基于CA-ABM模型的福州城市用地扩张研究
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摘要
以中国海西地区重要门户福州市为研究区,结合其地理位置多层次约束性条件,以地理加权回归模型作为元胞自动机(CA)层的转换规则,同时以2000-2015年多期Landsat TM/ETM+影像的城市用地情况为参照,借助GIS空间分析技术,对CA和多智能体(ABM)相耦合的城市用地扩张模型进行改进。然后利用传统的和改进后的CAABM模型,多角度、多层次地模拟福州市2000年、2005年、2010年、2015年城市用地扩张在微观格局上的变化。结果表明,传统的和改进后的CA-ABM模型的整体精度均在80%以上,模拟结果具有较强的可信度;改进的CAABM模型模拟的点对点总体精度和Kappa系数均高于传统的CA-ABM模型,而且模拟结果更加接近实际的城市用地扩张分布情况。结论可为平衡城市化进程和合理规划城市用地提供重要的理论技术支撑。
Fuzhou City is an important gateway west of the South China Sea. This study uses geographically weighted regression(GWR) as the transformation rules of cellular automata(CA) layer based on the multi-level constraint conditions, taking into account geographical location, natural factors, and the multi-criteria and willingness of various agents to make decisions on environmental change, to simulate urban land expansion of Fuzhou City from 2000 to 2015. Using the urban land use data derived from remote sensing imageries of Fuzhou City in 2000–2015 as a reference, and with the help of GIS spatial analysis technology, this study developed an improved model of urban land expansion based on coupled CA and ABM. The traditional and improved CAABM models were used to simulate urban land expansion and change with a microscopic view for Fuzhou City in 2000, 2005, 2010, and 2015 from multiple angles and at multiple levels. The results show that the overall accuracy of the traditional and improved CA-ABM models was higher than 80%, and the simulation results based on the CA-ABM models for Fuzhou City are reliable. The point-to-point overall accuracy and Kappa of the improved CA-ABM model were higher than the traditional CA-ABM model, and the results of the improved CA-ABM model were closer to the actual distribution of urban land expansion in Fuzhou. It indicates that the improved CA-ABM model can be used to simulate urban land expansion, more accurately expresses a variety of geographic processes and mechanisms, and improves the reliability and stability of the simulation results.Finally, a forecast of the distribution of urban land expansion in 2020 and 2030 based on the improved CA-ABM model with scenario natural, economic, and social developments in Fuzhou provides an important theoretical and technical support for the urban land use planning of the city.
Fuzhou City is an important gateway west of the South China Sea. This study uses geographically weighted regression(GWR) as the transformation rules of cellular automata(CA) layer based on the multi-level constraint conditions, taking into account geographical location, natural factors, and the multi-criteria and willingness of various agents to make decisions on environmental change, to simulate urban land expansion of Fuzhou City from 2000 to 2015. Using the urban land use data derived from remote sensing imageries of Fuzhou City in 2000–2015 as a reference, and with the help of GIS spatial analysis technology, this study developed an improved model of urban land expansion based on coupled CA and ABM. The traditional and improved CAABM models were used to simulate urban land expansion and change with a microscopic view for Fuzhou City in 2000, 2005, 2010, and 2015 from multiple angles and at multiple levels. The results show that the overall accuracy of the traditional and improved CA-ABM models was higher than 80%, and the simulation results based on the CA-ABM models for Fuzhou City are reliable. The point-to-point overall accuracy and Kappa of the improved CA-ABM model were higher than the traditional CA-ABM model, and the results of the improved CA-ABM model were closer to the actual distribution of urban land expansion in Fuzhou. It indicates that the improved CA-ABM model can be used to simulate urban land expansion, more accurately expresses a variety of geographic processes and mechanisms, and improves the reliability and stability of the simulation results.Finally, a forecast of the distribution of urban land expansion in 2020 and 2030 based on the improved CA-ABM model with scenario natural, economic, and social developments in Fuzhou provides an important theoretical and technical support for the urban land use planning of the city.
引文
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廖江福,唐立娜,王翠平,等.2014.城市元胞自动机扩展邻域效应的测量与校准研究[J].地理科学进展,33(12)1624-1633.[Liao J F,Tang L N,Wang C P,et al.2014Measuring and calibrating extended neighborhood effec of urban cellular automata model based on particle swarm optimization[J].Progress in Geography,33(12):16241633.]
刘小平,黎夏,艾彬,等.2006.基于多智能体的土地利用模拟与规划模型[J].地理学报,61(10):1101-1112.[Liu X PLi X,Ai B,et al.2006.Multi-agent systems for simulating and planning land use development[J].Acta Geographic Sinica,61(10):1101-1112.]
牛文元.2009.中国新型城市化报告:2009[M].北京:科学出版社.[Niu W Y.2009.China's new-urbanization report2009[M].Beijing,China:Science Press.]
汪光焘.2014.中国城市状况报告:2014/2015[M].北京:中国城市出版社.[Wang G T.2014.An introduction of urban status in China:2014/2015[M].Beijing,China:China City Press.]
汪锐良.2013.基于ABM的城市扩张、耕地保护与湿地流失的模拟研究:以杭州市萧山区为例[D].杭州:浙江大学[Wang R L.2013.Research on simulation of urban expan sion,cultivated land protection and wetland loss based on Agent-based model:A study of Xiaoshan[D].Hangzhou China:Zhejiang University.]
王贞超.2012.基于GIS和MAS的城市用地扩展模拟研究[D].南京:南京大学.[Wang Z C.2012.Study of simula tion for urban land expansion based on GIS and MAS[D]Nanjing,China:Nanjing University.]
肖琳,田光进,乔治.2014.基于Agent的城市扩张占用耕地动态模型及模拟[J].自然资源学报,29(3):516-527[Xiao L,Tian G J,Qiao Z.2014.An agent-based approach for urban encroachment on cropland dynamic model and simulation[J].Journal of Natural Resources,29(3):516527.]
徐新良,赵美艳,闵稀碧.2014.城市扩展研究的主要进展与展望[J].生态科学,33(3):619-624.[Xu X L,Zhao M YMin X B.2014.Main progress and prospect of urban ex pansion study[J].Ecological Science,33(3):619-624.]
杨青生,黎夏.2007a.多智能体与元胞自动机结合及城市用地扩张模拟[J].地理科学,27(4):542-548.[Yang Q S,LX.2007.Integration of multi-agent systems with cellula automata for simulating urban land expansion[J].Scienti Geographica Sinica,27(4):542-548.]
杨青生,黎夏.2007b.基于遗传算法自动获取CA模型的参数:以东莞市城市发展模拟为例[J].地理研究,26(2)229-237.[Yang Q S,Li X.2007.Calibrating urban cellula automata using genetic algorithms[J].Geographical Re search,26(2):229-237.]
翟瑞雪.2015.基于多主体模型的城市扩张模拟研究:以赣州市章贡区为例[D].北京:中国科学院大学.[Zhai R X2015.Research on simulation of urban expansion based on multi-agent model:A case study in Zhanggong District Ganzhou City[D].Beijing,China:University of Chines Academy of Sciences.]
张鸿辉,曾永年,刘慧敏.2011a.多目标土地利用空间优化配置模型及其应用[J].中南大学学报:自然科学版,42(4)1056-1065.[Zhang H H,Zeng Y N,Liu H M.2011.Multi objective spatial optimization model for land use alloca tion and its application[J].Journal of Central South Univer sity:Science and Technology,42(4):1056-1065.]
张鸿辉,曾永年,谭荣.2011b.基于多智能体的农地非农化时空模拟与规划模型[J].测绘学报,40(3):366-372[Zhang H H,Zeng Y N,Tan R.2011.A spatio-tempora simulation and planning model for farmland conversion based on multi-agent systems[J].Acta Geodaetica et Carto graphica Sinica,40(3):366-372.]
张鸿辉,曾永年,谭荣,等.2011c.多智能体区域土地利用优化配置模型及其应用[J].地理学报,66(7):972-984[Zhang H H,Zeng Y N,Tan R,et al.2011.A model for re gional land use optimization allocation based on multi agent system and its application[J].Acta Geographica Sini ca,66(7):972-984.]
张云堂.2014.基于CA与ABM的城市居住用地扩张微观驱动机理模拟:以杭州市为例[D].杭州:浙江大学,2014[Zhang Y T.2014.Research on simulation of urban resi dential land expansion's microscopic drive mechanism based on CA and Agent-based model:A case study o Hangzhou[D].Hangzhou,China:Zhejiang University.]
Angela S,Parent J,Civco D L,et al.2011.The dimensions o global urban expansion:Estimates and projections for al countries,2000-2050[J].Progress in Planning,75(2):53107.
Basse R M,Omrani H,Charif O,et al.2014.Land use chang es modelling using advanced methods:Cellular automat and artificial neural networks.The spatial and explicit rep resentation of land cover dynamics at the cross-border re gion scale[J].Applied Geography,53:160-171.
Liu Y L,He Q S,Tan R H,et al.2016.Modeling different ur ban growth patterns based on the evolution of urban form A case study from Huangpi,Central China[J].Applied Ge ography,66:109-118.
Rienow A,Stenger D.2014.Geosimulation of urban growth and demographic decline in the Ruhr:A case study fo2025 using the artificial intelligence of cells and agents[J]Journal of Geographical Systems,16(3):311-342.
Tian G J,Qiao Z.2014.Modeling urban expansion policy sce narios using an agent-based approach for Guangzhou Met ropolitan Region of China[J].Ecology and Society,19(3)52.
Tsai Y,Zia A,Koliba C,et al.2015.An interactive land us transition agent-based model(ILUTABM):Endogenizing human-environment interactions in the Western Missisquo Watershed[J].Land Use Policy,49:161-176.
Wahyudi A,Liu Y.2015.Spatial dynamic models for inclusiv cities:A brief concept of cellular automata(CA)and agent based model(ABM)[J].Journal Perencanaan Wilayah dan Kota,26(1):54-70.
Wei Y D,Ye X Y.2014.Urbanization,urban land expansion and environmental change in China[J].Stochastic Environ mental Research and Risk Assessment,28(4):757-765.
李新东,王立娜,郭伟立,等.2016.基于RS和GIS的北海市城市空间扩展监测分析[J].测绘与空间地理信息,39(1)97-99.[Li X D,Wang L N,Guo W L,et al.2016.Charac teristic monitor and analysis of spatial expansion of Beiha city based on RS and GIS[J].Geomatics&Spatial Infor mation Technology,39(1):97-99.]
廖江福,唐立娜,王翠平,等.2014.城市元胞自动机扩展邻域效应的测量与校准研究[J].地理科学进展,33(12)1624-1633.[Liao J F,Tang L N,Wang C P,et al.2014Measuring and calibrating extended neighborhood effec of urban cellular automata model based on particle swarm optimization[J].Progress in Geography,33(12):16241633.]
刘小平,黎夏,艾彬,等.2006.基于多智能体的土地利用模拟与规划模型[J].地理学报,61(10):1101-1112.[Liu X PLi X,Ai B,et al.2006.Multi-agent systems for simulating and planning land use development[J].Acta Geographic Sinica,61(10):1101-1112.]
牛文元.2009.中国新型城市化报告:2009[M].北京:科学出版社.[Niu W Y.2009.China's new-urbanization report2009[M].Beijing,China:Science Press.]
汪光焘.2014.中国城市状况报告:2014/2015[M].北京:中国城市出版社.[Wang G T.2014.An introduction of urban status in China:2014/2015[M].Beijing,China:China City Press.]
汪锐良.2013.基于ABM的城市扩张、耕地保护与湿地流失的模拟研究:以杭州市萧山区为例[D].杭州:浙江大学[Wang R L.2013.Research on simulation of urban expan sion,cultivated land protection and wetland loss based on Agent-based model:A study of Xiaoshan[D].Hangzhou China:Zhejiang University.]
王贞超.2012.基于GIS和MAS的城市用地扩展模拟研究[D].南京:南京大学.[Wang Z C.2012.Study of simula tion for urban land expansion based on GIS and MAS[D]Nanjing,China:Nanjing University.]
肖琳,田光进,乔治.2014.基于Agent的城市扩张占用耕地动态模型及模拟[J].自然资源学报,29(3):516-527[Xiao L,Tian G J,Qiao Z.2014.An agent-based approach for urban encroachment on cropland dynamic model and simulation[J].Journal of Natural Resources,29(3):516527.]
徐新良,赵美艳,闵稀碧.2014.城市扩展研究的主要进展与展望[J].生态科学,33(3):619-624.[Xu X L,Zhao M YMin X B.2014.Main progress and prospect of urban ex pansion study[J].Ecological Science,33(3):619-624.]
杨青生,黎夏.2007a.多智能体与元胞自动机结合及城市用地扩张模拟[J].地理科学,27(4):542-548.[Yang Q S,LX.2007.Integration of multi-agent systems with cellula automata for simulating urban land expansion[J].Scienti Geographica Sinica,27(4):542-548.]
杨青生,黎夏.2007b.基于遗传算法自动获取CA模型的参数:以东莞市城市发展模拟为例[J].地理研究,26(2)229-237.[Yang Q S,Li X.2007.Calibrating urban cellula automata using genetic algorithms[J].Geographical Re search,26(2):229-237.]
翟瑞雪.2015.基于多主体模型的城市扩张模拟研究:以赣州市章贡区为例[D].北京:中国科学院大学.[Zhai R X2015.Research on simulation of urban expansion based on multi-agent model:A case study in Zhanggong District Ganzhou City[D].Beijing,China:University of Chines Academy of Sciences.]
张鸿辉,曾永年,刘慧敏.2011a.多目标土地利用空间优化配置模型及其应用[J].中南大学学报:自然科学版,42(4)1056-1065.[Zhang H H,Zeng Y N,Liu H M.2011.Multi objective spatial optimization model for land use alloca tion and its application[J].Journal of Central South Univer sity:Science and Technology,42(4):1056-1065.]
张鸿辉,曾永年,谭荣.2011b.基于多智能体的农地非农化时空模拟与规划模型[J].测绘学报,40(3):366-372[Zhang H H,Zeng Y N,Tan R.2011.A spatio-tempora simulation and planning model for farmland conversion based on multi-agent systems[J].Acta Geodaetica et Carto graphica Sinica,40(3):366-372.]
张鸿辉,曾永年,谭荣,等.2011c.多智能体区域土地利用优化配置模型及其应用[J].地理学报,66(7):972-984[Zhang H H,Zeng Y N,Tan R,et al.2011.A model for re gional land use optimization allocation based on multi agent system and its application[J].Acta Geographica Sini ca,66(7):972-984.]
张云堂.2014.基于CA与ABM的城市居住用地扩张微观驱动机理模拟:以杭州市为例[D].杭州:浙江大学,2014[Zhang Y T.2014.Research on simulation of urban resi dential land expansion's microscopic drive mechanism based on CA and Agent-based model:A case study o Hangzhou[D].Hangzhou,China:Zhejiang University.]
Angela S,Parent J,Civco D L,et al.2011.The dimensions o global urban expansion:Estimates and projections for al countries,2000-2050[J].Progress in Planning,75(2):53107.
Basse R M,Omrani H,Charif O,et al.2014.Land use chang es modelling using advanced methods:Cellular automat and artificial neural networks.The spatial and explicit rep resentation of land cover dynamics at the cross-border re gion scale[J].Applied Geography,53:160-171.
Liu Y L,He Q S,Tan R H,et al.2016.Modeling different ur ban growth patterns based on the evolution of urban form A case study from Huangpi,Central China[J].Applied Ge ography,66:109-118.
Rienow A,Stenger D.2014.Geosimulation of urban growth and demographic decline in the Ruhr:A case study fo2025 using the artificial intelligence of cells and agents[J]Journal of Geographical Systems,16(3):311-342.
Tian G J,Qiao Z.2014.Modeling urban expansion policy sce narios using an agent-based approach for Guangzhou Met ropolitan Region of China[J].Ecology and Society,19(3)52.
Tsai Y,Zia A,Koliba C,et al.2015.An interactive land us transition agent-based model(ILUTABM):Endogenizing human-environment interactions in the Western Missisquo Watershed[J].Land Use Policy,49:161-176.
Wahyudi A,Liu Y.2015.Spatial dynamic models for inclusiv cities:A brief concept of cellular automata(CA)and agent based model(ABM)[J].Journal Perencanaan Wilayah dan Kota,26(1):54-70.
Wei Y D,Ye X Y.2014.Urbanization,urban land expansion and environmental change in China[J].Stochastic Environ mental Research and Risk Assessment,28(4):757-765.