DMSP/OLS和VIIRS夜光影像辐射亮度差异及其在电力消耗估算中的比较

doi:10.3969/j.issn.0255-8297.2019.01.010

Abstract

Abstract:

As the acquisition time of nighttime light image of defense meteorological satellite program/operational linescan system (DMSP/OLS) and visible infrared imaging radiometer suite (VⅡRS) is different, nighttime lights are different at different times in the same area. In view of the difference, the ratio of two kinds of NTL mean values is taken as the measurement index to create light difference index (LDI). In this paper, we explore the consistency and difference of the NTL at different time in the same area, and analyze the causes of the differences. Meanwhile, the capabilities of DMSP/OLS and VⅡRS are compared for predicting electricity power consumption (EPC) at provincial level in China. The results show that NTL behaves some time-consistency and time-difference. There is a good correlation between two kinds of NTL images, and the higher nighttime light mean value of DMSP/OLS, the smaller the light difference. The difference is related to the regional economic development. Undeveloped areas are more likely to have great differences. In the forecast of electricity power consumption (EPC), VⅡRS is more relevant to EPC and superior in estimating EPC than DMSP/OLS.

Key words: light difference index, time difference, electricity power consumption (EPC), nighttime light image

CLC Number:

P751.1

QIU Ya-qian, XUE Xiang-yu, HAN Wen-jun, CHEN Xiao-ling, LI Xi. Comparison of Radiation Intensity and Estimation of Electric Power Consumption between DMSP/OLS and VIIRS Nighttime Light Images[J]. Journal of Applied Sciences, 2019, 37(1): 99-111.

References

[1] Croft T. Nighttime images of the earth from space[J]. Scientific American, 1978, 239(1):86-98.
[2] 李德仁,李熙. 论夜光遥感数据挖掘[J]. 测绘学报,2015, 44(6):591-601. Li D R, Li X. An overview on data mining of nighttime light remote sensing[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(6):591-601. (in Chinese)
[3] Elvidge C D, Baugh K E, Kihn E A, Kroehl H W, Davis E R, Davis C W. Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption[J]. International Journal of Remote Sensing, 1997, 18(6):1373-1379.
[4] Elvidge C, Baugh K, Hobson V, Kihn E, Kroehl H, Davis E, Cocero D. Satellite inventory of human settlements using nocturnal radiation emissions:a contribution for the global toolchest[J]. Global Change Biology, 2010, 3(5):387-395.
[5] Henderson J V, Storeygard A, Weil D N. A bright idea for measuring economic growth[J]. American Economic Review, 2011, 101(3):194-199.
[6] 杨续超,康丽莉,张斌,冀春晓. 基于多源遥感信息的电力消费量估算与影响因素分析——以浙江省为例[J]. 地理科学,2013, 33(6):718-723. Yang X C, Kang L L, Zhang B, Ji C X. Electricity consumption estimation using multisensor remote sensing data:a case study of Zhejiang Province[J]. Scientia Geographica Sinica, 2013, 33(6):718-723. (in Chinese)
[7] Zhang Q, Seto K C. Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data[J]. Remote Sensing of Environment, 2011, 115(9):2320-2329.
[8] Imhoff M L, Lawrence W T, Stutzer D C, Elvidge C D. 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.
[9] Imhoff M L, Lawrence W T, Stutzer D C, Elvidge C D. Using nighttime DMSP/OLS images of city lights to estimate the impact of urban land use on soil resources in the United States[J]. Remote Sensing of Environment, 1997, 59(1):105-117.
[10] 范子英,彭飞,刘冲. 政治关联与经济增长——基于卫星灯光数据的研究[J]. 经济研究,2016(1):114-126. Fan Z Y, Peng F, Liu C. Political connections and economic growth:evidence from the DMSP/OLS satellite data[J]. Economic Research Journal, 2016(1):114-126. (in Chinese)
[11] 李德仁,余涵若,李熙. 基于夜光遥感影像的"一带一路"沿线国家城市发展时空格局分析[J]. 武汉大学学报(信息科学版),2017, 42(6):711-720. Li D R, Yu H R, Li X. The spatial-temporal pattern analysis of city development in countries along the belt and road initiative based on nighttime light data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(6):711-720. (in Chinese)
[12] Li X, Li D. Can night-time light images play a role in evaluating the Syrian crisis[J]. International Journal of Remote Sensing, 2014, 35(18):6648-6661.
[13] Elvidge C D, Ziskin D, Baugh K E, Tuttle B T, Ghosh T, Pack D W, Erwin E H, Zhizhin M. A fifteen year record of global natural gas flaring derived from satellite data[J]. Energies, 2009, 2(3):595-622.
[14] Chen X, Nordhaus W. A test of the new VⅡRS lights data set&58; population and economic output in Africa[J]. Remote Sensing, 2015, 7(4):4937-4947.
[15] Shi K, Huang C, Yu B, Yin B, Huang Y, Wu J. Evaluation of NPP-VⅡRS night-time light composite data for extracting built-up urban areas[J]. Remote Sensing Letters, 2014, 5(4):358-366.
[16] Li X, Xu H, Chen X, Li C. Potential of NPP-VⅡRS nighttime light imagery for modeling the regional economy of China[J]. Remote Sensing, 2013, 5(6):3057-3081.
[17] Jing X, Shao X, Cao C, Fu X, Yan L. Comparison between the Suomi-NPP day-night band and DMSP-OLS for correlating socio-economic variables at the provincial level in China[J]. Remote Sensing, 2015, 8(1):17.
[18] Shi K, Yu B, Huang Y, Hu Y, Yin B, Chen Z, Chen L, Wu J. Evaluating the ability of NPP-VⅡRS nighttime light data to estimate the gross domestic product and the electric power consumption of China at multiple scales:a comparison with DMSP-OLS data[J]. Remote Sensing, 2014, 6(2):1705-1724.
[19] Liu Z, He C, Zhang Q, Huang Q, Yang Y. Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008[J]. Landscape & Urban Planning, 2012, 106(1):62-72.
[20] Li X, Li D, Xu H, Wu C. 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(1):1-18.

Comparison of Radiation Intensity and Estimation of Electric Power Consumption between DMSP/OLS and VIIRS Nighttime Light Images

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