Temporal variations of artificial nighttime lights and their implications for urbanization in the conterminous United States, 2013-2017

Authors: Yanhua Xie*, SAGE, University of Wisconsin-Madison
Topics: Remote Sensing, Urban Geography, Land Use and Land Cover Change
Keywords: Nighttime lights, time series, seasonality, annual changes, urbanization, NPP/VIIRS
Session Type: Paper
Day: 4/4/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Taylor, Marriott, Mezzanine Level
Presentation File: No File Uploaded


Artificial nighttime lights (NTL) offer a unique opportunity to understand urban environments. Although previous studies have widely used NTL images to map urban extent at multiple scales, it remains a challenging task to address how NTL response exactly to urbanization and thus to map urbanization from NTL. In this study, using monthly Suomi National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) NTL images between 2013 and 2017, we developed a method to decompose time-series NTL signal into the annual and seasonal components. Further, we proposed an NTL-based indicator for the detection of impervious surfaces change (ISC) by integrating annual increment and seasonal variation of NTL brightness. The indicator was then used to identify ISC by using a thresholding method. The application of the methodology in the conterminous United States (CONUS) revealed a more rapid urbanization in the southern CONUS than the northern states and a northeastern-southwestern gradient of NTL seasonality. It was also found that NTL of November and December provided the most accurate characterization of urban extent for most areas in the CONUS. The detection of ISC in four representative regions (i.e. Dallas-Fort Worth-Arlington, greater Washington D.C., Denver-Aurora, and Atlanta) resulted in a moderate to high accuracy with the overall accuracy of ~80% and the Kappa value ranging from 0.56 to 0.73. The proposed method was found effective for mapping urban expansion at large geographical scales (e.g., continental and global), time-series NTL images of a longer period is more desirable, especially for the detection of newly built residential areas.

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