Detecting urban-scale dynamics of electricity consumption at Chinese cities using time-series DMSP-OLS (Defense Meteorological Satellite Program-Operational Linescan System) nighttime light imageries
Yanhua Xie and
Qihao Weng
Energy, 2016, vol. 100, issue C, 177-189
Abstract:
A better understanding of the spatiotemporal pattern of energy consumption at the urban scale is significant in the interactions between economic activities and environment. This study assessed the spatiotemporal dynamics of EC (electricity consumption) in UC (urban cores) and SR (suburban regions) in China from 2000 to 2012 by using remotely sensed NTL (nighttime light) imagery. Firstly, UC and SR were extracted using a threshold technique. Next, provincial level model was calibrated yearly by using Enhanced Vegetation Index and population-adjusted NTL data as independent variables. These models were then applied for pixel-based estimation to obtain time-series EC data sets. Finally, the spatiotemporal pattern of EC in both UC and SR were explored. The results indicated that the proportion of EC in urban areas rose from 50.6% to 71.32%, with a growing trend of spatial autocorrelation. Cities with high urban EC were either located in the coastal region or belonged to provincial capitals. These cities experienced a moderate to a rapid growth of EC in both UC and SR, while a slow growth was detected for the majority of western and northeastern cities. The findings suggested that EC in SR was more crucial for sustainable energy development in China.
Keywords: Energy consumption; Urban and suburban; Nighttime light imagery; Spatiotemporal pattern; Chinese cities (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544216000888
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:100:y:2016:i:c:p:177-189
DOI: 10.1016/j.energy.2016.01.058
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().