基于ANN-CA的城市用地扩张模拟优化——以潍坊市城区为例
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摘要
随着城市规模的不断扩大,土地覆盖和利用的格局发生了显著改变,利用神经网络—元胞自动机模型(ANN-CA)模拟预测未来城市用地变化,可为城市整体规划和布局提供依据。文章以潍坊市城区为例,采用地理模拟优化系统集成的ANN-CA模型,利用宏观规划方案对其进行优化,分别模拟了潍坊市城区2005、2011、2017年土地利用状况,并预测了2025年的土地利用状况。结果表明:2005至2017年期间,潍坊城区空闲用地面积减少,居住用地、城市道路用地面积增加,城市发展中心向城市北部偏移;优化后的模拟结果精度明显提高,说明加入宏观规划因子在一定程度上弥补ANN-CA模拟的不足;预测至2025年,潍坊城区居住、工矿用地和交通运输地面积将会继续增加,而绿地和空闲用地面积则会继续缩小。
With the urban scale expanding, the land cover and land use are significantly changed. By using ANN-CA to simulate the urban expansion, the reference basis can be provided for the overall city plan and pattern. Based on the ANN-CA model that integrated in GeoSOS and optimized based on the macro-planning scheme, this paper simulates the land use status of Weifang City in 2005, 2011 and 2017, and predicts the land use status of the study area in 2025. The results show that from 2005 to 2017, the area of unused land in Weifang City decreased. The area of residential land and urban roads increased, and the urban development center shifted to the north of the city. The accuracy of the optimized simulation results is significantly improved indicating that the macro-planning factor could be introduced. To some extent, it compensates for the shortcomings of ANN-CA simulation. The simulation results show that the land use change in Weifang City is still significant from 2017 to 2025. The area of residential, industrial and mining land and transportation areas continues to increase, and the area of green space and unused land continues to shrink.
With the urban scale expanding, the land cover and land use are significantly changed. By using ANN-CA to simulate the urban expansion, the reference basis can be provided for the overall city plan and pattern. Based on the ANN-CA model that integrated in GeoSOS and optimized based on the macro-planning scheme, this paper simulates the land use status of Weifang City in 2005, 2011 and 2017, and predicts the land use status of the study area in 2025. The results show that from 2005 to 2017, the area of unused land in Weifang City decreased. The area of residential land and urban roads increased, and the urban development center shifted to the north of the city. The accuracy of the optimized simulation results is significantly improved indicating that the macro-planning factor could be introduced. To some extent, it compensates for the shortcomings of ANN-CA simulation. The simulation results show that the land use change in Weifang City is still significant from 2017 to 2025. The area of residential, industrial and mining land and transportation areas continues to increase, and the area of green space and unused land continues to shrink.
引文
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[25] Pontius R G,Boersma W,Castella J C ,et al.Comparing the input,output,and validation maps for several models of land change[J].The Annals of Regional Science,2008,42(1):11-37.
[2] 张昌良.中国特色城市化道路——中小城市发展研究[J].河南社会科学,2008,16(4):76-77.
[3] 黄颖.基于遥感与景观指数的土地利用/覆盖变化及格局分析[D].长沙:中南大学,2007.
[4] 胡雪丽,徐凌,张树深.基于CA-Markov模型和多目标优化的大连市土地利用格局[J].应用生态学报,2013,24(6):1652-1660.
[5] 肖琳,田光进.天津城市扩展空间模式与驱动机制研究[J].资源科学,2014,36(7):1327-1335.
[6] 周成虎.地理元胞自动机研究[M].北京:科学出版社,1999.
[7] 黎夏.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.
[8] 冯永玖,童小华,刘妙龙,等.基于GIS的地理元胞自动机模拟框架及其应用[J].地理与地理信息科学,2010,26(1):41-43.
[9] 杨俊,解鹏,席建超,等.基于元胞自动机模型的土地利用变化模拟——以大连经济技术开发区为例[J].地理学报,2015,70(3):461-475.
[10] 黎夏,李丹,刘小平,等.地理模拟优化系统GeoSOS及前沿研究[J].地球科学进展,2009,24(8):899-907.
[11] Gharbia S S,Alfatah S A,Gill L,et al.Land use scenarios and projections simulation using an integrated GIS cellular automata algorithms[J].Modeling Earth Systems and Environment,2016,2:151.
[12] 黎夏,刘小平,何晋强,等.基于耦合的地理模拟优化系统[J].地理学报,2009,64(8):1009-1018.
[13] 黎夏,叶嘉安.基于神经网络的单元自动机CA及真实和忧化的城市模拟[J].地理学报,2002,57(2):159-166.
[14] Wu F L.Calibration of stochastic cellular automata:The application to rural-urban land conversions[J].International Journal of Geographical Information Science,2002,16(8):795-818.
[15] Li X,Yeh G A.Data mining of cellular automata’s transition rules[J].International Journal of Geographical Information Systems,2004,18(8):723-744.
[16] 陈逸敏,黎夏,刘小平,等.基于耦合地理模拟优化系统GeoSOS的农田保护区预警[J].地理学报,2010,65(9):1137-1145.
[17] 管超,哈斯.基于GeoSOS的城市扩展模拟——以旅顺口区为例[J].测绘与空间地理信息,2014(3):49-54.
[18] 夏南凯,陈晶莹.土地政策对城市空间的影响分析——以上海市为例[C].昆明:2012中国城市规划年会,2012:1-13.
[19] 李秉仁.试论城市规划在优化城市土地资源配置中的作用[J].城乡建设,1995(5):14-16.
[20] GB/T 21010—2017,土地利用现状分类 [S].北京:中国标准出版社,2017.
[21] 潍坊市自然资源与规划局.潍坊市土地利用总体规划(2006-2020)[EB/OL].(2018-03-29)[2019-05-07].http://www.wfdlr.gov.cn/ zwgk/ghjh.
[22] 潍坊国土资源局.潍坊市中心城区停车场专项规划[EB/OL].(2018-03-29) [2019-05-07].http://zyhgh.weifang.gov.cn/ghgb/201903/t201903265323532.html.
[23] 常琼玉,窦剑军.两个空间变量空间相关性的分析[J].统计学与应用,2016,5(4):397-403.
[24] Congalton R G,Mead R A.A quantitative method to test for consistency and correctness in photointerpretation[J].Photogrammetric Engineering and Remote Sensing,1983,49(1):69-74.
[25] Pontius R G,Boersma W,Castella J C ,et al.Comparing the input,output,and validation maps for several models of land change[J].The Annals of Regional Science,2008,42(1):11-37.
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