Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/63295
Título: Astrotourism and night sky brightness forecast: first probabilistic model approach
Autores/as: Caballero-Sánchez, Eleazar
Sánchez-Medina, Agustín J. 
Alonso-Hernández, Jesús B. 
Voltes-Dorta, Augusto 
Clasificación UNESCO: 33 Ciencias tecnológicas
531290 Economía sectorial: turismo
Palabras clave: Sky quality metre
Astrotourism
Celestial tourism
ARIMA
Artificial neural network (ANN), et al.
Fecha de publicación: 2019
Publicación seriada: Sensors 
Resumen: 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.
URI: http://hdl.handle.net/10553/63295
ISSN: 1424-8220
DOI: 10.3390/s19132840
Fuente: Sensors [ISSN 1424-8220], v. 19 (13), 2840
Colección:Artículos
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