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Author Benfield, J.A.; Nutt, R.J.; Taff, B.D.; Miller, Z.D.; Costigan, H.; Newman, P. url  doi
openurl 
  Title (up) A laboratory study of the psychological impact of light pollution in National Parks Type Journal Article
  Year 2018 Publication Journal of Environmental Psychology Abbreviated Journal Journal of Environmental Psychology  
  Volume 57 Issue Pages 67-72  
  Keywords Conservation; Skyglow; Psychology  
  Abstract Light pollution is ubiquitous in much of the developed and developing world, including rural and wilderness areas. Other sources of pollution, such as noise or motorized vehicle emissions, are known to impact the perceived quality of natural settings as well as the psychological well-being and satisfaction of visitors to those locations, but the effects of light pollution on visitors to natural settings is largely unstudied. Using experimental manipulations of light pollution levels in virtual reality simulations of three U.S. National Parks, the current study aimed to provide initial evidence of an effect on visitors. Results show that light pollution impacts a range of psychological and scene evaluation dimensions but that pristine night skies are not necessarily viewed as the ideal, likely due to being viewed as unfamiliar or unrealistic because so few have experienced the true baseline.  
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  Series Volume Series Issue Edition  
  ISSN 0272-4944 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 1941  
Permanent link to this record
 

 
Author Roberts, T.S. url  doi
openurl 
  Title (up) A Lapland Longspur Tragedy: Being an Account of a Great Destruction of These Birds during a Storm in Southwestern Minnesota and Northwestern Iowa in March, 1904 Type Journal Article
  Year 1907 Publication The Auk Abbreviated Journal The Auk  
  Volume 24 Issue 4 Pages 369-377  
  Keywords Animals  
  Abstract  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0004-8038 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2417  
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Author Li, C.; Li, G.; Zhu, Y.; Ge, Y.; Kung, H.-te; Wu, Y. url  doi
openurl 
  Title (up) A likelihood-based spatial statistical transformation model (LBSSTM) of regional economic development using DMSP/OLS time series and nighttime light imagery Type Journal Article
  Year 2017 Publication Spatial Statistics Abbreviated Journal Spatial Statistics  
  Volume 21 Issue B Pages 421-439  
  Keywords Remote Sensing  
  Abstract In a regional economy, the central city of a metropolitan area has a radiative effect and an accumulative effect on its surrounding cities. Considering the limitations of traditional data sources (e.g., its subjectivity) and the advantages of nighttime light data, including its objectivity, availability and cyclicity, this paper proposes a likelihood spatial statistical transformation model (LBSSTM) to invert for the gross domestic product (GDP) of the surrounding cities, using time series of Sum of Lights (SOL) data covering the central city and taking advantage of the economic and spatial association between the central city and the surrounding cities within a metropolitan area and the correlation between SOL and GDP. The Wuhan Metropolitan Area is chosen to verify the model using time series analysis and exploratory spatial data analysis (ESDA). The experimental results show the feasibility of the proposed LBSSTM. The prediction accuracy of our model is verified by cross-validation using data from 1998, 2004 and 2011, based on the 3σ rule. This model can quantitatively express the agglomeration and diffusion effect of the central city and reveal the spatial pattern of this effect. The results of this work are potentially useful in making spatio-temporal economic projections and filling in missing data from some regions, as well as gaining a deeper quantitative and spatio-temporal understanding of the laws underlying regional economic development.  
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  Series Volume Series Issue Edition  
  ISSN 2211-6753 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number LoNNe @ kyba @ Serial 1644  
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Author Sun, L.; Tang, L.; Shao, G.; Qiu, Q.; Lan, T.; Shao, J. url  doi
openurl 
  Title (up) A Machine Learning-Based Classification System for Urban Built-Up Areas Using Multiple Classifiers and Data Sources Type Journal Article
  Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing  
  Volume 12 Issue 1 Pages 91  
  Keywords Remote Sensing  
  Abstract Information about urban built-up areas is important for urban planning and management. However, obtaining accurate information about urban built-up areas is a challenge. This study developed a general-purpose built-up area intelligent classification (BAIC) system that supports various types of data and classifiers. All of the steps in the BAIC were implemented using Python modules including Numpy, Pandas, matplotlib, and scikit-learn. We used the BAIC to conduct a classification experiment that involved seven types of input data; namely, Point of Interest (POI), Road Network (RN), nighttime light (NTL), a combination of POI and RN data (POIRN), a combination of POI and NTL data (POINTL), a combination of RN and NTL data (RNNTL), and a combination of POI, RN, and NTL data (POIRNNTL), and five classifiers, namely, Logistic Regression (LR), Decision Tree (DT), Random Forests (RF), Gradient Boosted Decision Trees (GBDT), and AdaBoost. The results show the following: (1) among the 35 combinations of the five classifiers and seven types of input data, the overall accuracy (OA) ranged from 76 to 89%, F1 values ranged from 0.73 to 0.86, and the area under the receiver operating characteristic (ROC) curve (AUC) ranged from 0.83 to 0.95. The largest F1 value and OA were obtained using the POIRNNTL data and AdaBoost, while the largest AUC was obtained using POIRNNTL and POINTL data against AdaBoost, LR, and RF; and (2) the advantages of the BAIC include its support for multi-source input data, its objective accuracy assessment, and its robust classifiers. The BAIC can quickly and efficiently realize the automatic classification of urban built-up areas at a reasonably low cost and can be readily applied to other urban areas in the world where any kind of POI, RN, or NTL data coverage is available. The results of this study are expected to provide timely and effective reference information for urban planning and urban management departments, and could also potentially be used to develop large-scale maps of urban built-up areas in the future.  
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  Series Volume Series Issue Edition  
  ISSN 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2800  
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Author Fiorentin, P.; Boscaro, F. url  doi
openurl 
  Title (up) A method for measuring the light output of video advertising reproduced by LED billboards Type Journal Article
  Year 2019 Publication Measurement Abbreviated Journal Measurement  
  Volume 138 Issue Pages 25-33  
  Keywords Lighting; Energy; Instrumentation; Planning; Light-emitting diode displays; Photometry; Video recording; Image analysis; CCD image sensors; Luminance; Glare  
  Abstract Improving knowledge of the light output of digital billboards is important to better assess their effect on driver distraction when they are installed along roads. In this work the emission of an LED based billboard is measured when playing advertising video-clips. In particular the average and the maximum values of the luminance are evaluated. The same video-clips are also analyzed when shown on an LCD monitor, aiming at separating the variability of the videos and of the playing device. The results allow to evaluate an utilization factor of the billboard: the videos have an average luminance around 11% and a peak luminance of 35% of the maximum luminance obtainable from the billboard. The power consumption of the billboard is measured, aside the photometric analysis. The luminance of the device are found linearly dependent on both the power and the effective current absorbed by the device from the grid, with a discrepancy within 6%. It could be a useful information for billboard manufacturers to qualify their product when they do not own photometric instruments.  
  Address Department of Industrial Engineering, University of Padova, Padova, Italy; pietro.fiorentin(at)unipd.it  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0263-2241 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2214  
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