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Author Kinzey, B. R.; Smalley, E.; Ghosh, S.; Tuenge, J. R.; Pipkin, A.; Trevino, K. url  doi
openurl 
  Title Lighting and Power Upgrade Recommendations for U.S. National Park Service Caribbean Units Type Journal Article
  Year 2019 Publication National Park Service Caribbean Units Abbreviated Journal  
  Volume (up) Issue Pages  
  Keywords Lighting; Conservation; Ecology; Skyglow; Planning  
  Abstract The U.S. National Park Service (NPS) maintains and operates numerous park units along the Eastern Seaboard of the United States, extending into the Caribbean to Commonwealth territories like Puerto Rico and the U.S. Virgin Islands (USVI). Several of these units were in the direct path of hurricanes Irma and Maria during the 2017 hurricane season and suffered considerable damage, including power outages, structural damage, and destroyed equipment. In February 2018, a task force deployed to three locations in the Caribbean to assess hurricane damage to the existing lighting systems and energy infrastructure. The primary objective was providing related recommendations for resiliency upgrades to the lighting and electrical supply systems, with special added emphasis on the numerous goals, objectives, and requirements of the NPS (such as protecting night skies, wildlife, wilderness character, cultural resources, etc.). Numerous opportunities exist for simultaneously increasing resiliency and preserving natural environments within these sensitive locations, and technological approaches that work in the extreme conditions encountered here should readily translate to many other less complex sites across the greater park system. Ultimately, care and attention to detail in implementation are the most important underlying requirements for success across the myriad needs likely encountered at these sites, once commitment to resolving them has been secured  
  Address  
  Corporate Author Thesis  
  Publisher U.S. Department of Energy Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ intern @ Serial 2626  
Permanent link to this record
 

 
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 African Governance and Development Institute Abbreviated Journal  
  Volume (up) 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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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ intern @ Serial 2627  
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Author Chen, J., & Li, L. url  doi
openurl 
  Title Regional Economic Activity Derived From MODIS Data: A Comparison With DMSP/OLS and NPP/VIIRS Nighttime Light Data Type Journal Article
  Year 2019 Publication IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Abbreviated Journal  
  Volume (up) Issue Pages 1-11  
  Keywords Remote Sensing; Economics  
  Abstract Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) and Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light data are the two most commonly used indicators of gross domestic product (GDP) estimation. Few studies explore the potential of daytime satellite data for estimating GDP. This study demonstrates a linear support vector machine (Linear-SVM) model to estimate GDP over Hubei province and Guangdong province, China, in 2013 from Moderate Resolution Imaging Spectroradiometer (MODIS) data. Also, a comparison of MODIS data with DMSP/OLS and NPP/VIIRS nighttime light data was conducted. Results show that the Linear-SVM model (Hubei: R2 = 0.66, 0.71, 0.92; Guangdong: R2 = 0.37, 0.32, 0.67) has better model performance than simple linear regression (R2 = 0.54, 0.59, 0.86; R2 = 0.23, 0.23, 0.63) based on DMSP/OLS nighttime lights, DMSP/OLS corrected nighttime lights, and NPP/VIIRS nighttime lights, respectively, while MODIS data has model performance of R2 = 0.77 (Hubei) and R2 = 0.55 (Guangdong) based on the Linear-SVM model, further indicating that MODIS data improves the accuracy of GDP estimation compared to DMSP/OLS nighttime lights. In addition, MODIS data produced finer GDP estimation than DMSP/OLS nighttime lights, especially in dark and light saturated areas. Although MODIS data is not as accurate as the NPP/VIIRS nighttime lights for estimating GDP, the proposed method could be applicable to other daytime satellite data and has broad prospects for improving the spatial and temporal resolution of regional economic activity and improving estimation accuracy.  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ intern @ Serial 2630  
Permanent link to this record
 

 
Author Bauhr, M. & Carlitz, R. url  openurl
  Title Transparency and the quality of local public service provision Type Journal Article
  Year 2019 Publication The Quality of Government Institute Abbreviated Journal QOG  
  Volume (up) Issue 5 Pages 1-43  
  Keywords Economics; Remote Sensing; public service delivery; Vietnam; Asia  
  Abstract Transparency has been widely promoted as a tool for improving public service

delivery; however, empirical evidence is inconclusive. We suggest that the effects of transparency on service provision are contingent on the nature of the service. Specifically, transparency is more likely to improve the quality of service provision when street-level discretion is high, since discretion increases information asymmetries, and, in the absence of transparency, allows officials to target public services in suboptimal ways. Using finely grained data from the Vietnam Provincial Governance and Public Administration Performance Index between 2011–2017, we show that communes that experience increases in transparency also experience improved quality of education and health (services characterized by greater discretion), while the quality of infrastructure

provision (characterized by less discretion) bears no relation to increased transparency. The findings help us understand when transparency can improve service provision, as well the effects of transparency reforms in non-democratic settings.
 
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  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ intern @ Serial 2637  
Permanent link to this record
 

 
Author Carley J. S., Grabarczyk, E. E., Vonhof, M. J., & Gill, S. A. url  doi
openurl 
  Title Social factors, not anthropogenic noise or artificial light, influence onset of dawn singing in a common songbird Type Journal Article
  Year 2019 Publication The Auk: Ornithological Advances Abbreviated Journal  
  Volume (up) Issue Pages  
  Keywords Animals  
  Abstract With worldwide increases in artificial light and anthropogenic noise, understanding how these pollutants influence animals allows us to better mitigate potential negative effects. Both light and noise affect the timing of daily activities, including the onset of dawn song in birds, yet the influence of these pollutants compared with social factors that also influence song onset remains unknown. We investigated the onset of dawn song, testing hypotheses aimed at understanding the influences of light and noise pollution as well as male competition, pairing status, and breeding stage on timing of dawn singing by male House Wrens (Troglodytes aedon). Overall, models with social factors fit song onset data better than models with abiotic factors of noise and sky glow, and the highest ranking model included nesting stage, number of male neighbors, and temperature. Males began singing earlier when they were building nests and when mates were fertile than during later nesting stages. Males also sang earlier as the number of male neighbors increased. The timing of dawn song by male House Wrens appeared unaffected by day-to-day variation in light and noise pollution, with social factors having larger effects on the onset of daily behavior in this species.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ intern @ Serial 2643  
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