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Open AccessArticle

Astrotourism and Night Sky Brightness Forecast: First Probabilistic Model Approach

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Instituto Universitario de Ciencias y Tecnologías Cibernéticas (IUCTC), University of Las Palmas de Gran Canaria, Campus de Tafira, 35017 Las Palmas de Gran Canaria, Spain
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Instituto Universitario de Ciencias y Tecnologías Cibernéticas (IUCTC), University of Las Palmas de Gran Canaria, Despacho C-2.21, Ed. de Económicas y Empresariales, Campus de Tafira, 35017 Las Palmas de Gran Canaria, Spain
3
Instituto para el Desarrollo Tecnológico y la Innovación en Comunicaciones (IDeTIC), University of Las Palmas de Gran Canaria, Despacho D-102, Pabellón B, Ed. de Electrónica y Comunicaciones, 35017 Las Palmas de Gran Canaria, Spain
4
Management Science and Business Economics Group, University of Edinburgh Business School, Edinburgh EH8 9JS, UK
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(13), 2840; https://doi.org/10.3390/s19132840
Received: 14 April 2019 / Revised: 8 June 2019 / Accepted: 24 June 2019 / Published: 26 June 2019
(This article belongs to the Special Issue New Trends in Tourism Business Intelligence)
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. View Full-Text
Keywords: night sky brightness; sky quality metre; astrotourism; celestial tourism; ARIMA; artificial neural network (ANN) night sky brightness; sky quality metre; astrotourism; celestial tourism; ARIMA; artificial neural network (ANN)
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C-Sánchez, E.; Sánchez-Medina, A.J.; Alonso-Hernández, J.B.; Voltes-Dorta, A. Astrotourism and Night Sky Brightness Forecast: First Probabilistic Model Approach. Sensors 2019, 19, 2840.

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