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Author Omar, N. S., & Ismal, A. doi  openurl
  Title Night Lights and Economic Performance in Egypt Type Journal Article
  Year 2019 Publication (up) Advances in Economics and Business Abbreviated Journal  
  Volume 7 Issue 2 Pages 69-81  
  Keywords Economics; Remote Sensing  
  Abstract This paper, to the best of my knowledge, is the first to estimate the association between Nighttime Lights (NTL) and real Gross Domestic Product (GDP) at the national level, using sub-national GDP data for the 27 Egyptian governorates over FY08-FY13. The study finds that NTL has a positive and statistically significant

correlation with GDP at the sub-national and national levels. Hence, NTL can measure and predict GDP in Egypt, at the national and sub-national levels. These findings affirm most previous research that NTL could be a good proxy for GDP when official data are unavailable or time infrequent in developing countries.
 
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  Notes Approved no  
  Call Number IDA @ intern @ Serial 2301  
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Author Nelson, R.J.; DeVries, A.C. url  doi
openurl 
  Title Medical Hypothesis: Light at Night Is a Factor Worth Considering in Critical Care Units Type Journal Article
  Year 2017 Publication (up) Advances in Integrative Medicine Abbreviated Journal Advances in Integrative Medicine  
  Volume 4 Issue 3 Pages 115-120  
  Keywords Human Health  
  Abstract Exposure to light at night is not an innocuous consequence of modernization. There are compelling data linking long-term exposure to occupational and environmental light at night with serious health conditions, including heart disease, obesity, diabetes, and cancer. However, far less is known about the physiological and behavioral effects of acute exposure to light at night. Among healthy volunteers, acute night-time light exposure increases systolic blood pressure and inflammatory markers in the blood, and impairs glucose regulation. Whether critically ill patients in a hospital setting experience the same physiological shifts in response to evening light exposure is not known. This paper reviews the available data on light at night effects on health and wellbeing, and argues that the data are sufficiently compelling to warrant studies of how lighting in intensive care units may be influencing patient recovery.  
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  ISSN 2212-9588 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number LoNNe @ kyba @ Serial 1794  
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Author Liang, H.; Guo, Z.; Wu, J.; Chen, Z. url  doi
openurl 
  Title GDP spatialization in Ningbo City based on NPP/VIIRS night-time light and auxiliary data using random forest regression Type Journal Article
  Year 2019 Publication (up) Advances in Space Research Abbreviated Journal Advances in Space Research  
  Volume in press Issue Pages S0273117719307136  
  Keywords Remote Sensing; GDP; gross domestic product; spatialization; VIIRS-DNB; Nighttime light; numerical methods  
  Abstract Accurate spatial distribution information on gross domestic product (GDP) is of great importance for the analysis of economic development, industrial distribution and urbanization processes. Traditional administrative unit-based GDP statistics cannot depict the detailed spatial differences in GDP within each administrative unit. This paper presents a study of GDP spatialization in Ningbo City, China based on National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL) data and town-level GDP statistical data. The Landsat image, land cover, road network and topographic data were also employed as auxiliary data to derive independent variables for GDP modelling. Multivariate linear regression (MLR) and random forest (RF) regression were used to estimate GDP at the town scale and were assessed by cross-validation. The results show that the RF model achieved significantly higher accuracy, with a mean absolute error (MAE) of 109.46 million China Yuan (CNY)·km-2 and a determinate coefficient (R2=0.77) than the MLR model (MAE=161.8 million CNY·km-2, R2=0.59). Meanwhile, by comparing with the estimated GDP data at the county level, the town-level estimated data showed a better performance in mapping GDP distribution (MAE decreased from 115.1 million CNY·km-2 to 74.8 million CNY·km-2). Among all of the independent variables, NTL, land surface temperature (Ts) and plot ratio (PR) showed higher impacts on the GDP estimation accuracy than the other variables. The GDP density map generated by the RF model depicted the detailed spatial distribution of the economy in Ningbo City. By interpreting the spatial distribution of the GDP, we found that the GDP of Ningbo was high in the northeast and low in the southwest and formed continuous clusters in the north. In addition, the GDP of Ningbo also gradually decreased from the urban centre to its surrounding areas. The produced GDP map provides a good reference for the future urban planning and socio-economic development strategies.  
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  Series Volume Series Issue Edition  
  ISSN 0273-1177 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2680  
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Author Otchia, C. S. & Asongu, S. A. url  openurl
  Title Industrial Growth in Sub-Saharan Africa: Evidence from Machine Learning with Insights from Nightlight Satellite Images Type Journal Article
  Year 2019 Publication (up) African Governance and Development Institute Abbreviated Journal  
  Volume Issue Pages  
  Keywords Remote Sensing  
  Abstract This study uses nightlight time data and machine learning techniques to predict industrial development in Africa. The results provide the first evidence on how machine learning techniques and nightlight data can be used to predict economic development in places where subnational data are missing or not precise. Taken together, the research confirms four groups of important determinants of industrial growth: natural resources, agriculture growth, institutions, and manufacturing imports. Our findings indicate that Africa should follow a more

multisector approach for development, putting natural resources and agriculture productivity growth at the forefront.
 
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  Notes Approved no  
  Call Number IDA @ intern @ Serial 2627  
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Author Shen, J.; Tower, J. url  doi
openurl 
  Title Effects of light on aging and longevity Type Journal Article
  Year 2019 Publication (up) Ageing Research Reviews Abbreviated Journal Ageing Res Rev  
  Volume 53 Issue Pages 100913  
  Keywords Human Health; Review; Aging; longevity  
  Abstract Increasing evidence suggests an important role for light in regulation of aging and longevity. UV radiation is a mutagen that can promote aging and decrease longevity. In contrast, NIR light has shown protective effects in animal disease models. In invertebrates, visible light can shorten or extend lifespan, depending on the intensity and wavelength composition. Visible light also impacts human health, including retina function, sleep, cancer and psychiatric disorders. Possible mechanisms of visible light include: controlling circadian rhythms, inducing oxidative stress, and acting through the retina to affect neuronal circuits and systems. Changes in artificial lighting (e.g., LEDs) may have implications for human health. It will be important to further explore the mechanisms of how light affects aging and longevity, and how light affects human health.  
  Address Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles CA 90089-2910, United States  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 1568-1637 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:31154014 Approved no  
  Call Number GFZ @ kyba @ Serial 2514  
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