扬州城市建设用地扩张的时空演变特征及其驱动机制
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摘要
建设用地扩张是城市土地利用变化中最剧烈、最直观的表现。探究其时空演变特征及其驱动力将有助于揭示城市空间扩张机理,促进城市用地调控的科学化。以快速城市化的中型城市——扬州市为例,基于多期Landsat遥感影像(1995、2000、2005、2010和2015年)、社会经济数据等资料,分析建设用地扩张的时空演变特征,进而利用增强回归树(boosted regression tree)方法,探讨城市化进程中地理空间、社会和经济因子对建设用地扩张的影响。研究发现,1995—2015年,建设用地面积从725.4 km~2持续增加到1076.5 km~2。随着城市化的推进,建设用地的空间形态趋于紧凑、形状变得规则,重心也随之转移,表现出市辖区的局部吸引和联动特征。在地理空间、社会和经济因子中,地理空间因子(如海拔、距县市核心区和建成区的距离)对建设用地扩张的影响最大,但其相对影响却从1995—2000年的73.9%逐渐下降到2010—2015年的60.2%;社会和经济因子的相对影响则呈增加的趋势,即1995—2000年的5.2%和20.9%分别增加到2010—2015年的7.9%和31.9%。地理空间因子(如距县市核心区和建成区的距离)对建设用地扩张的影响以抑制作用为主,但不同社会经济因子的作用呈现较大差异,例如,人口密度、人均GDP和财政收入能够促进建设用地的形成,人口数量表现为抑制作用,第二产业则为先抑制后促进的作用。
Built-up land sprawl is the most drastic and visual manifestation of urban land-use change. Understanding spatiotemporal change of built-up land sprawl and its driving forces can reveal the inherent laws of urban sprawl,and thus scientifically regulate urban land use. In this study,we used multi-source data( e.g.,30 m resolution Landsat images in 1995,2000,2005,2010,and 2015) and socioeconomic data to analyze spatiotemporal changes of built-up land sprawl in Yangzhou City. Further,we employed the boosted regression tree method to quantify the effects of geographic,social and economic factors on such sprawl. Results showed that the builtup land area gradually increased from 725.4 km~2 in 1995 to 1076.5 km~2 in 2015. With the increasing urbanization,the spatial form of built-up land tended to be compact and regular,and the gravity coordinates also migrated accordingly,showing local attraction and linkage of municipal districts( e.g.,Hanjiang and Guangling). Among geographic,social,and economic factors,geographic factors( e. g.,altitude,the distance from the county core,the distance from built-up land) had the greatest influence on built-up land sprawl,with the relative influence gradually decreasing from 73.9% in 1995-2000 to 60.2% in 2010-2015. The influence of social and economic factors gradually increased from 5.2% and 20.9% in 1995-2000 to 7.9% and 31.9% in2010-2015. Geographic factors( e. g.,the distance from the county core and the distance from built-up land) generally had negative effect on built-up land sprawl,but the effects of social and economic factors were inconsistent. For example,population density,GDP per capita and fiscal revenue promoted built-up land sprawl,gross population inhibited it,and secondary industry first inhibited built-up land sprawl and then promoted it.
Built-up land sprawl is the most drastic and visual manifestation of urban land-use change. Understanding spatiotemporal change of built-up land sprawl and its driving forces can reveal the inherent laws of urban sprawl,and thus scientifically regulate urban land use. In this study,we used multi-source data( e.g.,30 m resolution Landsat images in 1995,2000,2005,2010,and 2015) and socioeconomic data to analyze spatiotemporal changes of built-up land sprawl in Yangzhou City. Further,we employed the boosted regression tree method to quantify the effects of geographic,social and economic factors on such sprawl. Results showed that the builtup land area gradually increased from 725.4 km~2 in 1995 to 1076.5 km~2 in 2015. With the increasing urbanization,the spatial form of built-up land tended to be compact and regular,and the gravity coordinates also migrated accordingly,showing local attraction and linkage of municipal districts( e.g.,Hanjiang and Guangling). Among geographic,social,and economic factors,geographic factors( e. g.,altitude,the distance from the county core,the distance from built-up land) had the greatest influence on built-up land sprawl,with the relative influence gradually decreasing from 73.9% in 1995-2000 to 60.2% in 2010-2015. The influence of social and economic factors gradually increased from 5.2% and 20.9% in 1995-2000 to 7.9% and 31.9% in2010-2015. Geographic factors( e. g.,the distance from the county core and the distance from built-up land) generally had negative effect on built-up land sprawl,but the effects of social and economic factors were inconsistent. For example,population density,GDP per capita and fiscal revenue promoted built-up land sprawl,gross population inhibited it,and secondary industry first inhibited built-up land sprawl and then promoted it.
引文
陈可嘉,臧永生,李成.2012.福建省产业结构演进对城市化的动态影响.城市问题,(12):58-62.
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高金龙,陈江龙,苏曦.2013.中国城市扩张态势与驱动机理研究学派综述.地理科学进展,32(5):743-754.
高晓俊.2016.基于情景规划的中小城市空间发展规划研究(硕士学位论文).合肥:合肥工业大学.
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焦琳琳,常禹,申丹,等.2015.利用增强回归树分析中国野火空间分布格局的影响因素.生态学杂志,34(8):2288-2296.
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潘竟虎,苏有才,黄永生,等.2012.近30年玉门市土地利用与景观格局变化及其驱动力.地理研究,31(9):1631-1639.
王芳,陈芝聪,谢小平.2018.太湖流域建设用地与耕地景观时空演变及驱动力.生态学报,38(9):3300-3310.
臧淑英,王凌云,那晓东,等.2011.基于经济驱动因子的土地利用结构变化区域差异分析---以哈大齐工业走廊为例.地理研究,30(2):224-232.
张耀宇,陈利根,宋璐怡.2016.中国城市用地扩张驱动机制的差异性研究.资源科学,38(1):30-40.
周国华,贺艳华.2006.长沙城市土地扩张特征及影响因素.地理学报,61(11):1171-1180.
Barbati A,Corona P,Salvati L,et al.2013.Natural forest expansion into suburban countryside:A contrasting perspective about changing forest landscape pattern.Urban Forestry and Urban Greening,12:36-43.
Daniel M,Pedro JL,Thomas S.2013.Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees.Agricultural Systems,117:66-77.
Elith J,Leathwick JR,Hastie T.2008.A working guide to boosted regression trees.Journal of Animal Ecology,77:802-813.
Estoque RC,Murayama Y.2013.Landscape pattern and ecosystem service value changes:Implications for environmental sustainability planning for the rapidly urbanizing summer capital of the Philippines.Landscape and Urban Planning,116:60-72.
Fang CL,Li GD,Wang SJ.2016.Changing and differentiated urban landscape in China:Spatiotemporal patterns and driving forces.Environmental Science and Technology,50:2217-2227.
Garouani AE,Mulla DJ,Garouani SE,et al.2017.Analysis of urban growth and sprawl from remote sensing data:Case of Fez,Morocco.International Journal of Sustainable Built Environment,6:160-169.
Grimm NB,Faeth SH,Golubiewski NE,et al.2008.Global change and the ecology of cities.Science,319:756-760.
Hastie T,Tibshirani R,Friedman J.2009.The Elements of Statistical Learning.New York:Springer.
Jiang L,Deng XZ,Seto KC.2012.Multi-level modeling of urban expansion and cultivated land conversion for urban hotspot counties in China.Landscape and Urban Planning,108:131-139.
Khila RD,Shawn B,Eric L.2017.Urban hypotheses and spatiotemporal characterization of urban growth in the Treasure Valley of Idaho,USA.Applied Geography,79:11-25.
Kuang WH,Chi WF,Lu DS,et al.2014.A comparative analysis of megacity expansions in China and the U.S.:Patterns,rates and driving forces.Landscape and Urban Planning,132:121-135.
Li C,Li JX,Wu JG.2013a.Quantifying the speed,growth modes,and landscape pattern changes of urbanization:Ahierarchical patch dynamics approach.Landscape Ecology,28:1875-1888.
Li XM,Zhou WQ,Ouyang ZY.2013b.Forty years of urban expansion in Beijing:What is the relative importance of physical,socioeconomic,and neighborhood factors?Applied Geography,38:1-10.
Li C,Li JX,Wu JG.2018.What drives urban growth in China?A multi-scale comparative analysis.Applied Geography,98:43-51.
Martin MP,Wattenbach M,Smith P,et al.2011.Spatial distribution of soil organic carbon stocks in France.Biogeosciences,8:1053-1065.
McGarigal K,Marks BJ.1995.FRAGSTATS:Spatial Pattern Analysis Program for Quantifying Landscape Structure(General Technical Report PNW-GTR-351).Oregon:USDA Forest Service,Pacific Northwest Research Station.
McGarigal K,Cushman SA,Neel MC,et al.2002.FRAG-STATS:Spatial Pattern Analysis Program for Categorical Maps.[EB/OL].[2018-09-01].http://www.umass.edu/landeco/research/fragstats/fragstats.html.
Salvati L.2014.Agro-forest landscape and the‘Fringe’city:Amultivariate assessment of land-use changes in a Sprawling region and implications for planning.Science of the Total Environment,490:715-723.
Serra P,Pons X,SaurìD.2008.Land-cover and land-use change in a Mediterranean landscape:A spatial analysis of driving forces integrating biophysical and human factors.Applied Geography,28:189-209.
Wang L,Li CC,Ying Q,et al.2012.China’s urban expansion from 1990 to 2010 determined with satellite remote sensing.Chinese Science Bulletin,57:2802-2812.
Zhao SQ,Liu SG,Xu CX,et al.2018.Contemporary evolution and scaling of 32 major cities in China.Ecological Applications,28:1655-1668.
冯仕超,高小红,亢健,等.2012.西宁市30多年来土地利用/土地覆被变化及城市扩展研究.干旱区研究,29(1):129-136.
高金龙,陈江龙,苏曦.2013.中国城市扩张态势与驱动机理研究学派综述.地理科学进展,32(5):743-754.
高晓俊.2016.基于情景规划的中小城市空间发展规划研究(硕士学位论文).合肥:合肥工业大学.
宫兆宁,张翼然,宫辉力,等.2011.北京湿地景观格局演变特征与驱动机制分析.地理学报,66(1):77-88.
郭瑞敏,千怀遂,李明霞,等.2013.广州市城市扩张和经济发展之间的关系.资源科学,35(2):447-454.
黄庆旭,何春阳,史培军,等.2009.城市扩展多尺度驱动机制分析-以北京为例.经济地理,29(5):714-721.
焦琳琳,常禹,申丹,等.2015.利用增强回归树分析中国野火空间分布格局的影响因素.生态学杂志,34(8):2288-2296.
李春林,刘淼,胡远满,等.2014.基于增强回归树和Logistic回归的城市扩展驱动力分析.生态学报,34(3):727-737.
孟祥林.2008.产业结构变化对城市化进程影响的经济学分析.北华大学学报:社会科学版,9(1):100-105.
欧强新,李海奎,雷相东,等.2018.基于清查数据的福建省马尾松生物量转换和扩展因子估算差异解析---3种集成学习决策树模型的比较.应用生态学报,29(6):2007-2016.
潘竟虎,苏有才,黄永生,等.2012.近30年玉门市土地利用与景观格局变化及其驱动力.地理研究,31(9):1631-1639.
王芳,陈芝聪,谢小平.2018.太湖流域建设用地与耕地景观时空演变及驱动力.生态学报,38(9):3300-3310.
臧淑英,王凌云,那晓东,等.2011.基于经济驱动因子的土地利用结构变化区域差异分析---以哈大齐工业走廊为例.地理研究,30(2):224-232.
张耀宇,陈利根,宋璐怡.2016.中国城市用地扩张驱动机制的差异性研究.资源科学,38(1):30-40.
周国华,贺艳华.2006.长沙城市土地扩张特征及影响因素.地理学报,61(11):1171-1180.
Barbati A,Corona P,Salvati L,et al.2013.Natural forest expansion into suburban countryside:A contrasting perspective about changing forest landscape pattern.Urban Forestry and Urban Greening,12:36-43.
Daniel M,Pedro JL,Thomas S.2013.Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees.Agricultural Systems,117:66-77.
Elith J,Leathwick JR,Hastie T.2008.A working guide to boosted regression trees.Journal of Animal Ecology,77:802-813.
Estoque RC,Murayama Y.2013.Landscape pattern and ecosystem service value changes:Implications for environmental sustainability planning for the rapidly urbanizing summer capital of the Philippines.Landscape and Urban Planning,116:60-72.
Fang CL,Li GD,Wang SJ.2016.Changing and differentiated urban landscape in China:Spatiotemporal patterns and driving forces.Environmental Science and Technology,50:2217-2227.
Garouani AE,Mulla DJ,Garouani SE,et al.2017.Analysis of urban growth and sprawl from remote sensing data:Case of Fez,Morocco.International Journal of Sustainable Built Environment,6:160-169.
Grimm NB,Faeth SH,Golubiewski NE,et al.2008.Global change and the ecology of cities.Science,319:756-760.
Hastie T,Tibshirani R,Friedman J.2009.The Elements of Statistical Learning.New York:Springer.
Jiang L,Deng XZ,Seto KC.2012.Multi-level modeling of urban expansion and cultivated land conversion for urban hotspot counties in China.Landscape and Urban Planning,108:131-139.
Khila RD,Shawn B,Eric L.2017.Urban hypotheses and spatiotemporal characterization of urban growth in the Treasure Valley of Idaho,USA.Applied Geography,79:11-25.
Kuang WH,Chi WF,Lu DS,et al.2014.A comparative analysis of megacity expansions in China and the U.S.:Patterns,rates and driving forces.Landscape and Urban Planning,132:121-135.
Li C,Li JX,Wu JG.2013a.Quantifying the speed,growth modes,and landscape pattern changes of urbanization:Ahierarchical patch dynamics approach.Landscape Ecology,28:1875-1888.
Li XM,Zhou WQ,Ouyang ZY.2013b.Forty years of urban expansion in Beijing:What is the relative importance of physical,socioeconomic,and neighborhood factors?Applied Geography,38:1-10.
Li C,Li JX,Wu JG.2018.What drives urban growth in China?A multi-scale comparative analysis.Applied Geography,98:43-51.
Martin MP,Wattenbach M,Smith P,et al.2011.Spatial distribution of soil organic carbon stocks in France.Biogeosciences,8:1053-1065.
McGarigal K,Marks BJ.1995.FRAGSTATS:Spatial Pattern Analysis Program for Quantifying Landscape Structure(General Technical Report PNW-GTR-351).Oregon:USDA Forest Service,Pacific Northwest Research Station.
McGarigal K,Cushman SA,Neel MC,et al.2002.FRAG-STATS:Spatial Pattern Analysis Program for Categorical Maps.[EB/OL].[2018-09-01].http://www.umass.edu/landeco/research/fragstats/fragstats.html.
Salvati L.2014.Agro-forest landscape and the‘Fringe’city:Amultivariate assessment of land-use changes in a Sprawling region and implications for planning.Science of the Total Environment,490:715-723.
Serra P,Pons X,SaurìD.2008.Land-cover and land-use change in a Mediterranean landscape:A spatial analysis of driving forces integrating biophysical and human factors.Applied Geography,28:189-209.
Wang L,Li CC,Ying Q,et al.2012.China’s urban expansion from 1990 to 2010 determined with satellite remote sensing.Chinese Science Bulletin,57:2802-2812.
Zhao SQ,Liu SG,Xu CX,et al.2018.Contemporary evolution and scaling of 32 major cities in China.Ecological Applications,28:1655-1668.