Evidence map›Paper›PMID 31247919›Full record

ArticleSensors (Basel, Switzerland)2019

Astrotourism and Night Sky Brightness Forecast: First Probabilistic Model Approach.

Eleazar C-Sánchez, Agustín J Sánchez-Medina, Jesús B Alonso-Hernández, Augusto Voltes-Dorta

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Eleazar C-SánchezInstituto Universitario de Ciencias y Tecnologías Cibernéticas (IUCTC), University of Las Palmas de Gran Canaria, Campus de Tafira, 35017 Las Palmas de Gran Canaria, Spain. eleazar.caballero101@alu.ulpgc.es.ORCID 0000-0002-2471-3457
Agustín J Sánchez-MedinaInstituto 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.ORCID 0000-0002-7569-3556
Jesús B Alonso-HernándezInstituto 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.ORCID 0000-0002-7866-585X
Augusto Voltes-DortaManagement Science and Business Economics Group, University of Edinburgh Business School, Edinburgh EH8 9JS, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

ARIMAartificial neural network (ANN)astrotourismcelestial tourismnight sky brightnesssky quality metre

Identifiers

PMID31247919
PMCPMC6651810

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.