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Title: Correcting incompatible DN values and geometric errors in nighttime lights time series images

Journal Article · · IEEE Transactions on Geoscience and Remote Sensing
 [1];  [2];  [3]
  1. Texas Tech Univ., Lubbock, TX (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Mayan Esteem Project, Farmington, CT (United States)

The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime lights imagery has proven to be a powerful remote sensing tool to monitor urbanization and assess socioeconomic activities at large scales. However, the existence of incompatible digital number (DN) values and geometric errors severely limit application of nighttime light image data on multi-year quantitative research. In this study we extend and improve previous studies on inter-calibrating nighttime lights image data to obtain more compatible and reliable nighttime lights time series (NLT) image data for China and the United States (US) through four steps: inter-calibration, geometric correction, steady increase adjustment, and population data correction. We then use gross domestic product (GDP) data to test the processed NLT image data indirectly and find that sum light (summed DN value of pixels in a nighttime light image) maintains apparent increase trends with relatively large GDP growth rates but does not increase or decrease with relatively small GDP growth rates. As nighttime light is a sensitive indicator for economic activity, the temporally consistent trends between sum light and GDP growth rate imply that brightness of nighttime lights on the ground is correctly represented by the processed NLT image data. Finally, through analyzing the corrected NLT image data from 1992 to 2008, we find that China experienced apparent nighttime lights development in 1992-1997 and 2001-2008 respectively and the US suffered from nighttime lights decay in large areas after 2001.

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
1166818
Report Number(s):
PNNL-SA-105036; 400409900
Journal Information:
IEEE Transactions on Geoscience and Remote Sensing, Vol. 53, Issue 4; ISSN 0196-2892
Publisher:
IEEE
Country of Publication:
United States
Language:
English

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