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Author (up) C-Sanchez, E.; Sanchez-Medina, A.J.; Alonso-Hernandez, J.B.; Voltes-Dorta, A. url  doi
  Title Astrotourism and Night Sky Brightness Forecast: First Probabilistic Model Approach Type Journal Article
  Year 2019 Publication Sensors (Basel, Switzerland) Abbreviated Journal Sensors (Basel)  
  Volume 19 Issue 13 Pages 2840  
  Keywords Society; Astrotourism; Skyglow; night sky brightness; artificial neural networks  
  Abstract Celestial tourism, also known as astrotourism, astronomical tourism or, less frequently, star tourism, refers to people's interest in visiting places where celestial phenomena can be clearly observed. Stars, skygazing, meteor showers or comets, among other phenomena, arouse people's interest, however, good night sky conditions are required to observe such phenomena. From an environmental point of view, several organisations have surfaced in defence of the protection of dark night skies against light pollution, while from an economic point of view; the idea also opens new possibilities for development in associated areas. The quality of dark skies for celestial tourism can be measured by night sky brightness (NSB), which is used to quantify the visual perception of the sky, including several light sources at a specific point on earth. The aim of this research is to model the nocturnal sky brightness by training and testing a probabilistic model using real NSB data. ARIMA and artificial neural network models have been applied to open NSB data provided by the Globe at Night international programme, with the results of this first model approach being promising and opening up new possibilities for astrotourism. To the best of the authors' knowledge, probabilistic models have not been applied to NSB forecasting.  
  Address Management Science and Business Economics Group, University of Edinburgh Business School, Edinburgh EH8 9JS, UK  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1424-8220 ISBN Medium  
  Area Expedition Conference  
  Notes PMID:31247919 Approved no  
  Call Number GFZ @ kyba @ Serial 2571  
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