整合DMSP/OLS和NPP/VIIRS夜间灯光遥感数据的长江三角洲城市格局时空演化研究

doi:10.12082/dqxxkx.2021.200380

地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (5): 837-849.doi: 10.12082/dqxxkx.2021.200380

• 地理空间分析综合应用 • 上一篇下一篇

整合DMSP/OLS和NPP/VIIRS夜间灯光遥感数据的长江三角洲城市格局时空演化研究

许正森(), 徐永明^*()

南京信息工程大学遥感与测绘工程学院,南京 210044

收稿日期:2020-07-18 修回日期:2020-09-04 出版日期:2021-05-25 发布日期:2021-07-25
通讯作者: *徐永明（1980— ）,男,江苏连云港人,博士,教授,研究方向为资源环境遥感。E-mail:xym30@263.net
作者简介:许正森（1998— ）,男,江苏徐州人,硕士生,研究方向为夜光遥感和模式识别。E-mail:xuzs@nuist.edu.cn
基金资助:
教育部人文社会科学研究基金项目(17YJCZH205);国家自然科学基金项目(41871028);江苏省环境监测科研基金项目(1903);江苏省青蓝工程(R2019Q03)

Study on the Spatio-Temporal Evolution of the Yangtze River Delta Urban Agglomeration by Integrating Dmsp/Ols and Npp/Viirs Nighttime Light Data

XU Zhengsen(), XU Yongming^*()

School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China

Received:2020-07-18 Revised:2020-09-04 Online:2021-05-25 Published:2021-07-25
Contact: XU Yongming
Supported by:
Humanities and Social Sciences Foundation of the Ministry of Education of China(17YJCZH205);National Natural Science Foundation of China(41871028);Environmental Monitoring Foundation of Jiangsu Province(1903);Qing Lan Project of Jiangsu Province(R2019Q03)

摘要/Abstract

摘要：

本文基于1992—2012年DMSP/OLS和2012—2018年NPP/VIIRS夜间灯光遥感数据,对长江三角洲城市群时空演化格局进行监测。考虑到不同卫星夜间灯光遥感数据之间的不一致性以及城市核心区亮度过饱和问题,对DMSP/OLS和NPP/VIIRS数据进行连续性校正、去饱和处理和一致性校正,构建长江三角洲区域1992—2018年长时间序列多源夜间灯光遥感数据集。利用二分法基于该数据逐年提取长江三角洲城市群各城市建成区空间分布,计算加权标准差椭圆和Zipf系数进行重心变化和方向性分布变化、规模体系变化等监测。结果表明： ① 本研究采用的连续性校正、去饱和处理和一致性校正方法能够构建稳定的长时间序列多源夜间灯光遥感数据集; ② 基于二分法提取的建成区面积平均绝对误差为6.85 km²,平均相对误差为8.10%; ③ 长三角城市群重心较为稳定,始终在苏州市境内的太湖沿岸附近,呈现出向东南方向移动的趋势城市群呈西北—东南方向分布,且分布方向有向南北方向转动的趋势,标准差椭圆的扁率持续减小,表明城市群的方向性分布减弱; ④ Zipf系数始终在1附近且呈缓慢降低的趋势,城市规模分布较为均衡。

关键词: DMSP/OLS, NPP/VIIRS, 夜间灯光, 长江三角洲, 城市群, 时空格局演变, 校正方法, VANUI

Abstract:

Accurately quantifying the spatiotemporal evolution of urban agglomerations is important for city management plan and urban agglomeration development strategy. In this study, the spatiotemporal evolution of the Yangtze River Delta (YRD) urban agglomeration was characterized based on the DMSP/OLS nighttime light (NTL) data from 1992 to 2012 and the NPP/VIIRS NTL data from 2012 to 2018. Considering that the discrepancy between the NTL data from different satellites or sensors and the oversaturation of DMSP/OLS NTL data in urban areas limit the applications of integrating NPP/VIIRS and DMSP/OLS NTL data in monitoring the urban expansion dynamics, discrepancy correction and saturation correction were conducted to produce a temporally consistent NTL dataset combining the two NTL datasets during 1992—2018. Using the city-level built-up data obtained from the statistical yearbook as the reference, the optimal threshold values were determined by a dichotomy method to extract annual urban build-up areas in the YRD urban agglomeration from the long-term NTL dataset. Based on the extracted annual urban build-up areas, the expansion rate, centroid (center of gravity), directional distribution, and city-size distribution of the YRD urban agglomeration were analyzed using the standard deviation ellipsoid method and the Zipf coefficient. Our results show that: (1) The discrepancy correction and saturation correction procedures employed in this study effectively improved the continuity and comparability of multi-source NTL data with less reference data. We produced a temporally consistent nighttime light dataset during the period of 1982—2018; (2) The annual build-up areas in the YRD urban agglomeration extracted by the dichotomy method achieved a good accuracy, with a mean relative error of 8.10% and a mean absolute error of 6.85 km²; (3) The city centroid of the YRD urban agglomeration was located along the Taihu Lake in Suzhou city and showed a trend of slowly moving southeast from 1982 to 2018. The YRD urban agglomeration was distributed along northwest-southeast direction, and the direction gradually shifted to the north-south then. The oblateness of weighted standard deviation ellipse gradually decreased, indicating a decrease of the directional distribution of the YRD urban agglomeration over time. This trend also suggested that the development of cities in this urban agglomeration had become more balanced in past two decades; (4) The Zipf index of the YRD urban agglomeration was close to 1 and slowly decreased, suggesting a relatively balanced pattern of the city-size distribution of this urban agglomeration.

Key words: DMSP/OLS, NPP/VIIRS, night-time light, YRD, urban agglomeration, spatiotemporal patterns dynamics, correction method, VANUI

许正森, 徐永明. 整合DMSP/OLS和NPP/VIIRS夜间灯光遥感数据的长江三角洲城市格局时空演化研究[J]. 地球信息科学学报, 2021, 23(5): 837-849.DOI:10.12082/dqxxkx.2021.200380

XU Zhengsen, XU Yongming. Study on the Spatio-Temporal Evolution of the Yangtze River Delta Urban Agglomeration by Integrating Dmsp/Ols and Npp/Viirs Nighttime Light Data[J]. Journal of Geo-information Science, 2021, 23(5): 837-849.DOI:10.12082/dqxxkx.2021.200380

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参考文献 56

[1]	国家统计局. 中国统计年鉴[M]. 北京: 中国统计出版社, 2011.
	[ National Bureau of Statistics. China Statistical Yearbook[M]. Beijing: China Statistics Press, 2011. ]
[2]	中国住房和城乡建设部. 2011年中国城市结构统计年鉴[M]. 北京: 中国统计出版社, 2011.
	[ Ministry of Housing and Urban-Rural Development of China, 2011 China City Structure Statistical Yearbook[M]. Beijing: China Statistics Press, 2011. ]
[3]	国家统计局. 2019年末城镇常住人口[EB/OL]. http://data.stats.gov.cn/ .
	[ National Bureau of Statistics. Urban permanent population at the end of 2019[EB/OL]. http://data.stats.gov.cn/. ]
[4]	梁泽, 黄姣, 韦飞黎, 等. 基于夜光遥感影像与百度POI数据的中国城市群空间范围识别方法[J]. 地理研究, 2020,39(1):92-102. doi: 10.11821/dlyj020181002
	[ Liang Z, Huang J, Wei F L, et al. Identifying the spatial range of urban agglomerations in China based on night light remote sensing and POI data[J]. Geographical Research, 2020,39(1):92-102. ]
[5]	Liu J Y, Liu M L, Zhuang D F, et al. Study on spatial pattern of land-use change in China during 1995-2000[J]. Science in China Series D: Earth Sciences, 2003,46(4):373-384.
[6]	Tan M H, Li X B, Xie H, et al. Urban land expansion and arable land loss in China: A case study of Beijing-Tianjin-Hebei region[J]. Land Use Policy, 2005,22(3):187-196. doi: 10.1016/j.landusepol.2004.03.003
[7]	Shao M, Tang X Y, Zhang Y H, et al. City clusters in China: Air and surface water pollution[J]. Frontiers in Ecology and the Environment, 2006,4(7):353-361. doi: 10.1890/1540-9295(2006)004[0353:CCICAA]2.0.CO;2
[8]	Weng Q H. Modeling urban growth effects on surface runoff with the integration of remote sensing and GIS[J]. Environmental Management, 2001,28(6):737-748. pmid: 11915963
[9]	Zhou L, Dickinson R E, Tian Y, et al. Evidence for a significant urbanization effect on climate in China[J]. Proceedings of the National Academy of Sciences of the United States of America, 2004,101(26):9540-9544.
[10]	Zhao S Q, Da L J, Tang Z Y, et al. Ecological consequences of rapid urban expansion: Shanghai, China[J]. Frontiers in Ecology and the Environment, 2006,4(7):341-346. doi: 10.1890/1540-9295(2006)004[0341:ECORUE]2.0.CO;2
[11]	王晓慧. 基于DMSP/OLS夜间灯光数据的中国近30年城镇扩展研究[D]. 南京:南京大学, 2013.
	[ Wang X H. Urban expansion in China over the past 30 years detected using DMSP/OLS nighttime light data[D]. Nanjing: Nanjing University, 2013. ]
[12]	吴建楠, 程绍铂, 姚士谋. 中国城市群空间结构研究进展[J]. 现代城市研究, 2013,28(12):97-101.
	[ Wu J N, Cheng S B, Yao S M. Review and prospect of research on spatial structure of China's urban agglomerations[J]. Modern Urban Research, 2013,28(12):97-101. ]
[13]	梅安新. 遥感导论[M]. 北京: 高等教育出版社, 2001.
	[ Mei A X. An introduction to remote sensing[M]. Beijing: Higher Education Press, 2001. ]
[14]	Carter H. The study of urban geography[M]. Hachette: A Hodder Arnold Publication, 1995.
[15]	陈佐旗. 基于多源夜间灯光遥感影像的多尺度城市空间形态结构分析[D]. 上海:华东师范大学, 2017.
	[ Chen Z Q. A multiscale analysis on urban area and spatial structure based on nighttime light data[D]. Shanghai: East Normal China University, 2017. ]
[16]	Croft T A. Nighttime Images of the Earth from Space[J]. Scientific American, 1978,239(1):86-101. doi: 10.1038/scientificamerican0778-86
[17]	L.Imhoff M, Lawrence W T, Stutzer D C, et al. A technique for using composite DMSP/OLS“City Lights”satellite data to map urban area[J]. Remote Sensing of Environment, 1997,61(3):361-370. doi: 10.1016/S0034-4257(97)00046-1
[18]	Small C, Pozzi F, Elvidge C D. Spatial analysis of global urban extent from DMSP-OLS night lights[J]. Remote Sensing of Environment, 2005,96(3):277-291. doi: 10.1016/j.rse.2005.02.002
[19]	Sutton P. Modeling population density with night-time satellite imagery and GIS[J]. Computers, Environment and Urban Systems, 1997,21(3/4):227-244. doi: 10.1016/S0198-9715(97)01005-3
[20]	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,T001.
	[ Chen J, Zhuo L, Shi 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, T001. ]
[21]	杨任飞, 罗红霞, 周盛, 等. 夜间灯光数据驱动的成渝城市群空间形成过程重建及分析[J]. 地球信息科学学报, 2017,19(5):653-661. doi: 10.3724/SP.J.1047.2017.00653
	[ Yang R F, Luo H X, Zhou S, et al. Restoring and analyzing the space forming process of Chengdu-Chongqing urban agglomeration by using DMSP/OLS night-time light data[J]. Journal of Geo-information Science, 2017,19(5):653-661. ]
[22]	Chen Z, Yu B, Zhou Y, et al. Mapping global urban areas from 2000 to 2012 using time-series nighttime light data and MODIS products[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019,12(4):1143-1153. doi: 10.1109/JSTARS.4609443
[23]	Duque J C, Lozano-Gracia N, Patino J E, et al. Spatiotemporal dynamics of urban growth in Latin American cities: An analysis using nighttime light imagery[J]. Landscape and Urban Planning, 2019,191:103640. doi: 10.1016/j.landurbplan.2019.103640
[24]	林中立, 徐涵秋, 黄绍霖. 基于DMSP/OLS夜间灯光影像的中国东部沿海地区城市扩展动态监测[J]. 地球信息科学学报, 2019,21(7):1074-1085. doi: 10.12082/dqxxkx.2019.180600
	[ Lin Z L, Xu H Q, Huang S L. Monitoring of the urban expansion dynamics in China's east Coast using DMSP/OLS nighttime light imagery[J]. Journal of Geo-information Science, 2019,21(7):1074-1085. ]
[25]	Chen J, Wei H, Li N, et al. Exploring the spatial-temporal dynamics of the Yangtze River Delta urban agglomeration based on night-time light remote sensing technology[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI: 10.1109/JSTARS.2020.3022178.
[26]	陈永文. 长江三角洲自然地理概貌[J]. 社会科学, 1983,10(5):35-37.
	[ Chen Y W. An overview of the natural geography of the Yangtze River Delta[J]. Social Sciences Shanghai China, 1983,10(5):35-37. ]
[27]	新华社. 中共中央国务院印发《长江三角洲区域一体化发展规划纲要》[EB/OL]. http://www.gov.cn/zhengce/2019-12/01/content_5457442.htm.
	[ Xinhua News Agency. The Communist Party of China Central Committee and the State Council jointly issued an outline of the integrated regional development of the Yangtze River Delta [EB/OL]. http://www.gov.cn/zhengce/2019-12/01/content_5457442.htm. ]
[28]	National Geophysical Data Center. Operational Line scan System-data Description [EB/OL]. 2008-09-06. http://www.ngdc.noaa.gov/dmsp/sensors/ols.html.
[29]	Levin N, Kyba C C M, Zhang Q L, et al. Remote sensing of night lights: a review and an outlook for the future[J]. Remote Sensing of Environment, 2020,237(1):111443. doi: 10.1016/j.rse.2019.111443
[30]	徐新良. 中国月度植被指数(NDVI)空间分布数据集. 中国科学院资源环境科学数据中心数据注册与出版系统(http://www.resdc.cn/DOI), 2018. DOI: 10.12078/2018060 602.
	[ Xu X L. China monthly vegetation index (NDVI) spatial distribution data set. Data registration and publication system of Resource and Environment Data Cloud Platform (http://www.resdc.cn/DOI), 2018. DOI: 10.12078/2018060602. ]
[31]	Fensholt R, Rasmussen K, Nielsen T T, et al. Evaluation of earth observation based long term vegetation trends: Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data[J]. Remote Sensing of Environment, 2009,113(9):1886-1898. doi: 10.1016/j.rse.2009.04.004
[32]	蒲英霞, 马荣华, 马晓冬, 等. 长江三角洲地区城市规模分布的时空演变特征[J]. 地理研究, 2009,28(1):161-172.
	[ Pu Y X, Ma R H, Ma X D, et al. Spatio-temporal dynamics of City-size distribution in Yangtze River Delta[J]. Geographical Research, 2009,28(1):161-172. ]
[33]	国家统计局城市社会经济调查司. 中国城市统计年鉴[M]. 北京: 中国统计出版社, 2011.
[34]	曹子阳, 吴志峰, 匡耀求, 等. DMSP/OLS夜间灯光影像中国区域的校正及应用[J]. 地球信息科学学报, 2015,17(9):1092-1102. doi: 10.3724/SP.J.1047.2015.01092
	[ Cao Z Y, Wu Z F, Kuang Y Q, et al. Correction of DMSP/OLS night-time light images and its application in China[J]. Journal of Geo-information Science, 2015,17(9):1092-1102. ]
[35]	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(1):62-72. doi: 10.1016/j.landurbplan.2012.02.013
[36]	Yu B, Tang M, Wu Q, et al. Urban built-up area extraction from log- transformed NPP-VIIRS nighttime light composite data[J]. IEEE Geoscience and Remote Sensing Letters, 2018,15(8):1279-1283. doi: 10.1109/LGRS.2018.2830797
[37]	Zhao M, Zhou Y Y, Li X C, et al. Building a series of consistent night-time light data (1992-2018) in Southeast Asia by integrating DMSP-OLS and NPP-VIIRS[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020,58(3):1843-1856. doi: 10.1109/TGRS.36
[38]	Ma Q, He C Y, Wu J G, et al. Quantifying spatiotemporal patterns of urban impervious surfaces in China: An improved assessment using nighttime light data[J]. Landscape and Urban Planning, 2014,130(5):36-49. doi: 10.1016/j.landurbplan.2014.06.009
[39]	Li X, Li D R, Xu H M, et al. Intercalibration between DMSP/OLS and VIIRS night-time light images to evaluate City light dynamics of Syria's major human settlement during Syrian Civil War[J]. International Journal of Remote Sensing, 2017,38(21):5934-5951. doi: 10.1080/01431161.2017.1331476
[40]	Elvidge C D, Baugh K E, Zhizhin M, et al. Why VIIRS data are superior to DMSP for mapping nighttime lights[J]. Proceedings of the Asia-Pacific Advanced Network, 2013,35(7):62-69. doi: 10.7125/APAN.35
[41]	He C Y, Shi P J, Li J G, et al. Restoring urbanization process in China in the 1990s by using non-radiance-calibrated DMSP/OLS nighttime light imagery and statistical data[J]. Chinese Science Bulletin, 2006,51(13):1614-1620. doi: 10.1007/s11434-006-2006-3
[42]	陈昕, 彭建, 刘焱序, 等. 基于DMSP/OLS夜间灯光数据的京津冀地区城市空间扩展与空间关联测度[J]. 地理研究, 2018,37(5):898-909. doi: 10.11821/dlyj201805004
	[ Chen X, Peng J, Liu Y X, et al. Measuring spatial expansion and correlations of cities in Beijing-Tianjin-Hebei Urban Agglomeration using DMSP/OLS nighttime light data[J]. Geographical Research, 2018,37(5):898-909. ]
[43]	Lefever D W. Measuring geographic concentration by means of the standard deviational ellipse[J]. American Journal of Sociology, 1926,32(1):88-94. doi: 10.1086/214027
[44]	赵作权. 地理空间分布整体统计研究进展[J]. 地理科学进展, 2009,28(1):1-8. doi: 10.11820/dlkxjz.2009.01.001
	[ Zhao Z Q. Global statistics of spatial distribution: a literature review[J]. Progress in Geography, 2009,28(1):1-8. ]
[45]	卢萌. 白话空间统计之九:方向分布(标准差椭圆)[EB/OL]. https://blog.csdn.net/allenlu2008/article/details/103028570.
	[ Lu M. Vernacular Spatial Statistics IX: Directional Distribution (Standard Deviation Ellipse)[EB/OL]. https://blog.csdn.net/allenlu2008/article/details/103028570. ]
[46]	路春燕, 许燕婷, 林晓晴, 等. 基于DMSP/OLS夜间灯光数据的环渤海城市群时空演变研究[J]. 国土资源遥感, 2019,31(4):218-226.
	[ Lu C Y, Xu Y T, Lin X Q, et al. Study of spatio-temporal evolution of the circum-Bohai urban agglomeration based on DMSP/OLS night-time light data[J]. Remote Sensing for Land & Resources, 2019,31(4):218-226. ]
[47]	唐敏. 基于对数变换的NPP-VIIRS夜间灯光遥感影像在城市建成区提取中的应用[D]. 上海:华东师范大学, 2017.
	[ Tang M. Urban built-up area extraction from logarithm transformed NPP/VIIRS nighttime light composite data[D]. Shanghai: East China Normal University, 2017. ]
[48]	徐梦洁, 陈黎, 刘焕金, 等. 基于DMSP/OLS夜间灯光数据的长江三角洲地区城市化格局与过程研究[J]. 国土资源遥感, 2011,23(3):106-112.
	[ Xu M J, Chen L, Liu H J, et al. Pattern and process of urbanization in the Yangtze delta based on DMSP/OLS data[J]. Remote Sensing for Land & Resources, 2011,23(3):106-112. ]
[49]	陈龙胤. 基于DMSP/OLS夜间灯光影像的中国东部沿海地区城市扩张监测与分析[D]. 长春:东北师范大学, 2014.
	[ Chen L Y. Monitoring and analysis of urban expansion in eastern coastal area of china based on DMSP/OLS night lights image[D]. Changchun: Northeast Normal University, 2014. ]
[50]	王伟. 中国三大城市群经济空间重心轨迹特征比较[J]. 城市规划学刊, 2009,20(3):24-32.
	[ Wang W. A comparative study of shift route of eco-spatial gravity center of the three major urban agglomerations in China[J]. Urban Planning Forum, 2009,20(3):24-32. ]
[51]	白雪. 长三角城市群经济重心动态演变及区域发展差异分析[J]. 华东经济管理, 2015,29(3):46-50.
	[ Bai X. An analysis on dynamic evolution of economic gravity center and difference of regional development in the Yangtze River Delta urban agglomeration[J]. East China Economic Management, 2015,29(3):46-50. ]
[52]	董鹤松, 李仁杰, 李建明, 等. 基于DMSP-OLS与NPP-VIIRS整合数据的中国三大城市群城市空间扩展时空格局[J]. 地球信息科学学报, 2020,22(5):1161-1174. doi: 10.12082/dqxxkx.2020.190711
	[ Dong H S, Li R J, Li J M, et al. Study on urban spatiotemporal expansion pattern of three first-class urban agglomerations in China derived from integrated DMSP-OLS and NPP-VIIRS nighttime light data[J]. Journal of Geo-information Science, 2020,22(5):1161-1174. ]
[53]	孙贵艳, 王传胜, 肖磊, 等. 长江三角洲城市群城镇体系演化时空特征[J]. 长江流域资源与环境, 2011,20(6):641-649.
	[ Sun G Y, Wang C S, Xiao L, et al. Temporal-spatial characteristics of evolution of the urban system in the Yangtze River Delta[J]. Resources and Environment in the Yangtza Basin, 2011,20(6):641-649. ]
[54]	毕秀晶. 长三角城市群空间演化研究[D]. 上海:华东师范大学, 2014.
	[ Bi X J. Pattern, dynamics and mechanism of spatial evolution in Yangtze River Delta[D]. Shanghai: East China Normal University, 2017. ]
[55]	晁静, 赵新正, 李同昇, 等. 基于多源夜间灯光数据的长江经济带三大城市群规模结构动态比较[J]. 地理与地理信息科学, 2020,36(1):44-51,I0003.
	[ Chao J, Zhao X Z, Li T S, et al. Comparative analysis on the dynamic characteristics of scale structure among three urban agglomerations in the Yangtze River economic belt based on multi-source nighttime light data[J]. Geography and Geo-Information Science, 2020,36(1):44-51, I0003. ]
[56]	人大网. 中华人民共和国城市规划法[EB/OL]. http://www.npc.gov.cn/wxzl/gongbao/1989-12/26/content_1481128.htm.
	[ NPC. Urban Planning Law of the People's Republic of China[EB/OL]. http://www.npc.gov.cn/wxzl/gongbao/1989-12/26/content_1481128.htm. ]

整合DMSP/OLS和NPP/VIIRS夜间灯光遥感数据的长江三角洲城市格局时空演化研究

Study on the Spatio-Temporal Evolution of the Yangtze River Delta Urban Agglomeration by Integrating Dmsp/Ols and Npp/Viirs Nighttime Light Data

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