[何力, 刘耀林. 基于城市流模型的城市群扩张模拟: 以武汉城市圈为例. 华中师范大学学报(自然科学版), 2017, 51(2): 224-230.] | |
[20] |
Xia C, Zhang A Q, Wang H J, et al. Modeling urban growth in a metropolitan area based on bidirectional flows, an improved gravitational field model, and partitioned cellular automata. International Journal of Geographical Information Science, 2019, 33(5): 877-899.
doi: 10.1080/13658816.2018.1562067 |
[21] |
Xia C, Zhang A Q, Wang H J, et al. Delineating early warning zones in rapidly growing metropolitan areas by integrating a multiscale urban growth model with biogeography-based optimization. Land Use Policy, 2020, 90: 104332. DOI: 10.1016/j.landusepol.2019.104332.
doi: 10.1016/j.landusepol.2019.104332 |
[22] |
Chen Y M, Li X, Liu X P, et al. Tele-connecting China's future urban growth to impacts on ecosystem services under the shared socioeconomic pathways. Science of the Total Environment, 2019, 652: 765-779.
doi: 10.1016/j.scitotenv.2018.10.283 |
[23] |
Sun Yizhong, Yang Jing, Song Shuying, et al. Modeling of multilevel vector cellular automata and its simulation of land use change. Acta Geographica Sinica, 2020, 75(10): 2164-2179.
doi: 10.11821/dlxb202010009 |
[孙毅中, 杨静, 宋书颖, 等. 多层次矢量元胞自动机建模及土地利用变化模拟. 地理学报, 2020, 75(10): 2164-2179.] | |
[24] |
Shu B R, Zhu S H, Qu Y, et al. Modelling multi-regional urban growth with multilevel logistic cellular automata. Computers. Environment and Urban Systems, 2020, 80: 101457. DOI: 10.1016/j.compenvurbsys.2019.101457.
doi: 10.1016/j.compenvurbsys.2019.101457 |
[25] | Li Xueyan, Xin Tao. Hierarchical linear model for binary data: Principle and application. Psychological Development and Education, 2006, 22(4): 97-102. |
[李雪燕, 辛涛. 二分数据的多层线性模型: 原理与应用. 心理发展与教育, 2006, 22(4): 97-102.] | |
[26] | Hox J. Multilevel Modeling: When and Why. Berlin: Springer Berlin Heidelberg, 1999. |
[27] | Lei Li, Zhang Lei. Principle and application of the hierarchical linear model. Journal of Capital Normal University (Social Sciences Edition), 2002(2): 110-114. |
[雷雳, 张雷. 多层线性模型的原理及应用. 首都师范大学学报(社会科学版), 2002(2): 110-114.] | |
[28] | Li Xia, Ye Jiaan. Geographical Simulation System: Cellular Automata and Multi-Agent System. Beijing: Science Press, 2007: 43-46. |
[黎夏, 叶嘉安. 地理模拟系统: 元胞自动机与多智能体. 北京: 科学出版社, 2007: 43-46.] | |
[29] | Wuhan Statistical Bureau. 2019 Statistical bulletin of the national economic and social development of Wuhan Province. www.wuhan.gov.cn/zwgk/tzgg, 2020-03-29(06). |
[Wuhan Statistical Bureau. 2019年武汉市国民经济和社会发展统计公报. www.wuhan.gov.cn/zwgk/tzgg, 2020-03-29(06).] | |
[30] |
Gong P, Li X C, Zhang W. 40-Year (1978-2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing. Science Bulletin, 2019, 64(11): 756-763.
doi: 10.1016/j.scib.2019.04.024 |
[31] | Zhai Lijun. Urban spatial connection and function of urban agglomeration in the middle reaches of Yangtze River[D]. Wuhan: Wuhan University, 2019. |
[翟丽君. 长江中游城市群城际空间联系和功能分析[D]. 武汉: 武汉大学, 2019.] | |
[32] | Wang Haijun, Zhai Lijun, Liu Yanfang, et al. Urban connection and function in Wuhan urban agglomeration based on multi-dimensional urban factor flows. Economic Geography, 2018, 38(7): 50-58. |
[王海军, 翟丽君, 刘艳芳, 等. 基于多维城市要素流的武汉城市圈城市联系与功能分析. 经济地理, 2018, 38(7): 50-58.] | |
[33] |
Wang Haijun, Zhang Bin, Liu Yaolin, et al. Multi-dimensional analysis of urban expansion patterns and their driving forces based on the center of gravity-GTWR model: A case study of the Beijing-Tianjin-Hebei urban agglomeration. Acta Geographica Sinica, 2018, 73(6): 1076-1092.
doi: 10.11821/dlxb201806007 |
[王海军, 张彬, 刘耀林, 等. 基于重心-GTWR模型的京津冀城市群城镇扩展格局与驱动力多维解析. 地理学报, 2018, 73(6): 1076-1092.] |
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