中国建设用地空间格局分析
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摘要
全面准确地分析中国建设用地空间格局,是衡量城市景观的生态环境效应和制定区域发展战略的重要依据。为此,本文基于空间分辨率为12 m的2012年的全球城市足迹数据,分别在国家、经济区和城市群量化了中国建设用地空间格局。结果表明,12 m分辨率的数据能更细致和准确地刻画中国建设用地的特征。2012年中国建设用地面积为1.73×105km2,占中国陆地总面积的1.81%。从建设用地的空间格局来看,城市群尺度的建设用地破碎度最高,其建设用地平均斑块密度分别是国家和经济区平均水平的3.66倍和1.62倍。进一步分析表明,社会经济和地形因素共同影响建设用地空间格局。今后,应针对建设用地空间格局破碎问题,因地制宜地制定合理的措施,推动中国建设用地的合理发展。
Accurately quantifying spatial pattern of built-up areas is of great significance to analyzing the ecological and environmental impacts of the built-up landscape and planning for regional development. In this paper, we used the Global Urban Footprint(GUF) data with 12 m spatial resolution in 2012 to analyze the spatial pattern of built-up areas in China at three scales, i.e., the national, economic zone and urban agglomeration scales. Specifically, we chose six landscape metrics, i.e., total area of the built-up area,percentage of the built-up area of the landscape, number of patches, patch density, landscape shape index and mean Euclidean nearest-neighbor distance to measure spatial pattern of the built-up areas. Then, we explored the relationship between spatial pattern of built-up area and socioeconomic variable at different scales. The results showed the 12 m GUF dataset can delineate the built-up area in China with higher accuracy and more details, compared to previous coarse resolution datasets. The built-up areas reached 1.73 × 105 km2 in 2012,accounting for 1.81% of the total land area in China. At the economic zone scale, more than half of built-up areas concentrated in three economic zones, the Northern Coastal region, the Middle Reaches of the Yellow River and the Eastern Coastal region. From the perspective of the spatial pattern of the built-up areas, the fragmentation of built-up areas was highest at the urban agglomeration scale. The mean patch density at the urban agglomeration scale were 3.66 and 1.62 times as large as those at the national and economic zone scales.The results of correlation analysis indicated that population and economic level played important roles in influencing the spatial pattern of built-up areas. The number of patches and the degree of fragmentation for builtup areas increased with the amount of urban residents, gross domestic product and investment in the fixed assets. The correlation coefficients between these two sets of measurements ranged from 0.55 to 0.94(P<0.05).In the future, we should make place-based plans to solve the fragmentation of the built-up areas and to promote a rational development of built-up areas in China.
Accurately quantifying spatial pattern of built-up areas is of great significance to analyzing the ecological and environmental impacts of the built-up landscape and planning for regional development. In this paper, we used the Global Urban Footprint(GUF) data with 12 m spatial resolution in 2012 to analyze the spatial pattern of built-up areas in China at three scales, i.e., the national, economic zone and urban agglomeration scales. Specifically, we chose six landscape metrics, i.e., total area of the built-up area,percentage of the built-up area of the landscape, number of patches, patch density, landscape shape index and mean Euclidean nearest-neighbor distance to measure spatial pattern of the built-up areas. Then, we explored the relationship between spatial pattern of built-up area and socioeconomic variable at different scales. The results showed the 12 m GUF dataset can delineate the built-up area in China with higher accuracy and more details, compared to previous coarse resolution datasets. The built-up areas reached 1.73 × 105 km2 in 2012,accounting for 1.81% of the total land area in China. At the economic zone scale, more than half of built-up areas concentrated in three economic zones, the Northern Coastal region, the Middle Reaches of the Yellow River and the Eastern Coastal region. From the perspective of the spatial pattern of the built-up areas, the fragmentation of built-up areas was highest at the urban agglomeration scale. The mean patch density at the urban agglomeration scale were 3.66 and 1.62 times as large as those at the national and economic zone scales.The results of correlation analysis indicated that population and economic level played important roles in influencing the spatial pattern of built-up areas. The number of patches and the degree of fragmentation for builtup areas increased with the amount of urban residents, gross domestic product and investment in the fixed assets. The correlation coefficients between these two sets of measurements ranged from 0.55 to 0.94(P<0.05).In the future, we should make place-based plans to solve the fragmentation of the built-up areas and to promote a rational development of built-up areas in China.
引文
[1]Liu Z F,He C Y,Zhou Y Y,et al.How much of the world's land has been urbanized,really?A hierarchical framework for avoiding confusion[J].Landscape Ecology,2014,29:763-771.
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[8]丁俊,王开泳.珠三角城市群工业生产空间的时空演化及驱动机制[J].地理研究,2018,37(1):53-66.[Ding J,Wang K Y.Spatio-temporal evolution of industrial production space and its driving mechanisms in Pearl River Delta urban agglomeration[J].Geographical Research,2018,37(1):53-66.]
[9]Hu Z W,Li Q Q,Zhang Q,et al.Representation of blockbased image features in a multi-scale framework for builtup area detection[J].Remote Sensing,2016,8:155.
[10]Xu M,He C Y,Liu Z F,et al.How did urban land expand in China between 1992 and 2015?A multi-scale landscape analysis[J].PLoS One,2016,11:e0154839.
[11]Sharma R C,Tateishi R,Hara K,et al.Global mapping of urban built-up areas of year 2014 by combining MODISmultispectral data with VIIRS nighttime light data[J].International Journal of Digital Earth,2016,9(10):1004-1020.
[12]Kuang W H,Liu J Y,Dong J W,et al.The rapid and massive urban and industrial land expansions in China between 1990 and 2010:A CLUD-based analysis of their trajectories,patterns,and drivers[J].Landscape and Urban Planning,2016,145:21-33.
[13]Wang L,Li C C,Ying Q,et al.China's urban expansion from 1990 to 2010 determined with satellite remote sensing[J].Chinese Science Bulletin,2012,57(22):2802-2812.
[14]Chen X H,Cao X,Liao A P,et al.Global mapping of artificial surfaces at 30-m resolution[J].Science China Earth Sciences,2016,59(12):2295-2306.
[15]Esch T,Asamer H,Boettcher M,et al.Earth observationsupported service platform for the pevelopment and provision of thematic information on the built environmentthe Tep-Urban Project[C].ISPRS-International Archives of the Photogrammetry.Remote Sensing and Spatial Information Sciences,2016,XLI-B8:1379-1384.
[16]Minghini M,Molinari M B,See L,et al.Preliminary assessment of the global urban footprint and the global human settlement layer for the city of Milan[C].20thAgile Conference on Geographic Information Science,2017.
[17]Esch T,Wieke H,Andreas H,et al.Breaking new ground in mapping human settlements from space:The global urban footprint[J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,134:30-42.
[18]刘纪远,刘文超,匡文慧,等.基于主体功能区规划的中国城乡建设用地扩张时空特征遥感分析[J].地理学报,2016,71(3):355-369.[Liu J Y,Liu W C,Kuang W H,et al.Remote sensing-based analysis of the spatiotemporal characteristics of built-up area across China based on the plan for major function-oriented zones[J].Acta Geographica Sinica,2016,71(3):355-369.]
[19]赵雪,黄庆旭,何春阳.城市扩展过程对湿地影响的情景模拟研究——以河北怀来为例[J].自然资源学报,2017,32(9):1469-1481.[Zhao X,Huang Q X,He C Y.Scenarios simulation of the spatial stress on wetlands by urban expansion:A case study of Huailai County[J].Journal of Natural Resources,2017,32(9):1469-1481.]
[20]Xu Y,Gao X J,Shen Y et al.A daily temperature dataset over China and its application in validating a RCM simulation[J].Advances in Atmospheric Sciences,2009,26(4):763-772.
[21]吴佳,高学杰.一套格点化的中国区域逐日观测资料及与其它资料的对比[J].地球物理学报,2013,56(4):1102-1111.[Wu J,Gao X J.A gridded daily observation dataset over China region and comparison with the other datasets[J].Chinese Journal of Geophysics,2013,56(4):1102-1111.]
[22]邬建国.景观生态学:格局、过程、尺度与等级(第2版)[M].北京:高等教育出版社,2007.[Wu J G.Landscape ecology:pattern,process,scale and hierarchy(Second Edition)[M].Beijing:Higher Education Press,2007.]
[23]Wu J G.Urban sustainability:an inevitable goal of landscape research[J].Landscape Ecology,2010,25:1-4.
[24]McGarigal K,Cushman S A,Ene E.Fragstats v4:Spatial pattern analysis program for categorical and continuous maps[CP].Computer software program produced by the authors at the University of Massachusetts,Amherst,2012.http://www.umass.edu/landeco/research/fragstats/fragtats.html.
[25]中共中央国务院.国家新型城镇化规划(2014-2020年)[R].北京:新华社,2014.[The CPC Central Committee TSC.National New-type Urbanization Plan(2014-2020)[R].Beijing:Xinhua News Agency,2014.]
[26]Fang C L,Ma H T,Wang J.A Regional Categorization for"New-Type Urbanization"in China[J].PloS One,2015,10(8):e0134253.
[27]国务院.中华人民共和国国民经济和社会发展第十三个五年(2016-2020年)规划纲要[R].北京,2016-03-17.[The State Council of PRC.The 13thFive-Year Plan for Economic and Social Development of the People’s Republic of China(2016-2020)[R].Beijing,2016-03-17.]
[28]许学强,周一星,宁越敏.城市地理学[M].北京:高等教育出版社,2009.[Xu X Q,Zhou Y X,Ning Y M.Urban geography[M].Beijing:Higher Education Press,2009.]
[29]Xia N,Wang Y J,Xu H,et al.Demarcation of prime farmland protection areas around a metropolis based on highresolution satellite imagery[J].Scientific Reports,2016,6:37634.
[30]Jayasekare A S,Wickramasuriya R,Namazi-Rad M,et al.Hybrid method for building extraction in vegetation-rich urban areas from very high-resolution satellite imagery[J].Journal of Applied Remote Sensing,2017,11(3):036017-1-036017-12.
[31]刘珍环,王仰麟,彭建.深圳市不透水表面的遥感监测与时空格局[J].地理研究,2012,31(8):1535-1545.[Liu Z H,Wang Y L,Peng J.Quatifying spatiotemporal patterns dynamics of impervious surface in Shenzhen[J].Geographical Research,2012,31(8):1535-1545.]
[32]Chen Y X,Qin K,Gan S Z,et al.Structural feature modeling of high-resolution remote sensing images using directional spatial correlation[J].IEEE Geoscience and Remote Sensing Letters,2014,11(10):1727-1731.
[33]Zhang L B,Li A X,Zhang Z J,et al.Global and local saliency analysis for the extraction of residential areas in high-spatial-resolution remote sensing image[J].IEEETransactions on Geoscience and Remote Sensing,2016,54:3750-3763.
[34]汪权方,许纪承,陈媛媛等.遥感影像空间分辨率对居民地信息提取的影响[J].资源科学,2012,34(1):159-165.[Wang Q F,Xu J C,Chen Y Y,et al.Influence of the varied spatial resolution of remote sensing images on urban and rural residential information extraction[J].Resources Science,2012,34(1):159-165.]
[35]Li X M,Zhou W Q,Ouyang Z Y.Relationship between land surface temperature and spatial pattern of greenspace:What are the effects of spatial resolution?[J].Landscape and Urban Planning,2013,114(8):1-8.
[36]黄庆旭,何春阳,史培军等.城市扩展多尺度驱动机制分析——以北京为例[J].经济地理,2009,29(5):714-721.[Huang Q X,He C Y,Shi P J,et al.Understanding multiscale urban expansion driving forces:In the case study of Beijing[J].Economic Geography,2009,29(5):714-721.]
[37]Huang J N,Lu X X,Sellers J M.A global comparative analysis of urban form:Applying spatial metrics and remote sensing[J].Landscape and Urban Planning,2007,82:184-97.
[38]Clarke K C,Hoppen S,Gaydos L.A self-modifying cellular automation model of historical urbanization in the San Francisco bay area[J].Environment and Planning B:Planning and Design,1997,24:247-261.
[39]韩会然,杨成凤,宋金平.北京市土地利用空间格局演化模拟及预测[J].地理科学进展,2015,34(8):976-986.[Han H R,Yang C F,Song J P.Simulation and projection of landuse change in Beijing under different scenarios[J].Progress in Geography,2015,34(8):976-986.]
[40]刘纪远,张增祥,徐新良等.21世纪初中国土地利用变化的空间格局与驱动力分析[J].地理学报,2009,64(12):1411-1420.[Liu J Y,Zhang Z X,Xu X L,et al.Spatial patterns and driving forces of land use change in China in the early 21stcentury[J].Acta Geographica Sinica,2009,64(12):1411-1420.]
[41]任志远,李冬玉,杨勇.关中地区土地利用格局模拟与驱动力分析[J].测绘科学,2011,36(1):105-108.[Ren Z Y,Li D Y,Yang Y.Simulation and driving force analysis of land use pattern in Guanzhong region,Shaanxi Province[J].Science of Surveying and Mapping,2011,36(1):105-108.]
[2]Liu Z F,He C Y,Zhang Q F,et al.Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008[J].Landscape and Urban Planning,2012,106:62-72.
[3]国家统计局.中国统计年鉴-2017[M].北京:中国统计出版社,2017.[National Bureau of Statistics of China 2017China Statistical Yearbook[M].Beijing:China Statistics Press,2017.]
[4]Aronson M F,La Sorte F A,Nilon C H,et al.A global analysis of the impacts of urbanization on bird and plant diversity reveals key anthropogenic drivers[J].Proceedings Biological Sciences,2014,281(1780):20133330.
[5]Zhou Y Y,Wang Y Q,Gold A J,et al.Assessing impact of urban impervious surface on watershed hydrology using distributed object-oriented simulation and spatial regression[J].GeoJournal,2013,79:155-66.
[6]方创琳.中国快速城市化过程中的资源环境保障问题与对策建议[J].中国科学院院刊,2009,24(5):468-474.[Fang C L.Issues of resources and environment protection in China's rapid urbanization process and suggestions on countermeasures[J].Bulletin of Chinese Academy of Sciences,2009,24(5):468-474.]
[7]周春山,叶昌东.中国特大城市空间增长特征及其原因分析[J].地理学报,2013,68(6):728-738.[Zhou C S,Ye C D.Features and causes of urban spatial growth in Chinese metropolises[J].Acta Geographica Sinica,2013,68(6):728-738.]
[8]丁俊,王开泳.珠三角城市群工业生产空间的时空演化及驱动机制[J].地理研究,2018,37(1):53-66.[Ding J,Wang K Y.Spatio-temporal evolution of industrial production space and its driving mechanisms in Pearl River Delta urban agglomeration[J].Geographical Research,2018,37(1):53-66.]
[9]Hu Z W,Li Q Q,Zhang Q,et al.Representation of blockbased image features in a multi-scale framework for builtup area detection[J].Remote Sensing,2016,8:155.
[10]Xu M,He C Y,Liu Z F,et al.How did urban land expand in China between 1992 and 2015?A multi-scale landscape analysis[J].PLoS One,2016,11:e0154839.
[11]Sharma R C,Tateishi R,Hara K,et al.Global mapping of urban built-up areas of year 2014 by combining MODISmultispectral data with VIIRS nighttime light data[J].International Journal of Digital Earth,2016,9(10):1004-1020.
[12]Kuang W H,Liu J Y,Dong J W,et al.The rapid and massive urban and industrial land expansions in China between 1990 and 2010:A CLUD-based analysis of their trajectories,patterns,and drivers[J].Landscape and Urban Planning,2016,145:21-33.
[13]Wang L,Li C C,Ying Q,et al.China's urban expansion from 1990 to 2010 determined with satellite remote sensing[J].Chinese Science Bulletin,2012,57(22):2802-2812.
[14]Chen X H,Cao X,Liao A P,et al.Global mapping of artificial surfaces at 30-m resolution[J].Science China Earth Sciences,2016,59(12):2295-2306.
[15]Esch T,Asamer H,Boettcher M,et al.Earth observationsupported service platform for the pevelopment and provision of thematic information on the built environmentthe Tep-Urban Project[C].ISPRS-International Archives of the Photogrammetry.Remote Sensing and Spatial Information Sciences,2016,XLI-B8:1379-1384.
[16]Minghini M,Molinari M B,See L,et al.Preliminary assessment of the global urban footprint and the global human settlement layer for the city of Milan[C].20thAgile Conference on Geographic Information Science,2017.
[17]Esch T,Wieke H,Andreas H,et al.Breaking new ground in mapping human settlements from space:The global urban footprint[J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,134:30-42.
[18]刘纪远,刘文超,匡文慧,等.基于主体功能区规划的中国城乡建设用地扩张时空特征遥感分析[J].地理学报,2016,71(3):355-369.[Liu J Y,Liu W C,Kuang W H,et al.Remote sensing-based analysis of the spatiotemporal characteristics of built-up area across China based on the plan for major function-oriented zones[J].Acta Geographica Sinica,2016,71(3):355-369.]
[19]赵雪,黄庆旭,何春阳.城市扩展过程对湿地影响的情景模拟研究——以河北怀来为例[J].自然资源学报,2017,32(9):1469-1481.[Zhao X,Huang Q X,He C Y.Scenarios simulation of the spatial stress on wetlands by urban expansion:A case study of Huailai County[J].Journal of Natural Resources,2017,32(9):1469-1481.]
[20]Xu Y,Gao X J,Shen Y et al.A daily temperature dataset over China and its application in validating a RCM simulation[J].Advances in Atmospheric Sciences,2009,26(4):763-772.
[21]吴佳,高学杰.一套格点化的中国区域逐日观测资料及与其它资料的对比[J].地球物理学报,2013,56(4):1102-1111.[Wu J,Gao X J.A gridded daily observation dataset over China region and comparison with the other datasets[J].Chinese Journal of Geophysics,2013,56(4):1102-1111.]
[22]邬建国.景观生态学:格局、过程、尺度与等级(第2版)[M].北京:高等教育出版社,2007.[Wu J G.Landscape ecology:pattern,process,scale and hierarchy(Second Edition)[M].Beijing:Higher Education Press,2007.]
[23]Wu J G.Urban sustainability:an inevitable goal of landscape research[J].Landscape Ecology,2010,25:1-4.
[24]McGarigal K,Cushman S A,Ene E.Fragstats v4:Spatial pattern analysis program for categorical and continuous maps[CP].Computer software program produced by the authors at the University of Massachusetts,Amherst,2012.http://www.umass.edu/landeco/research/fragstats/fragtats.html.
[25]中共中央国务院.国家新型城镇化规划(2014-2020年)[R].北京:新华社,2014.[The CPC Central Committee TSC.National New-type Urbanization Plan(2014-2020)[R].Beijing:Xinhua News Agency,2014.]
[26]Fang C L,Ma H T,Wang J.A Regional Categorization for"New-Type Urbanization"in China[J].PloS One,2015,10(8):e0134253.
[27]国务院.中华人民共和国国民经济和社会发展第十三个五年(2016-2020年)规划纲要[R].北京,2016-03-17.[The State Council of PRC.The 13thFive-Year Plan for Economic and Social Development of the People’s Republic of China(2016-2020)[R].Beijing,2016-03-17.]
[28]许学强,周一星,宁越敏.城市地理学[M].北京:高等教育出版社,2009.[Xu X Q,Zhou Y X,Ning Y M.Urban geography[M].Beijing:Higher Education Press,2009.]
[29]Xia N,Wang Y J,Xu H,et al.Demarcation of prime farmland protection areas around a metropolis based on highresolution satellite imagery[J].Scientific Reports,2016,6:37634.
[30]Jayasekare A S,Wickramasuriya R,Namazi-Rad M,et al.Hybrid method for building extraction in vegetation-rich urban areas from very high-resolution satellite imagery[J].Journal of Applied Remote Sensing,2017,11(3):036017-1-036017-12.
[31]刘珍环,王仰麟,彭建.深圳市不透水表面的遥感监测与时空格局[J].地理研究,2012,31(8):1535-1545.[Liu Z H,Wang Y L,Peng J.Quatifying spatiotemporal patterns dynamics of impervious surface in Shenzhen[J].Geographical Research,2012,31(8):1535-1545.]
[32]Chen Y X,Qin K,Gan S Z,et al.Structural feature modeling of high-resolution remote sensing images using directional spatial correlation[J].IEEE Geoscience and Remote Sensing Letters,2014,11(10):1727-1731.
[33]Zhang L B,Li A X,Zhang Z J,et al.Global and local saliency analysis for the extraction of residential areas in high-spatial-resolution remote sensing image[J].IEEETransactions on Geoscience and Remote Sensing,2016,54:3750-3763.
[34]汪权方,许纪承,陈媛媛等.遥感影像空间分辨率对居民地信息提取的影响[J].资源科学,2012,34(1):159-165.[Wang Q F,Xu J C,Chen Y Y,et al.Influence of the varied spatial resolution of remote sensing images on urban and rural residential information extraction[J].Resources Science,2012,34(1):159-165.]
[35]Li X M,Zhou W Q,Ouyang Z Y.Relationship between land surface temperature and spatial pattern of greenspace:What are the effects of spatial resolution?[J].Landscape and Urban Planning,2013,114(8):1-8.
[36]黄庆旭,何春阳,史培军等.城市扩展多尺度驱动机制分析——以北京为例[J].经济地理,2009,29(5):714-721.[Huang Q X,He C Y,Shi P J,et al.Understanding multiscale urban expansion driving forces:In the case study of Beijing[J].Economic Geography,2009,29(5):714-721.]
[37]Huang J N,Lu X X,Sellers J M.A global comparative analysis of urban form:Applying spatial metrics and remote sensing[J].Landscape and Urban Planning,2007,82:184-97.
[38]Clarke K C,Hoppen S,Gaydos L.A self-modifying cellular automation model of historical urbanization in the San Francisco bay area[J].Environment and Planning B:Planning and Design,1997,24:247-261.
[39]韩会然,杨成凤,宋金平.北京市土地利用空间格局演化模拟及预测[J].地理科学进展,2015,34(8):976-986.[Han H R,Yang C F,Song J P.Simulation and projection of landuse change in Beijing under different scenarios[J].Progress in Geography,2015,34(8):976-986.]
[40]刘纪远,张增祥,徐新良等.21世纪初中国土地利用变化的空间格局与驱动力分析[J].地理学报,2009,64(12):1411-1420.[Liu J Y,Zhang Z X,Xu X L,et al.Spatial patterns and driving forces of land use change in China in the early 21stcentury[J].Acta Geographica Sinica,2009,64(12):1411-1420.]
[41]任志远,李冬玉,杨勇.关中地区土地利用格局模拟与驱动力分析[J].测绘科学,2011,36(1):105-108.[Ren Z Y,Li D Y,Yang Y.Simulation and driving force analysis of land use pattern in Guanzhong region,Shaanxi Province[J].Science of Surveying and Mapping,2011,36(1):105-108.]