夜光遥感大数据视角下的中国城市化时空特征
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摘要
社会经济的高速发展直接驱动了中国过去几十年的持续快速城市化进程。城市化是一个典型的复杂地理现象,伴随着高密度人口聚集、土地利用改变、基础设施建设和生态环境变化等系列人和自然交互过程的发生。深入理解城市发展的时空演化规律对研究、规划、管理和相关政策制定在内的诸多领域都有十分重要的意义。近些年来,由于快速发展的夜光遥感大数据具有空间清晰的与城市化有关的社会经济活动强度的感知信息,其为探索城市和城市化问题提供了新的研究途径。虽然有许多成果对利用夜光遥感数据进行城市化的研究进行了探讨,但大部分集中在城市化面积、人口规模和其他社会经济变量的定量相关和数值统计分析上,仍然缺乏对中国过去几十年来的城市化时空特征的综合多角度分析和理解。本研究利用1992-2013年的夜光遥感时间序列大数据,从夜光照亮面积、亮度变化时间转折点、不同亮度区的空间结构转换和亮度信号的空间扩散速度4个方面进行了定量化的信息提取与分析。研究结果从夜光辐射遥感大数据的视角综合揭示了中国在过去研究期间包括城市空间扩展、城市化发展的时间分布、城市空间结构演化和城市化活动空间扩散速度在内的定量时空特征。本研究的结果可以为深入理解中国城市化的时空模式与演化特征提供新的参考。
The rapid growth of nation's economy has driven the unprecedented pace of urbanization in China over the past several decades.Urbanization process is a complicated geographical phenomenon involving humannature interactions,such as population aggregation,land use change,infrastructure construction and ecoenvironmental changes.Hence,an understanding of the spatiotemporal dynamics of urban development is increasingly important for a variety of issues including research,planning,management and policy decision making.Owing to a spatially and temporally explicit manner of sensed information with respect to the magnitude of socio-economic activity related to urban development,the recent emergence of satellite-derived nighttime light data provides new means for investigating urban patterns and urbanization processes.In the present study,four kinds of quantitative information,including the spatial lighting area,temporal turning point,the spatial transformation of different types of lit areas and the velocity of spatial disperse of nighttime lightings signals,have been obtained and quantitatively analyzed based on time series of big data of annual composite products of nighttime light radiances during the period 1992-2013 from the Defense Meteorological Satellite Program(DMSP).Analysis results reveal the spatiotemporal patterns of China's urbanization over the past 22 years from the perspective of remotely sensed big data of artificial nighttime lighting signals in context of the spatial expansion,the distribution of urbanization onset time,the evolution of spatial structure and the urbanization velocity.This study can provide new insights into the understating of the fundamental spatiotemporal features of the rapid urbanization process in the present-day China using the remotely sensed big data of observed anthropogenic nighttime lighting signals.
The rapid growth of nation's economy has driven the unprecedented pace of urbanization in China over the past several decades.Urbanization process is a complicated geographical phenomenon involving humannature interactions,such as population aggregation,land use change,infrastructure construction and ecoenvironmental changes.Hence,an understanding of the spatiotemporal dynamics of urban development is increasingly important for a variety of issues including research,planning,management and policy decision making.Owing to a spatially and temporally explicit manner of sensed information with respect to the magnitude of socio-economic activity related to urban development,the recent emergence of satellite-derived nighttime light data provides new means for investigating urban patterns and urbanization processes.In the present study,four kinds of quantitative information,including the spatial lighting area,temporal turning point,the spatial transformation of different types of lit areas and the velocity of spatial disperse of nighttime lightings signals,have been obtained and quantitatively analyzed based on time series of big data of annual composite products of nighttime light radiances during the period 1992-2013 from the Defense Meteorological Satellite Program(DMSP).Analysis results reveal the spatiotemporal patterns of China's urbanization over the past 22 years from the perspective of remotely sensed big data of artificial nighttime lighting signals in context of the spatial expansion,the distribution of urbanization onset time,the evolution of spatial structure and the urbanization velocity.This study can provide new insights into the understating of the fundamental spatiotemporal features of the rapid urbanization process in the present-day China using the remotely sensed big data of observed anthropogenic nighttime lighting signals.
引文
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[12]Small C,Elvidge C D,Balk D,et al.Spatial scaling of stable night lights[J].Remote Sensing of Environment,2011115:269-280.
[13]Zhang Q,Seto K C.Mapping urbanization dynamics at regional and global scales using multi-temporal DMSPOLS nighttime light data[J].Remote Sensing of Environment,2011,115:2320-2329.
[14]Elvidge C D,Baugh K E,Anderson S J,et al.The nigh light development index(NLDI):A spatially explicit measure of human development from satellite[J].Social Geography,2012,7:23-35.
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[16]Shi K F,Huang C,Yu B L,et al.Evaluation of NPP-VI-IRS nighttime light composite data for extracting built-up urban areas[J].Remote Sensing Letters,2014,5(4):358-366.
[17]Wei Y,Liu H X,Song W,et al.Normalization of time series DMSP-OLS nighttime light images for urban growth analysis with pseudo invariant features[J].Landscape and Urban Planning,2014,128(1):1-13.
[18]Yu B L,Shu S,Liu H X,et al.Object-based spatial cluster analysis of urban landscape pattern using nighttime light satellite images:A case study of China[J].International Journal of Geographical Information Science,2014,28(11):2328-2355.
[19]Yu B L,Shi K F,Hu Y J,et al.Poverty evaluation using NPP-VIIRS nighttime light composite data at the county level in China[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2015,8(3):1217-1229.
[20]Chen Z Q,Yu B L,Song W,et al.A new approach for detecting urban centers and their spatial structure with nighttime light remote sensing[J].IEEE Transactions on Geoscience and Remote Sensing,2017,55(11):6305-6319.
[21]李小敏,郑新奇,袁涛.DMSP/OLS夜间灯光数据研究成果知识图谱分析[J].地球信息科学学报,2018,20(3):351-359.[Li X M,Zheng X Q,Yuan T.Knowledge mapping of research results on DMSP/OLS nighttime light data[J].Journal of Geo-information Science,2018,20(3):351-359.]
[22]Elvidge C D,Ziskin D,Baugh,K E,et al.A fifteen year record of global natural gas flaring derived from satellite data[J].Energies,2009,2:595-622.
[23]卓莉,张晓帆,郑璟,等.基于EVI指数的DMSP/OLS夜间灯光数据去饱和方法[J].地理学报,2015,70(8):1339-1350.[Zhou L,Zhang X F,Zheng Jing,et al.An EVI_based method to reduce saturation of DMSP/OLSnighttime light data[J].Acta Geographica Sinica,2015,70(8):1339-1350.]
[24]Xu T,Ma T,Zhou C H,et al.Characterizing spatio-temporal dynamics of urbanization in China using time series of DMSP/OLS night light data[J].Remote Sensing,2014,6:7708-7731.
[25]Ma T,Zhou Y K,Zhou C H,et al.Night-time light derived estimation of spatio-temporal characteristics of urbanization dynamics using DMSP/OLS satellite data[J].Remote Sensing of Environment,2015,158:453-464.
[26]Ma T,Yin Z,Li B L,et al.Quantitative estimation of the velocity of urbanization in China using nighttime luminosity data[J].Remote Sensing,2016,8(2):94.
[27]Elvidge C D,Baugh K E,Zhizhin M,et al.Why VIIRSdata are superior to DMSP for mapping nighttime lights[J].Proceedings of the Asia-Pacific Advanced Network,2013,35:62-69.
[2]王新生,刘纪远,庄大方,等.中国特大城市空间形态变化的时空特征[J].地理学报,2005,60(3):392-400.[Wang XS,Liu J Y,Zhuang D F,et al.Spatial-temporal changes of urban spatial morphology in China[J].Acta Geographica Sinica,2005,60(3):392-400.]
[3]周春山,叶昌东.中国特大城市空间增长特征记忆原因分析[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.]
[4]杨坤矗,毕润成,孙然好,等.京津冀地区城市化发展时空差异特征[J].生态学报,2017,37(12):3998-4007.[Yang KC,Bi R C,Sun R H,et al.The spatio-temporal changes of urbanization in Beijing-Tianjin-Hebei region in Northern China[J].Acta Ecologica Sinica,2017,37(12):3998-4007.]
[5]Elvidge C D,Baugh K E,Kihn E A,et al.Mapping city lights with nighttime data from the DMSP operational linescan system[J].Photogrammetric Engineering&Remote Sensing,1997,63:727-734.
[6]Elvidge C D,Baugh K E,Dietz J B,et al.Radiance calibration of DMSP-OLS low light imaging data of human settlements[J].Remote Sensing of Environment,1999,68:77-88.
[7]Doll C N H,Muller J P,Elvidge C D.Night-time imagery as a tool for global mapping of socioeconomic parameters and greenhouse gas emissions[J].Ambio,2000,29:157-162.
[8]卓莉,史培军,陈晋,等.20世纪90年代中国城市时空变化特征:基于灯光指数CNLI方法的探讨[J].地理学报2003,58(6):893-902.[Zhuo L,Shi P J,Chen J,et al.Application of compound night light index derived from DMSP/OLS data to urbanization analysis in China in the1990s[J].Acta Geographica Sinica,2003,58(6):893-902.]
[9]陈晋,卓莉,史培军,等.基于DMSP/OLS数据的中国城市化过程研究:反映区域城市化水平的灯光指数的构建[J].遥感学报,2003,7(3):168-175,241.[Chen J,Zhuo LShi P J,et al.The study on urbanization process in China based on DMSP/OLS data:Development of a light index for urbanization level estimation[J].Journal of Remote Sensing,2003,7(3):168-175,241.]
[10]Doll C N H,Muller J P,Morley J G.Mapping regiona economic activity from night-time light satellite imagery[J].Ecological Economics,2006,57:75-92.
[11]Small C,Elvidge C D.Mapping decadal change in anthropogenic night light[J].Procedia Environmental Sciences2011,7:353-358.
[12]Small C,Elvidge C D,Balk D,et al.Spatial scaling of stable night lights[J].Remote Sensing of Environment,2011115:269-280.
[13]Zhang Q,Seto K C.Mapping urbanization dynamics at regional and global scales using multi-temporal DMSPOLS nighttime light data[J].Remote Sensing of Environment,2011,115:2320-2329.
[14]Elvidge C D,Baugh K E,Anderson S J,et al.The nigh light development index(NLDI):A spatially explicit measure of human development from satellite[J].Social Geography,2012,7:23-35.
[15]Small C,Elvidge C D.Night on earth:Mapping decada changes of anthropogenic night light in Asia[J].International Journal of Applied Earth Observation and Geo-information,2013,22:40-52.
[16]Shi K F,Huang C,Yu B L,et al.Evaluation of NPP-VI-IRS nighttime light composite data for extracting built-up urban areas[J].Remote Sensing Letters,2014,5(4):358-366.
[17]Wei Y,Liu H X,Song W,et al.Normalization of time series DMSP-OLS nighttime light images for urban growth analysis with pseudo invariant features[J].Landscape and Urban Planning,2014,128(1):1-13.
[18]Yu B L,Shu S,Liu H X,et al.Object-based spatial cluster analysis of urban landscape pattern using nighttime light satellite images:A case study of China[J].International Journal of Geographical Information Science,2014,28(11):2328-2355.
[19]Yu B L,Shi K F,Hu Y J,et al.Poverty evaluation using NPP-VIIRS nighttime light composite data at the county level in China[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2015,8(3):1217-1229.
[20]Chen Z Q,Yu B L,Song W,et al.A new approach for detecting urban centers and their spatial structure with nighttime light remote sensing[J].IEEE Transactions on Geoscience and Remote Sensing,2017,55(11):6305-6319.
[21]李小敏,郑新奇,袁涛.DMSP/OLS夜间灯光数据研究成果知识图谱分析[J].地球信息科学学报,2018,20(3):351-359.[Li X M,Zheng X Q,Yuan T.Knowledge mapping of research results on DMSP/OLS nighttime light data[J].Journal of Geo-information Science,2018,20(3):351-359.]
[22]Elvidge C D,Ziskin D,Baugh,K E,et al.A fifteen year record of global natural gas flaring derived from satellite data[J].Energies,2009,2:595-622.
[23]卓莉,张晓帆,郑璟,等.基于EVI指数的DMSP/OLS夜间灯光数据去饱和方法[J].地理学报,2015,70(8):1339-1350.[Zhou L,Zhang X F,Zheng Jing,et al.An EVI_based method to reduce saturation of DMSP/OLSnighttime light data[J].Acta Geographica Sinica,2015,70(8):1339-1350.]
[24]Xu T,Ma T,Zhou C H,et al.Characterizing spatio-temporal dynamics of urbanization in China using time series of DMSP/OLS night light data[J].Remote Sensing,2014,6:7708-7731.
[25]Ma T,Zhou Y K,Zhou C H,et al.Night-time light derived estimation of spatio-temporal characteristics of urbanization dynamics using DMSP/OLS satellite data[J].Remote Sensing of Environment,2015,158:453-464.
[26]Ma T,Yin Z,Li B L,et al.Quantitative estimation of the velocity of urbanization in China using nighttime luminosity data[J].Remote Sensing,2016,8(2):94.
[27]Elvidge C D,Baugh K E,Zhizhin M,et al.Why VIIRSdata are superior to DMSP for mapping nighttime lights[J].Proceedings of the Asia-Pacific Advanced Network,2013,35:62-69.
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