近20年京津唐主体城区地表热场空间特征变化分析
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摘要
基于Landsat遥感影像获取京津唐主体城区1995～2015年地表温度(Land Surface Temperature, LST)和不透水地表盖度(Impervious Surface Percentage, ISP)数据。采用热点聚集和阈值分割法,依据地表的温度和不透水盖度属性将京津唐主体城区划分成9种地表热场类型,分析并探讨地表热场的发展规律、年际变化状况和区域贡献作用。研究发现,京津唐主体城区地表温度与不透水地表盖度间存在显著的正向相关关系,两者分别呈现"阶梯降"和"两端高、中间低"的变化特征。京津唐主体城区地表热场的发展主轴保持在西北-东南方向,且随时间推移沿主轴呈聚集态势。京津唐主体城区地表热场的影响范围在空间上持续扩张,对于不同的主体城区,其在整体区域的热场贡献中有差异化表现。
The changes in the characteristics of urban land surface thermal field caused by urban development have significant impacts on regional climate and ecological environment. Urban land surface thermal field reflects the relationship between urban expansion and environmental temperature. Understanding the formation causes and coupling association of urban land surface thermal field and urban development has important academic research significance. Conducting long-term surface monitoring and measurement in Beijing-Tianjin-Tangshan region, studying the characteristics of the land surface thermal field and its variation by the perspective of regionalization. Land surface temperature(LST) and impervious surface percentage(ISP) in the main urban area of Beijing-Tianjin-Tangshan in 1995, 2005, and 2015 were obtained by Landsat remote sensing images. The methods of ten fold cross validation and record value verification were used to evaluate results of ISP and LST. Based on the hot spot aggregation method, study area was zoned for low, medium, and high LST zones. In the same way, study area was zoned to natural land surface, low, and high ISP zones based on threshold segmentation method. And the land surface thermal field in the main urban area of Beijing-Tianjin-Tangshan was divided into nine types according to the regionalization information about LST and ISP.Then the development law, the inter-annual change situation, and the regional contribution of different types of land surface thermal field were analyzed and discussed based on the method of mathematical statistics, standard deviation ellipse, and contribution index. The study find that the LST has a significant correlation with the ISP in main urban area of Beijing-Tianjin-Tangshan, the multiple correlation coefficients are 0.88, 0.92, and0.94 from 1995 to 2015, this also reflects that the relationship between the two land surface attributes is gradually strengthening. The LST would rise with the increase of ISP. This growth phenomenon performs fast in1995 and is slow in 2005 and 2015 relative. The mean value of ISP is 49.72%, 53.87%, and 57.17% in three periods, and high LST zone area also maintains 1.5 time growth rates over time. The development focal axis of land surface thermal field remains in the northwest-southeast direction and accumulates along the axis over time. The centroid of land surface thermal field in the main urban area of Beijing-Tianjin-Tangshan is concentrated in the central part of each city. The inter-annual change rate of land surface thermal field increases from12.00% to 13.71%, the type of land surface thermal field continues to change to the form of"high LST and high ISP". Besides, the land surface thermal field shows the change characteristics of"step down"in LST and"large at both ends and small in the middle"in ISP. The land surface thermal field of the main urban area of Beijing-Tianjin-Tangshan continues to expand in space. The spatial distribution of the land surface thermal field in Beijing's main urban area gradually spreads from the south to the entire area. Tianjin's land surface thermal field spreads rapidly from the central area to the port. Tangshan's spatial distribution of land surface thermal field is more significant in the north. Different main urban areas have different contributions to the overall area: Beijing's contribution is concentrated in areas of high-grade land surface thermal fields. Tianjin's contribution to various types of land surface thermal field is balanced. And Tangshan's contribution is inclined to shift to higher grade land surface thermal fields. The study is applicable to assessing spatial and temporal changes in the thermal field in the Beijing-Tianjin-Tangshan region, and promoting the coordinated development of construction planning and ecological environment in the urban community area.
The changes in the characteristics of urban land surface thermal field caused by urban development have significant impacts on regional climate and ecological environment. Urban land surface thermal field reflects the relationship between urban expansion and environmental temperature. Understanding the formation causes and coupling association of urban land surface thermal field and urban development has important academic research significance. Conducting long-term surface monitoring and measurement in Beijing-Tianjin-Tangshan region, studying the characteristics of the land surface thermal field and its variation by the perspective of regionalization. Land surface temperature(LST) and impervious surface percentage(ISP) in the main urban area of Beijing-Tianjin-Tangshan in 1995, 2005, and 2015 were obtained by Landsat remote sensing images. The methods of ten fold cross validation and record value verification were used to evaluate results of ISP and LST. Based on the hot spot aggregation method, study area was zoned for low, medium, and high LST zones. In the same way, study area was zoned to natural land surface, low, and high ISP zones based on threshold segmentation method. And the land surface thermal field in the main urban area of Beijing-Tianjin-Tangshan was divided into nine types according to the regionalization information about LST and ISP.Then the development law, the inter-annual change situation, and the regional contribution of different types of land surface thermal field were analyzed and discussed based on the method of mathematical statistics, standard deviation ellipse, and contribution index. The study find that the LST has a significant correlation with the ISP in main urban area of Beijing-Tianjin-Tangshan, the multiple correlation coefficients are 0.88, 0.92, and0.94 from 1995 to 2015, this also reflects that the relationship between the two land surface attributes is gradually strengthening. The LST would rise with the increase of ISP. This growth phenomenon performs fast in1995 and is slow in 2005 and 2015 relative. The mean value of ISP is 49.72%, 53.87%, and 57.17% in three periods, and high LST zone area also maintains 1.5 time growth rates over time. The development focal axis of land surface thermal field remains in the northwest-southeast direction and accumulates along the axis over time. The centroid of land surface thermal field in the main urban area of Beijing-Tianjin-Tangshan is concentrated in the central part of each city. The inter-annual change rate of land surface thermal field increases from12.00% to 13.71%, the type of land surface thermal field continues to change to the form of"high LST and high ISP". Besides, the land surface thermal field shows the change characteristics of"step down"in LST and"large at both ends and small in the middle"in ISP. The land surface thermal field of the main urban area of Beijing-Tianjin-Tangshan continues to expand in space. The spatial distribution of the land surface thermal field in Beijing's main urban area gradually spreads from the south to the entire area. Tianjin's land surface thermal field spreads rapidly from the central area to the port. Tangshan's spatial distribution of land surface thermal field is more significant in the north. Different main urban areas have different contributions to the overall area: Beijing's contribution is concentrated in areas of high-grade land surface thermal fields. Tianjin's contribution to various types of land surface thermal field is balanced. And Tangshan's contribution is inclined to shift to higher grade land surface thermal fields. The study is applicable to assessing spatial and temporal changes in the thermal field in the Beijing-Tianjin-Tangshan region, and promoting the coordinated development of construction planning and ecological environment in the urban community area.
引文
[1]Yuan S,Katzschner L,Ng E.Modelling the fine-scale spatiotemporal pattern of urban heat island effect using land use regression approach in a megacity[J].Science of the Total Environment,2018,618:891-904.
[2]杨续超,陈葆德,胡可嘉.城市化对极端高温事件影响研究进展[J].地理科学进展,2015,34(10):1219-1228.[Yang Xuchao,Chen Baode,Hu Kejia.A review of impacts of urbanization on extreme heat events.Progress in Geography,2015,34(10):1219-1228.]
[3]Coseo P,Larsen L.How factors of land use/land cover,building configuration,and adjacent heat sources and sinks explain Urban Heat Islands in Chicago[J].Landscape&urban Planning,2014,125(6):117-129.
[4]Mohajerani A,Bakaric J,Jeffreybailey T.The urban heat island effect its causes and mitigation with reference to the thermal properties of asphalt concrete[J].Journal of Environmental Management,2017,197:522-538.
[5]张佳华,孟倩文,李欣.北京城区城市热岛的多时空尺度变化[J].地理科学,2011,31(11):1349-1354.[Zhang Jiahua,Meng Qianwen,Li Xin.Urban heat island variations in Beijing region in multi spatial and temporal scales.Scientia Geographica Sinica,2011,31(11):1349-1354.]
[6]刘伟东,尤焕苓,孙丹.1971~2010年京津冀大城市热岛效应多时间尺度分析[J].气象,2016,42(5):598-606.[Liu Weidong,You Huanling,Sun Dan.Multi-time scale analysis of megacities heat island effect in Beijing-Tianjin-Hebei region from 1971 to2010.Meteorological Monthly,2016,42(5):598-606.]
[7]寿亦萱,张大林.城市热岛效应的研究进展与展望[J].气象学报,2012,70(3):338-353.[Shou Yixuan,Zhang Dalin.Recent advances in understanding urban heat island effects with some future prospects.Acta Meteorologica Sinica,2012,70(3):338-353.]
[8]高建成,尹泽凯,张睿.快速城镇化地区热岛景观动态变化研究--以唐山市建成区为例[J].干旱区资源与环境,2015,29(9):165-170.[Gao Jiancheng,Yin Zekai,Zhang Rui.Spatial and temporal changes of urban thermal landscape pattern in rapid urbanization area-Taking Tangshan urban built-up area as examples.Journal of Arid Land Resources and Environment,2015,29(9):165-170.]
[9]蒋明卓,曾穗平,曾坚.天津城市扩张及其微气候特征演化研究--基于城市热环境的角度[J].干旱区资源与环境,2015,29(9):159-164.[Jiang Mingzhuo,Zeng Suiping,Zeng Jian.Urban expansion of Tianjin and the micro climate characteristics evolution--Based on the urban thermal environment perspective.Journal of Arid Land Resources and Environment,2015,29(9):159-164.]
[10]徐永明,刘勇洪.基于TM影像的北京市热环境及其与不透水面的关系研究[J].生态环境学报,2013,22(4):639-643.[Xu Yongming,Liu Yonghong.Study on the thermal environment and its relationship with impervious surface in Beijing city using TM image.Ecology and Environmental Sciences,2013,22(4):639-643.]
[11]Zhang Y,Zhan Y,Yu T et al.Urban green effects on land surface temperature caused by surface characteristics:A case study of summer Beijing Metropolitan Region[J].Infrared Physics&Technology,2017,86:35-43.
[12]乔治,田光进.北京市热环境时空分异与区划[J].遥感学报,2014,18(3):715-734.[Qiao Zhi,Tian Guangjin.Spatiotemporal diversity and regionalization of the urban thermal environment in Beijing.Journal of Remote Sensing,2014,18(3):715-734.]
[13]刘勇洪,栾庆祖,权维俊,等.基于多源卫星资料的京津唐城市群热环境研究[J].生态环境学报,2015,24(7):1150-1158.[Liu Yonghong,Luan Qingzu,Quan Weijun et al.Research on heat environment of Beijing-Tianjin-Tangshan urban group based on multisource satellite data.Ecology and Environmental Sciences,2015,24(7):1150-1158.]
[14]周纪,陈云浩,李京,等.基于遥感影像的城市热岛容量模型及其应用--以北京地区为例[J].遥感学报,2008,12(5):734-742.[Zhou Ji,Chen Yunhao,Li Jing et al.A volume model for urban heat island based on remote sensing imagery and its application:A case study in Beijing.Journal of Remote Sensing,2008,12(5):734-742.]
[15]Wang J,Huang B,Fu D J et al.Response of urban heat island to future urban expansion over the Beijing-Tianjin-Hebei metropolitan area[J].Applied Geography,2016,70:26-36.
[16]孟倩文.京津唐城市群热环境的时空变化及其影响因子研究[D].北京:中国气象科学研究院,2011.[Meng Qianwen.Study on spatial and temporal variation of thermal environment and its influencing factors over Beijing-Tianjin-Tangshan urban group.Beijing:Chinese Academy of Meteorological Sciences,2011.]
[17]刘勇洪,房小怡,张硕,等.京津冀城市群热岛定量评估[J].生态学报,2017,37(17):5818-5835.[Liu Yonghong,Fang Xiaoyi,Zhang Shuo et al.Research on quantitative evaluations of heat islands for the Beijing-Tianjin-Hebei Urban Agglomeration.Acta Ecologica Sinica,2017,37(17):5818-5835.]
[18]匡文慧,刘纪远,陆灯盛.京津唐城市群不透水地表增长格局以及水环境效应[J].地理学报,2011,66(11):1486-1496.[Kuang Wenhui,Liu Jiyuan,Lu Dengsheng.Pattern of impervious surface change and its effect on water environment in the Beijing-Tianjin-Tangshan Metropolitan Area.Acta Geographica Sinica,2011,66(11):1486-1496.]
[19]张勇,余涛,顾行发,等.CBERS-02 IRMSS热红外数据地表温度反演及其在城市热岛效应定量化分析中的应用[J].遥感学报,2006,10(5):789-797.[Zhang Yong,Yu Tao,Gu Xingfa et al.Land surface temperature retrieval from CBERS-02 IRMSSthermal infrared data and its applications in quantitative analysis of urban heat island effect.Journal of Remote Sensing,2006,10(5):789-797.]
[20]贾琦,运迎霞.京津冀都市圈城镇化质量测度及区域差异分析[J].干旱区资源与环境,2015,29(3):8-12.[Jia Qi,Yun Yingxia.Measurement of urbanization development quality and analysis of regional disparities in Beijing-Tianjin-Hebei metropolitan region.Journal of Arid Land Resources and Environment,2015,29(3):8-12.]
[21]匡文慧,刘纪远,张增祥,等.21世纪初中国人工建设不透水地表遥感监测与时空分析[J].科学通报,2013,58(Z1):465-478.[Kuang Wenhui,Liu Jiyuan,Zhang Zengxiang et al.Spatiotemporal dynamics of impervious surface areas across China during the early 21st century.Chinese Science Bulletin,2013,58(Z1):465-478.]
[22]Yang L,Huang C,Homer C G et al.An approach for mapping large-area impervious surfaces:Synergistic use of Landsat-7ETM+and high spatial resolution imagery[J].Canadian Journal of Remote Sensing,2003,29(2):230-240.
[23]肖荣波,欧阳志云,蔡云楠,等.基于亚像元估测的城市硬化地表景观格局分析[J].生态学报,2007,27(8):3189-3197.[Xiao Rongbo,Ouyang Zhiyun,Cai Yunnan et al.Urban landscape pattern study based on sub-pixel estimation of impervious surface.Acta Ecologica Sinica,2007,27(8):3189-3197.]
[24]乔琨,朱文泉,胡德勇,等.北京市不同功能区不透水地表时空变化差异[J].地理学报,2017,72(11):2018-2031.[Qiao Kun,Zhu Wenquan,Hu Deyong et al.Examining the distribution and dynamics of impervious surface in different functional zones of Beijing.Acta Geographica sinica,2017,72(11):2018-2031.]
[25]赵璐,赵作权.基于特征椭圆的中国经济空间分异研究[J].地理科学,2014,34(8):979-986.[Zhao Lu,Zhao Zuoquan.Projecting the spatial variation of economic based on the specific ellipses in China.Scientia Geographica Sinica,2014,34(8):979-986.]
[26]Peng J,Xie P,Liu Y et al.Urban thermal environment dynamics and associated landscape pattern factors:A case study in the Beijing metropolitan region[J].Remote Sensing of Environment,2016,173:145-155.
[2]杨续超,陈葆德,胡可嘉.城市化对极端高温事件影响研究进展[J].地理科学进展,2015,34(10):1219-1228.[Yang Xuchao,Chen Baode,Hu Kejia.A review of impacts of urbanization on extreme heat events.Progress in Geography,2015,34(10):1219-1228.]
[3]Coseo P,Larsen L.How factors of land use/land cover,building configuration,and adjacent heat sources and sinks explain Urban Heat Islands in Chicago[J].Landscape&urban Planning,2014,125(6):117-129.
[4]Mohajerani A,Bakaric J,Jeffreybailey T.The urban heat island effect its causes and mitigation with reference to the thermal properties of asphalt concrete[J].Journal of Environmental Management,2017,197:522-538.
[5]张佳华,孟倩文,李欣.北京城区城市热岛的多时空尺度变化[J].地理科学,2011,31(11):1349-1354.[Zhang Jiahua,Meng Qianwen,Li Xin.Urban heat island variations in Beijing region in multi spatial and temporal scales.Scientia Geographica Sinica,2011,31(11):1349-1354.]
[6]刘伟东,尤焕苓,孙丹.1971~2010年京津冀大城市热岛效应多时间尺度分析[J].气象,2016,42(5):598-606.[Liu Weidong,You Huanling,Sun Dan.Multi-time scale analysis of megacities heat island effect in Beijing-Tianjin-Hebei region from 1971 to2010.Meteorological Monthly,2016,42(5):598-606.]
[7]寿亦萱,张大林.城市热岛效应的研究进展与展望[J].气象学报,2012,70(3):338-353.[Shou Yixuan,Zhang Dalin.Recent advances in understanding urban heat island effects with some future prospects.Acta Meteorologica Sinica,2012,70(3):338-353.]
[8]高建成,尹泽凯,张睿.快速城镇化地区热岛景观动态变化研究--以唐山市建成区为例[J].干旱区资源与环境,2015,29(9):165-170.[Gao Jiancheng,Yin Zekai,Zhang Rui.Spatial and temporal changes of urban thermal landscape pattern in rapid urbanization area-Taking Tangshan urban built-up area as examples.Journal of Arid Land Resources and Environment,2015,29(9):165-170.]
[9]蒋明卓,曾穗平,曾坚.天津城市扩张及其微气候特征演化研究--基于城市热环境的角度[J].干旱区资源与环境,2015,29(9):159-164.[Jiang Mingzhuo,Zeng Suiping,Zeng Jian.Urban expansion of Tianjin and the micro climate characteristics evolution--Based on the urban thermal environment perspective.Journal of Arid Land Resources and Environment,2015,29(9):159-164.]
[10]徐永明,刘勇洪.基于TM影像的北京市热环境及其与不透水面的关系研究[J].生态环境学报,2013,22(4):639-643.[Xu Yongming,Liu Yonghong.Study on the thermal environment and its relationship with impervious surface in Beijing city using TM image.Ecology and Environmental Sciences,2013,22(4):639-643.]
[11]Zhang Y,Zhan Y,Yu T et al.Urban green effects on land surface temperature caused by surface characteristics:A case study of summer Beijing Metropolitan Region[J].Infrared Physics&Technology,2017,86:35-43.
[12]乔治,田光进.北京市热环境时空分异与区划[J].遥感学报,2014,18(3):715-734.[Qiao Zhi,Tian Guangjin.Spatiotemporal diversity and regionalization of the urban thermal environment in Beijing.Journal of Remote Sensing,2014,18(3):715-734.]
[13]刘勇洪,栾庆祖,权维俊,等.基于多源卫星资料的京津唐城市群热环境研究[J].生态环境学报,2015,24(7):1150-1158.[Liu Yonghong,Luan Qingzu,Quan Weijun et al.Research on heat environment of Beijing-Tianjin-Tangshan urban group based on multisource satellite data.Ecology and Environmental Sciences,2015,24(7):1150-1158.]
[14]周纪,陈云浩,李京,等.基于遥感影像的城市热岛容量模型及其应用--以北京地区为例[J].遥感学报,2008,12(5):734-742.[Zhou Ji,Chen Yunhao,Li Jing et al.A volume model for urban heat island based on remote sensing imagery and its application:A case study in Beijing.Journal of Remote Sensing,2008,12(5):734-742.]
[15]Wang J,Huang B,Fu D J et al.Response of urban heat island to future urban expansion over the Beijing-Tianjin-Hebei metropolitan area[J].Applied Geography,2016,70:26-36.
[16]孟倩文.京津唐城市群热环境的时空变化及其影响因子研究[D].北京:中国气象科学研究院,2011.[Meng Qianwen.Study on spatial and temporal variation of thermal environment and its influencing factors over Beijing-Tianjin-Tangshan urban group.Beijing:Chinese Academy of Meteorological Sciences,2011.]
[17]刘勇洪,房小怡,张硕,等.京津冀城市群热岛定量评估[J].生态学报,2017,37(17):5818-5835.[Liu Yonghong,Fang Xiaoyi,Zhang Shuo et al.Research on quantitative evaluations of heat islands for the Beijing-Tianjin-Hebei Urban Agglomeration.Acta Ecologica Sinica,2017,37(17):5818-5835.]
[18]匡文慧,刘纪远,陆灯盛.京津唐城市群不透水地表增长格局以及水环境效应[J].地理学报,2011,66(11):1486-1496.[Kuang Wenhui,Liu Jiyuan,Lu Dengsheng.Pattern of impervious surface change and its effect on water environment in the Beijing-Tianjin-Tangshan Metropolitan Area.Acta Geographica Sinica,2011,66(11):1486-1496.]
[19]张勇,余涛,顾行发,等.CBERS-02 IRMSS热红外数据地表温度反演及其在城市热岛效应定量化分析中的应用[J].遥感学报,2006,10(5):789-797.[Zhang Yong,Yu Tao,Gu Xingfa et al.Land surface temperature retrieval from CBERS-02 IRMSSthermal infrared data and its applications in quantitative analysis of urban heat island effect.Journal of Remote Sensing,2006,10(5):789-797.]
[20]贾琦,运迎霞.京津冀都市圈城镇化质量测度及区域差异分析[J].干旱区资源与环境,2015,29(3):8-12.[Jia Qi,Yun Yingxia.Measurement of urbanization development quality and analysis of regional disparities in Beijing-Tianjin-Hebei metropolitan region.Journal of Arid Land Resources and Environment,2015,29(3):8-12.]
[21]匡文慧,刘纪远,张增祥,等.21世纪初中国人工建设不透水地表遥感监测与时空分析[J].科学通报,2013,58(Z1):465-478.[Kuang Wenhui,Liu Jiyuan,Zhang Zengxiang et al.Spatiotemporal dynamics of impervious surface areas across China during the early 21st century.Chinese Science Bulletin,2013,58(Z1):465-478.]
[22]Yang L,Huang C,Homer C G et al.An approach for mapping large-area impervious surfaces:Synergistic use of Landsat-7ETM+and high spatial resolution imagery[J].Canadian Journal of Remote Sensing,2003,29(2):230-240.
[23]肖荣波,欧阳志云,蔡云楠,等.基于亚像元估测的城市硬化地表景观格局分析[J].生态学报,2007,27(8):3189-3197.[Xiao Rongbo,Ouyang Zhiyun,Cai Yunnan et al.Urban landscape pattern study based on sub-pixel estimation of impervious surface.Acta Ecologica Sinica,2007,27(8):3189-3197.]
[24]乔琨,朱文泉,胡德勇,等.北京市不同功能区不透水地表时空变化差异[J].地理学报,2017,72(11):2018-2031.[Qiao Kun,Zhu Wenquan,Hu Deyong et al.Examining the distribution and dynamics of impervious surface in different functional zones of Beijing.Acta Geographica sinica,2017,72(11):2018-2031.]
[25]赵璐,赵作权.基于特征椭圆的中国经济空间分异研究[J].地理科学,2014,34(8):979-986.[Zhao Lu,Zhao Zuoquan.Projecting the spatial variation of economic based on the specific ellipses in China.Scientia Geographica Sinica,2014,34(8):979-986.]
[26]Peng J,Xie P,Liu Y et al.Urban thermal environment dynamics and associated landscape pattern factors:A case study in the Beijing metropolitan region[J].Remote Sensing of Environment,2016,173:145-155.