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Author (up) Bennett, M.M.; Smith, L.C. url  doi
openurl 
  Title Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics Type Journal Article
  Year 2017 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment  
  Volume 192 Issue Pages 176-197  
  Keywords Remote Sensing  
  Abstract Since the late 1990s, remotely sensed night-time lights (NTL) satellite imagery has been shown to correlate with socioeconomic parameters including urbanization, economic activity, and population. More recent research demonstrates that multitemporal NTL data can serve as a reliable proxy for change over time in these variables whether they are increasing or decreasing. Time series analysis of NTL data is especially valuable for detecting, estimating, and monitoring socioeconomic dynamics in countries and subnational regions where reliable official statistics may be lacking. Until 2012, multitemporal NTL imagery came primarily from the Defense Meteorological Satellite Program – Operational Linescan System (DMSP-OLS), for which digital imagery is available from 1992 to 2013. In October 2011, the launch of NASA/NOAA's Suomi National Polar-orbiting Partnership satellite, whose Visible Infrared Imaging Radiometer Suite (VIIRS) sensor has a Day/Night Band (DNB) specifically designed for capturing radiance from the Earth at night, marked the start of a new era in NTL data collection and applications. In light of these advances, this paper reviews progress in using multitemporal DMSP-OLS and VIIRS imagery to analyze urbanization, economic, and population dynamics across a range of geographic scales. An overview of data corrections and processing for comparison of multitemporal NTL imagery is provided, followed by a meta-analysis and integrative synthesis of these studies. Figures are included that visualize the capabilities of DMSP-OLS and VIIRS to capture socioeconomic change in the post-Soviet Russian Far East and war-torn Syria, respectively. Finally, future directions for NTL research are suggested, particularly in the areas of determining the fundamental causes of observed light and in leveraging VIIRS' superior sensitivity and spatial and radiometric resolution.  
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  Series Volume Series Issue Edition  
  ISSN 0034-4257 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2024  
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Author (up) Cao, X.; Chen, J.; Imura, H.; Higashi, O. url  doi
openurl 
  Title A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data Type Journal Article
  Year 2009 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment  
  Volume 113 Issue 10 Pages 2205-2209  
  Keywords Remote Sensing  
  Abstract Mapping urban areas at regional and global scales has become an urgent task because of the increasing pressures from rapid urbanization and associated environmental problems. Satellite imaging of stable anthropogenic lights from DMSP-OLS provides an accurate, economical, and straightforward way to map the global distribution of urban areas. To address problems in the thresholding methods that use empirical strategies or manual trial-and-error procedures, we proposed a support vector machine (SVM)-based region-growing algorithm to semi-automatically extract urban areas from DMSP-OLS and SPOT NDVI data. Several simple criteria were used to select SVM training sets of urban and non-urban pixels, and an iterative classification and training procedure was adopted to identify the urban pixels through region growing. The new method was validated using the extents of 25 Chinese cities, as classified by Landsat ETM+ images, and then compared with two common thresholding methods. The results showed that the SVM-based algorithm could not only achieve comparable results to the local-optimized threshold method, but also avoid its tedious trial-and-error procedure, suggesting that the new method is an easy and simple alternative for extracting urban extent from DMSP-OLS and SPOT NDVI data.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0034-4257 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2041  
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Author (up) Cao, X.; Hu, Y.; Zhu, X.; Shi, F.; Zhuo, L.; Chen, J. url  doi
openurl 
  Title A simple self-adjusting model for correcting the blooming effects in DMSP-OLS nighttime light images Type Journal Article
  Year 2019 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment  
  Volume 224 Issue Pages 401-411  
  Keywords Remote Sensing  
  Abstract Night-time light (NTL) data from the Defense Meteorological Satellite Program (DMSP) Operation Linescan System (OLS) provide important observations of human activities; however, DMSP-OLS NTL data suffer from problems such as saturation and blooming. This research developed a self-adjusting model (SEAM) to correct blooming effects in DMSP-OLS NTL data based on a spatial response function and without using any ancillary data. By assuming that the pixels adjacent to the background contain no lights (i.e., pseudo light pixels, PLPs), the blooming effect intensity, a parameter in the SEAM model, can be estimated by pixel-based regression using PLPs and their neighboring light sources. SEAM was applied to all of China, and its performance was assessed for twelve cities with different population sizes. The results show that SEAM can largely reduce the blooming effect in the original DMSP-OLS dataset and enhance its quality. The images after blooming effect correction have higher spatial similarity with Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) images and higher spatial variability than the original DMSP-OLS data. We also found that the average effective blooming distance is approximately 3.5 km in China, which may be amplified if the city is surrounded by water surfaces, and that the blooming effect intensity is positively correlated to atmospheric quality. The effectiveness of the proposed model will improve the capacity of DMSP-OLS images for mapping the urban extent and modeling socioeconomic parameters.  
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  ISSN 0034-4257 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2239  
Permanent link to this record
 

 
Author (up) Elvidge, C. D.; Baugh, K. E.; Dietz, J. B.; Bland, T.; Sutton, P. C.; Kroehl, H. W. url  doi
openurl 
  Title Radiance calibration of DMSP-OLS low-light imaging data of human settlements. Type Journal Article
  Year 1999 Publication Remote Sensing of Environment Abbreviated Journal  
  Volume 68 Issue 1 Pages 77-88  
  Keywords Remote Sensing; DMSP; DMSP-OLS; satellite; night lights; light pollution  
  Abstract Nocturnal lighting is a primary method for enabling human activity. Outdoor lighting is used extensively worldwide in residential, commercial, industrial, public facilities, and roadways. A radiance calibrated nighttime lights image of the United States has been assembled from Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). The satellite observation of the location and intensity of nocturnal lighting provide a unique view of humanities presence and can be used as a spatial indicator for other variables that are more difficult to observe at a global scale. Examples include the modeling of population density and energy related greenhouse gas emissions.  
  Address NOAA National Geophysical Data Center, Boulder, CO USA  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number LoNNe @ kagoburian @ Serial 930  
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Author (up) Gong, P.; Li, X.; Wang, J.; Bai, Y.; Chen, B.; Hu, T.; Liu, X.; Xu, B.; Yang, J.; Zhang, W.; Zhou, Y. url  doi
openurl 
  Title Annual maps of global artificial impervious area (GAIA) between 1985 and 2018 Type Journal Article
  Year 2020 Publication Remote Sensing of Environment Abbreviated Journal Remote Sensing of Environment  
  Volume 236 Issue Pages in press  
  Keywords Remote Sensing  
  Abstract Artificial impervious areas are predominant indicators of human settlements. Timely, accurate, and frequent information on artificial impervious areas is critical to understanding the process of urbanization and land use/cover change, as well as of their impacts on the environment and biodiversity. Despite their importance, there still lack annual maps of high-resolution Global Artificial Impervious Areas (GAIA) with longer than 30-year records, due to the high demand of high performance computation and the lack of effective mapping algorithms. In this paper, we mapped annual GAIA from 1985 to 2018 using the full archive of 30-m resolution Landsat images on the Google Earth Engine platform. With ancillary datasets, including the nighttime light data and the Sentinel-1 Synthetic Aperture Radar data, we improved the performance of our previously developed algorithm in arid areas. We evaluated the GAIA data for 1985, 1990, 1995, 2000, 2005, 2010, and 2015, and the mean overall accuracy is higher than 90%. A cross-product comparison indicates the GAIA data are the only dataset spanning over 30 years. The temporal trend in GAIA agrees well with other datasets at the local, regional, and global scales. Our results indicate that the GAIA reached 797,076 km2 in 2018, which is 1.5 times more than that in 1990. China and the United States (US) rank among the top two in artificial impervious area, accounting for approximately 50% of the world's total in 2018. The artificial impervious area of China surpassed that of the US in 2015. By 2018, the remaining eight among the top ten countries are India, Russia, Brazil, France, Italy, Germany, Japan, and Canada. The GAIA dataset can be freely downloaded from http://data.ess.tsinghua.edu.cn.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0034-4257 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2756  
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