Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground Brightness
There are several tools and methods to quantify light pollution due to direct or reflected light emitted towards the sky. Unmanned aerial vehicles (UAV) are still rarely used in light pollution studies. In this study, a digital camera and a sky quality meter mounted on a UAV have been used to study...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/9/2052 |
| _version_ | 1797503084703776768 |
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| author | Luciano Massetti Marco Paterni Silvia Merlino |
| author_facet | Luciano Massetti Marco Paterni Silvia Merlino |
| author_sort | Luciano Massetti |
| collection | DOAJ |
| description | There are several tools and methods to quantify light pollution due to direct or reflected light emitted towards the sky. Unmanned aerial vehicles (UAV) are still rarely used in light pollution studies. In this study, a digital camera and a sky quality meter mounted on a UAV have been used to study the relationship between indices computed on night images and night ground brightness (NGB) measured by an optical device pointed downward towards the ground. Both measurements were taken simultaneously during flights at an altitude of 70 and 100 m, and with varying exposure time. NGB correlated significantly both with the brightness index (−0.49 ÷ −0.56) and with red (−0.52 ÷ −0.58) and green band indices (−0.42 ÷ −0.58). A linear regression model based on the luminous intensity index was able to estimate observed NGB with an RMSE varying between 0.21 and 0.46 mpsas. Multispectral analysis applied to images taken at 70 m showed that increasing exposure time might cause a saturation of the colors of the image, especially in the red band, that worsens the correlation between image indices and NGB. Our study suggests that the combined use of low cost devices such as UAV and a sky quality meter can be used for assessing hotspot areas of light pollution originating from the surface. |
| first_indexed | 2024-03-10T03:45:27Z |
| format | Article |
| id | doaj.art-f917d592340448069c93e5739a7ae2f0 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T03:45:27Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-f917d592340448069c93e5739a7ae2f02023-11-23T09:09:49ZengMDPI AGRemote Sensing2072-42922022-04-01149205210.3390/rs14092052Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground BrightnessLuciano Massetti0Marco Paterni1Silvia Merlino2Istituto per la BioEconomia del Consiglio Nazionale delle Ricerche, IBE–CNR, 50019 Sesto Fiorentino, FI, ItalyIstituto di Fisiologia Clinica del Consiglio Nazionale delle Ricerche, IFC–CNR, 56124 Pisa, PI, ItalyIstituto di Scienze Marine del Consiglio Nazionale delle Ricerche, ISMAR–CNR, 19032 Lerici, SP, ItalyThere are several tools and methods to quantify light pollution due to direct or reflected light emitted towards the sky. Unmanned aerial vehicles (UAV) are still rarely used in light pollution studies. In this study, a digital camera and a sky quality meter mounted on a UAV have been used to study the relationship between indices computed on night images and night ground brightness (NGB) measured by an optical device pointed downward towards the ground. Both measurements were taken simultaneously during flights at an altitude of 70 and 100 m, and with varying exposure time. NGB correlated significantly both with the brightness index (−0.49 ÷ −0.56) and with red (−0.52 ÷ −0.58) and green band indices (−0.42 ÷ −0.58). A linear regression model based on the luminous intensity index was able to estimate observed NGB with an RMSE varying between 0.21 and 0.46 mpsas. Multispectral analysis applied to images taken at 70 m showed that increasing exposure time might cause a saturation of the colors of the image, especially in the red band, that worsens the correlation between image indices and NGB. Our study suggests that the combined use of low cost devices such as UAV and a sky quality meter can be used for assessing hotspot areas of light pollution originating from the surface.https://www.mdpi.com/2072-4292/14/9/2052light pollutionartificial light at nightunmanned aerial vehiclesky quality meterremote sensingnight-time lights |
| spellingShingle | Luciano Massetti Marco Paterni Silvia Merlino Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground Brightness Remote Sensing light pollution artificial light at night unmanned aerial vehicle sky quality meter remote sensing night-time lights |
| title | Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground Brightness |
| title_full | Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground Brightness |
| title_fullStr | Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground Brightness |
| title_full_unstemmed | Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground Brightness |
| title_short | Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground Brightness |
| title_sort | monitoring light pollution with an unmanned aerial vehicle a case study comparing rgb images and night ground brightness |
| topic | light pollution artificial light at night unmanned aerial vehicle sky quality meter remote sensing night-time lights |
| url | https://www.mdpi.com/2072-4292/14/9/2052 |
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