Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data

被引:153
|
作者
Shi, Kaifang [1 ,2 ,3 ]
Chen, Yun [3 ]
Yu, Bailang [1 ,2 ]
Xu, Tingbao [4 ]
Yang, Chengshu [1 ,2 ]
Li, Linyi [5 ]
Huang, Chang [6 ]
Chen, Zuoqi [1 ,2 ]
Liu, Rui [1 ,2 ]
Wu, Jianping [1 ,2 ]
机构
[1] East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China
[2] East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
[3] CSIRO Land & Water, Canberra, ACT 2601, Australia
[4] Australian Natl Univ, Fenner Sch Environm & Soc, Linnaeus Way, Canberra, ACT 2601, Australia
[5] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
[6] Northwest Univ, Coll Urban & Environm Sci, Xian 710127, Peoples R China
基金
上海市自然科学基金; 中国国家自然科学基金;
关键词
Electric power consumption; Spatiotemporal dynamics; Remote sensing; DMSP-OLS; Nighttime light; CARBON-DIOXIDE EMISSIONS; ENERGY-CONSUMPTION; CHINA; IMAGERY; POPULATION; SCALES; GROWTH;
D O I
10.1016/j.apenergy.2016.10.032
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The rapid development of global industrialization and urbanization has resulted in a great deal of electric power consumption (EPC), which is closely related to economic growth, carbon emissions, and the long-term stability of global climate. This study attempts to detect spatiotemporal dynamics of global EPC using the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime stable light (NSL) data. The global NSL data from 1992 to 2013 were intercalibrated via a modified invariant region (MIR) method. The global EPC at 1 km resolution was then modeled using the intercalibrated NSL data to assess spatiotemporal dynamics of EPC from a global scale down to continental and national scales. The results showed that the MIR method not only reduced the saturated lighted pixels, but also improved the continuity and comparability of the NSL data. An accuracy assessment was undertaken and confined that the intercalibrated NSL data were relatively suitable and accurate for estimating EPC in the world. Spatiotemporal variations of EPC were mainly identified in Europe, North America, and Asia. Special attention should be paid to China where the high grade and high-growth type of EPC covered 0.409% and 1.041% of the total country area during the study period, respectively. The results of this study greatly enhance the understanding of spatiotemporal dynamics of global EPC at the multiple scales. They will provide a scientific evidence base for tracking spatiotemporal dynamics of global EPC. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:450 / 463
页数:14
相关论文
共 50 条
  • [31] Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data
    Zhang, Qingling
    Seto, Karen C.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2011, 115 (09) : 2320 - 2329
  • [32] Evaluation of NPP-VIIRS Nighttime Light Data for Mapping Global Fossil Fuel Combustion CO2 Emissions: A Comparison with DMSP-OLS Nighttime Light Data
    Ou, Jinpei
    Liu, Xiaoping
    Li, Xia
    Li, Meifang
    Li, Wenkai
    [J]. PLOS ONE, 2015, 10 (09):
  • [33] Monitoring Regional Urban Dynamics Using DMSP/OLS Nighttime Light Data in Zhejiang Province
    Xu, Pengfei
    Jin, Pingbin
    Cheng, Qian
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2020, 2020
  • [34] Spatialization of electricity consumption of China using saturation-corrected DMSP-OLS data
    Cao, Xin
    Wang, Jianmin
    Chen, Jin
    Shi, Feng
    [J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2014, 28 : 193 - 200
  • [35] Use of the DMSP-OLS Nighttime Light Data to Study Urbanization and Its Influence on NDVI in Taihu Basin, China
    Deng, Pengxin
    Hu, Qingfang
    Wang, Yintang
    Lv, Sunyun
    Zhang, Dongdong
    [J]. JOURNAL OF URBAN PLANNING AND DEVELOPMENT, 2016, 142 (04)
  • [36] A New Framework for Reconstructing Time Series DMSP-OLS Nighttime Light Data Using the Improved Stepwise Calibration (ISC) Method
    Wang, Mingyue
    Feng, Chunhui
    Hu, Bifeng
    Wang, Nan
    Xu, Jintao
    Ma, Ziqiang
    Peng, Jie
    Shi, Zhou
    [J]. REMOTE SENSING, 2022, 14 (17)
  • [37] CARBON DIOXIDE EMISSIONS STIMULATION AND ANALYSIS BASED ON CITY INDUSTRIAL STRUCTURE AND DMSP-OLS NIGHTTIME LIGHT DATA
    Li, Shuyi
    Cheng, Liang
    [J]. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 1853 - 1856
  • [38] MAPPING DEVELOPMENT PATTERN IN CHINA USING DMSP/OLS NIGHTTIME LIGHT DATA
    Hu, Yi'na
    Qi, Kun
    Hu, Tao
    [J]. IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2018, : 850 - 853
  • [39] Detecting the Effects of Wars in the Caucasus Regions of Russia and Georgia Using Radiometrically Normalized DMSP-OLS Nighttime Lights Imagery
    Witmer, Frank D. W.
    O'Loughlin, John
    [J]. GISCIENCE & REMOTE SENSING, 2011, 48 (04) : 478 - 500
  • [40] Examining Urbanization Dynamics in Turkey Using DMSP-OLS and Socio-Economic Data
    Yucer, Emre
    Erener, Arzu
    [J]. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2018, 46 (07) : 1159 - 1169