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Author Li, S.; Cheng, L.; Liu, X.; Mao, J.; Wu, J.; Li, M. url  doi
openurl 
  Title City type-oriented modeling electric power consumption in China using NPP-VIIRS nighttime stable light data Type Journal Article
  Year 2019 Publication Energy Abbreviated Journal Energy  
  Volume (down) 189 Issue Pages 116040  
  Keywords Energy; Remote Sensing; China; electric power consumption; Night lights; Nighttime light; VIIRS-DNB  
  Abstract Accelerating urbanization has created tremendous pressure on the global environment and energy supply, making accurate estimates of energy use of great importance. Most current models for estimating electric power consumption (EPC) from nighttime light (NTL) imagery are oversimplified, ignoring influential social and economic factors. Here we propose first classifying cities by economic focus and then separately estimating each category’s EPC using NTL data. We tested this approach using statistical employment data for 198 Chinese cities, 2015 NTL data from the Visible Infrared Imaging Radiometer Suite (VIIRS), and annual electricity consumption statistics. We used cluster analysis of employment by sector to divide the cities into three types (industrial, service, and technology and education), then established a linear regression model for each city's NTL and EPC. Compared with the estimation results before city classification (R2: 0.785), the R2 of the separately modeled service cities and technology and education cities increased to 0.866 and 0.830, respectively. However, the results for industrial cities were less consistent due to their more complex energy consumption structure. In general, using classification before modeling helps reflect factors affecting the relationship between EPC and NTL, making the estimation process more reasonable and improving the accuracy of the results.  
  Address School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China  
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  Series Volume Series Issue Edition  
  ISSN 0360-5442 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2672  
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Author Lu, L.; Weng, Q.; Xie, Y.; Guo, H.; Li, Q. url  doi
openurl 
  Title An assessment of global electric power consumption using the Defense Meteorological Satellite Program-Operational Linescan System nighttime light imagery Type Journal Article
  Year 2019 Publication Energy Abbreviated Journal Energy  
  Volume (down) 189 Issue Pages 116351  
  Keywords Remote Sensing; Energy; electric power consumption; Night lights  
  Abstract Industrialization and urbanization have led to a remarkable increase of electric power consumption (EPC) during the past decades. To assess the changing patterns of EPC at the global scale, this study utilized nighttime lights in conjunction with population and built-up datasets to map EPC at 1 km resolution. Firstly, the inter-calibrated nighttime light data were enhanced using the V4.0 Gridded Population Density data and the Global Human Settlement Layer. Secondly, linear models were calibrated to relate EPC to the enhanced nighttime light data; these models were then employed to estimate per-pixel EPC in 2000 and 2013. Finally, the spatiotemporal patterns of EPC between the periods were analyzed at the country, continental, and global scales. The evaluation of the EPC estimation shows a reasonable accuracy at the provincial scale with R2 of 0.8429. Over 30% of the human settlements in Asia, Europe, and North America showed apparent EPC growth. At the national scale, moderate and high EPC growth was observed in 45% of the built-up areas in East Asia. The spatial clustering patterns revealed that EPC decreased in Russia and the Western Europe. This study provides fresh insight into the spatial pattern and variations of global electric power consumption.  
  Address Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, PR China; qweng(at)indstate.edu  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0360-5442 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2701  
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Author Hasler, B.P. url  doi
openurl 
  Title Commentary on Bedroom Light Exposure at Night and the Incidence of Depressive Symptoms: A Longitudinal Study of the HEIJOKYO Cohort (Obayashi et al) Type Journal Article
  Year 2018 Publication American Journal of Epidemiology Abbreviated Journal  
  Volume (down) 187 Issue 3 Pages 435-438  
  Keywords Commentary; Human Health  
  Abstract In modern society, we are increasingly disconnected from natural light/dark cycles and beset by round-the-clock exposure to artificial light. Light has powerful effects on physical and mental health, in part via the circadian system, and thus the timing of light exposure dictates whether it is helpful or harmful. In their compelling paper, Obayashi and colleagues offer evidence that light at night can prospectively predict an elevated incidence of depressive symptoms in older adults. Strengths of the study include the longitudinal design and direct, objective assessment of light levels, as well as accounting for multiple plausible confounders during analyses. Follow-up studies should address the study's limitations, including reliance on a global self-report of sleep quality and a two-night assessment of light exposure that may not reliably represent typical light exposure. In addition, experimental studies including physiological circadian measures will be necessary to determine if the light effects on depression are mediated through the circadian system or are so-called “direct” effects of light. In any case, these exciting findings could inform novel new approaches to preventing depressive disorders in older adults.  
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  ISSN 0002-9262 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number LoNNe @ kyba @ Serial 1716  
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Author Obayashi, K.; Saeki, K.; Kurumatani, N. url  doi
openurl 
  Title Obayashi et al. Respond to “Light at Night Predicts Depression—What Next?” Type Journal Article
  Year 2018 Publication American Journal of Epidemiology Abbreviated Journal  
  Volume (down) 187 Issue 3 Pages 439-440  
  Keywords Commentary; Human Health  
  Abstract Our research includes some strengths and limitations. The most important strength is objective measurement of light at night (LAN) intensity using a bedside light meter. Most previous studies evaluating the association between LAN and health outcomes have assessed indoor LAN levels using a self-reported questionnaire or outdoor LAN levels using satellite data; however, self-reported indoor LAN levels has not yet been validated with objective measurement and outdoor LAN levels are surrogates for an individual LAN exposure. The second strength of our study includes its longitudinal design using multivariable methods to adjust for confounders, which indicated LAN exposure may be a cause of the incidence of depressive symptoms. Indeed, the depressive score evaluated by questionnaires may be above or below the cut-off value over the short term; therefore, a long-term study considering such unstable outcomes should be conducted. In the current study, LAN exposure was measured for only two nights; thus, an amplitude of LAN intensity has been focused. However, multiple measurements over time in the future study would allow an analysis of fluctuations in LAN exposure, which might be important for circadian physiology.  
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  ISSN 0002-9262 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number LoNNe @ kyba @ Serial 1717  
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Author Shi, K.; Chen, Y.; Yu, B.; Xu, T.; Yang, C.; Li, L.; Huang, C.; Chen, Z.; Liu, R.; Wu, J. url  doi
openurl 
  Title Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data Type Journal Article
  Year 2016 Publication Applied Energy Abbreviated Journal Applied Energy  
  Volume (down) 184 Issue Pages 450-463  
  Keywords Remote Sensing  
  Abstract 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.  
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  Series Volume Series Issue Edition  
  ISSN 0306-2619 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2486  
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