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Nighttime light (NTL) data from The Defense Meteorological Satellite Program/Operational Linescan System has a number of unique features that meet the needs of wide‐scale surveys of urban environment with high temporal coverage. These features include long‐term data archive from 1992 to 2013 and show strong correlation to human settlements and activities such as population distribution, economic activities, and energy consumption (EC). This chapter proposes a new method for large‐scale urbanization analysis by spatiotemporally adjusting NTL data and associating the thresholds of different images. This method aims at increasing the consistency over the time and the details of NTL data. The chapter analyzes the spatiotemporal pattern of electricity consumption (EC) for United States and China from 2000 to 2012 by using the NTL imagery. This analysis offers a spatially explicit method to characterize the spatial and temporal pattern of EC and provide the potential of creating EC data sets at pixel, local, regional, and global scale.
Nighttime light (NTL) data from The Defense Meteorological Satellite Program/Operational Linescan System has a number of unique features that meet the needs of wide‐scale surveys of urban environment with high temporal coverage. These features include long‐term data archive from 1992 to 2013 and show strong correlation to human settlements and activities such as population distribution, economic activities, and energy consumption (EC). This chapter proposes a new method for large‐scale urbanization analysis by spatiotemporally adjusting NTL data and associating the thresholds of different images. This method aims at increasing the consistency over the time and the details of NTL data. The chapter analyzes the spatiotemporal pattern of electricity consumption (EC) for United States and China from 2000 to 2012 by using the NTL imagery. This analysis offers a spatially explicit method to characterize the spatial and temporal pattern of EC and provide the potential of creating EC data sets at pixel, local, regional, and global scale.
Cities at Night
Weng, Qihao (author)
2019-11-01
26 pages
Article/Chapter (Book)
Electronic Resource
English
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