Citizen Science to Assess Light Pollution with Mobile Phones
The analysis of the colour of artificial lights at night has an impact on diverse fields, but current data sources have either limited resolution or scarce availability of images for a specific region. In this work, we propose crowdsourced photos of streetlights as an alternative data source: for th...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/19/4976 |
| _version_ | 1827653143939252224 |
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| author | Gorka Muñoz-Gil Alexandre Dauphin Federica A. Beduini Alejandro Sánchez de Miguel |
| author_facet | Gorka Muñoz-Gil Alexandre Dauphin Federica A. Beduini Alejandro Sánchez de Miguel |
| author_sort | Gorka Muñoz-Gil |
| collection | DOAJ |
| description | The analysis of the colour of artificial lights at night has an impact on diverse fields, but current data sources have either limited resolution or scarce availability of images for a specific region. In this work, we propose crowdsourced photos of streetlights as an alternative data source: for this, we designed NightUp Castelldefels, a pilot for a citizen science experiment aimed at collecting data about the colour of streetlights. In particular, we extract the colour from the collected images and compare it to an official database, showing that it is possible to classify streetlights according to their colour from photos taken by untrained citizens with their own smartphones. We also compare our findings to the results obtained from one of the current sources for this kind of study. The comparison highlights how the two approaches give complementary information about artificial lights at night in the area. This work opens a new avenue in the study of the colour of artificial lights at night with the possibility of accurate, massive and cheap data collection. |
| first_indexed | 2024-03-09T21:12:54Z |
| format | Article |
| id | doaj.art-4a7833438ccf45ee995703b5446d2419 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T21:12:54Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-4a7833438ccf45ee995703b5446d24192023-11-23T21:41:49ZengMDPI AGRemote Sensing2072-42922022-10-011419497610.3390/rs14194976Citizen Science to Assess Light Pollution with Mobile PhonesGorka Muñoz-Gil0Alexandre Dauphin1Federica A. Beduini2Alejandro Sánchez de Miguel3ICFO—Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Castelldefels, 08860 Barcelona, SpainICFO—Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Castelldefels, 08860 Barcelona, SpainICFO—Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Castelldefels, 08860 Barcelona, SpainDepartamento de Física de la Tierra y Astrofísica, Instituto de Física de Partículas y del Cosmos (IPARCOS), Universidad Complutense, 28040 Madrid, SpainThe analysis of the colour of artificial lights at night has an impact on diverse fields, but current data sources have either limited resolution or scarce availability of images for a specific region. In this work, we propose crowdsourced photos of streetlights as an alternative data source: for this, we designed NightUp Castelldefels, a pilot for a citizen science experiment aimed at collecting data about the colour of streetlights. In particular, we extract the colour from the collected images and compare it to an official database, showing that it is possible to classify streetlights according to their colour from photos taken by untrained citizens with their own smartphones. We also compare our findings to the results obtained from one of the current sources for this kind of study. The comparison highlights how the two approaches give complementary information about artificial lights at night in the area. This work opens a new avenue in the study of the colour of artificial lights at night with the possibility of accurate, massive and cheap data collection.https://www.mdpi.com/2072-4292/14/19/4976citizen sciencelight pollutionmultispectral properties of lighting |
| spellingShingle | Gorka Muñoz-Gil Alexandre Dauphin Federica A. Beduini Alejandro Sánchez de Miguel Citizen Science to Assess Light Pollution with Mobile Phones Remote Sensing citizen science light pollution multispectral properties of lighting |
| title | Citizen Science to Assess Light Pollution with Mobile Phones |
| title_full | Citizen Science to Assess Light Pollution with Mobile Phones |
| title_fullStr | Citizen Science to Assess Light Pollution with Mobile Phones |
| title_full_unstemmed | Citizen Science to Assess Light Pollution with Mobile Phones |
| title_short | Citizen Science to Assess Light Pollution with Mobile Phones |
| title_sort | citizen science to assess light pollution with mobile phones |
| topic | citizen science light pollution multispectral properties of lighting |
| url | https://www.mdpi.com/2072-4292/14/19/4976 |
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