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Convergence between Increased Light Pollution and Urban Sprawl Dynamic in Poland (2012–2022)
Corresponding Author(s) : Hubert Horynek
Geomatics and Environmental Engineering,
Vol. 18 No. 6 (2024): Geomatics and Environmental Engineering
Abstract
Urban sprawl is a nuisance – both economically and ecologically speaking. Among the causes of this nuisance is light pollution; both the scale of the light pollution and the spatial expansion of suburbs in Poland increased significantly during the period 2012–2022. The most significant light pollution occurs in urbanized areas in general; however, the scattered developments of suburbs make the problem of light pollution in these areas disproportionate to the population density as compared to cities. The research that is described below analyzed changes in the amounts of light that were emitted into the sky (radiance) as were calculated on the basis of observational data from the Suomi NPP meteorological satellite as well as housing production dynamics. Data regarding both radiance and housing production was acquired for communes and then aggregated to larger areas depending on the urban, suburban, or rural character of each commune. Then, the agglomeration areas were analyzed – distinguishing between urban centers and non-urban agglomeration areas (suburbs). Two convergence indices were analyzed: Spearman’s rank correlation coefficient, and coefficient of determination R2. It turns out that, in suburban areas, both indices returned much higher convergence rates between light pollution and housing construction than in the cases of the cities. The causes of this phenomenon need further research; nevertheless, two possible top-down solutions of this problem may be lighting masterplans and the modernization of lighting fixtures.
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- Redding S.J.: Suburbanization in the United States 1970–2010. National Bureau of Economic Research, No. w28841, 2021.
- Cocheci R.-M., Alexandru-Ionut P.: Assessing the Negative Effects of Suburbanization: The Urban Sprawl Restrictiveness Index in Romania’s Metropolitan Areas. Land, vol. 12, no. 5, 2023, 966. https://doi.org/10.3390/land12050966.
- Wang H., Shi Y., Zhang A., Cao Y., Liu H..: Does suburbanization cause ecological deterioration? An empirical analysis of Shanghai, China. Sustainability, vol. 9, no. 1, 2017, 124. https://doi.org/10.3390/su9010124.
- Hlaváček P., Kopáček M., Horáčková L.: Impact of suburbanisation on sustainable development of settlements in suburban spaces: Smart and new solutions. Sustainability, vol. 11, no. 24, 2019, 7182. https://doi.org/10.3390/su11247182.
- Szarek-Iwaniuk P.: A comparative analysis of spatial data and land use/land cover classification in urbanized areas and areas subjected to anthropogenic pressure for the example of Poland. Sustainability, vol. 13, no. 6, 2021, 3070. https://doi.org/10.3390/su13063070.
- Brody S.: The characteristics, causes, and consequences of sprawling devel opment patterns in the United States. Nature Education Knowledge, vol. 4, no. 5, 2013, 2.
- Jägerbrand A.K.: New framework of sustainable indicators for outdoor LED (light emitting diodes) lighting and SSL (solid state lighting). Sustainability, vol. 7, no. 1, 2015, pp. 1028–1063. https://doi.org/10.3390/su7011028.
- Bennie J., Davies T.W., Duffy J.P., Inger R., Gaston K.J.: Contrasting trends in light pollution across Europe based on satellite observed night time lights. Scientific Reports, 4(1), 2014, 3789.
- Barua E., Kabir M.N., Islam, M.A.: Monitoring the Trend of Nighttime Light Pollution (NLP) in the Chattogram District, Bangladesh, Using DMSP/OLS and VIIRS Data. Journal of Geovisualization and Spatial Analysis, vol. 8(2), 2024, 31.
- Zhou Y., Li X., Asrar G.R., Smith S.J., Imhoff M.: A global record of annual urban dynamics (1992–2013) from nighttime lights. Remote Sensing of Environment, vol. 219, 2018, pp. 206–220. https://doi.org/10.1016/j.rse.2018.10.015.
- Zhao M., Zhou Y., Li X., Cao W., He C., Yu B., Li X., Elvidge C., Cheng W., Zhou C.: Applications of satellite remote sensing of nighttime light observations: Advances, challenges, and perspectives. Remote Sensing, vol. 11(17), 2019, 1971. https://doi.org/10.3390/rs11171971.
- Lamphar H.: Spatiotemporal association of light pollution and urban sprawl using remote sensing imagery and GIS: a simple method based in Otsu’s algorithm. Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 251, 2020, 107060. https://doi.org/10.1016/j.jqsrt.2020.107060.
- Ma T., Zhou C., Pei T., Haynie S., Fan J.: Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: A comparative case study from China’s cities. Remote Sensing of Environment, vol. 124, 2012, pp. 99–107. https://doi.org/10.1016/j.rse.2012.04.018.
- Kotarba A.Z.: Zanieczyszczenie światłem w Polsce. Raport 2023, 2023. [on-line] www.lptt.org.pl [access: 24.07.2024].
- Bustamante-Calabria M., Sánchez de Miguel A., Martín-Ruiz S., Ortiz J.L., Vílchez J.M., Pelegrina A., García A., Zamorano J., Bennie J., Gaston K.J..: Effects of the COVID19 lockdown on urban light emissions: ground and satellite comparison. Remote Sensing, vol. 13, no. 2, 2021, 258. https://doi.org/10.3390/rs13020258.
- Górniak-Zimroz J., Romańczukiewicz K., Sitarska M., Szrek A.: Light-Pollution-Monitoring Method for Selected Environmental and Social Elements. Remote Sensing, vol. 16, no. 5, 2024, 774. https://doi.org/10.3390/rs16050774.
- Kyba C.C.M., Ruhtz T., Fischer J., Hölker F.: Cloud coverage acts as an amplifier for ecological light pollution in urban ecosystems. PloS ONE, vol. 6, no. 3, 2011, e17307. https://doi.org/10.1371/journal.pone.0017307.
- Pun C.S.J., So C.W., Leung W.Y., Wong C.F.: Contributions of artificial lighting sources on light pollution in Hong Kong measured through a night sky brightness monitoring network. Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 139, 2014, pp. 90–108. https://doi.org/10.1016/j.jqsrt.2013.12.014.
- Kocifaj M., Kómar L., Lamphar H., Barentine J., Wallner S.: A systematic light pollution modelling bias in present night sky brightness predictions. Nature Astronomy, vol. 7, no. 3, 2023, pp. 269–279. https://www.nature.com/articles/s41550-023-01916-y.
- Jiang B., Li S., Li J., Zhang Y., Zheng Z.: Spatiotemporal dynamics and sensitive distance identification of light pollution in protected areas based on mutisource data: A case study of Guangdong province, China. International Journal of Environmental Research and Public Health, vol. 19, no. 19, 2022, 12662. https://doi.org/10.3390/ijerph191912662.
- Nadybal S.M., Collins T.W., Grineski S.E.: Light pollution inequities in the continental United States: A distributive environmental justice analysis. Environmental Research, vol. 189, 2020, 109959. https://doi.org/10.1016/j.envres.2020.109959.
- Sun B., Zhang Y., Zhou Q., Gao D.: Streetscale analysis of population exposure to light pollution based on remote sensing and mobile big data – Shenzhen city as a case. Sensors, vol. 20, no. 9, 2020, 2728. https://doi.org/10.3390/s20092728.
- Zheng H., Gui Z., Wu H., Song A.: Developing non-negative spatial autoregressive models for better exploring relation between nighttime light images and land use types. Remote Sensing, vol. 12, no. 5, 2020, 798. https://doi.org/10.3390/rs12050798.
- Huang C., Ye Y., Jin Y., Liang B.: Research progress, hotspots, and evolution of nighttime light pollution: Analysis based on WOS database and remote sensing data. Remote Sensing, vol. 15, no. 9, 2023, 2305. https://doi.org/10.3390/rs15092305.
- Jiang W., He G., Long T., Wang C., Ni Y., Ma R.: Assessing light pollution in China based on nighttime light imagery. Remote Sensing, vol. 9, no. 2, 2017, 135. https://doi.org/10.3390/rs9020135.
- Eurostat, Degree of urbanisation, Information on data, [on-line:] https://ec.europa.eu/eurostat/web/degree-of-urbanisation/information-data [access: 24.07.2024].
- Eurostat, Degree of urbanisation, Methodology, [on-line:] https://ec.europa.eu/eurostat/web/degree-of-urbanisation/methodology [access: 24.07.2024].
- GUS, Funkcjonalne obszary miejskie (FUA), [on-line:] https://stat.gov.pl/statystyka-regionalna/jednostki-terytorialne/unijne-typologie-terytorialne-tercet/funkcjonalne-obszary-miejskie-fua/ [access: 24.07.2024].
- GUS, Delimitacja obszarów wiejskich (DOW), [on-line:] https://stat.gov.pl/statystyka-regionalna/jednostki-terytorialne/delimitacja-obszarow-wiejskich-dow-/ [access: 24.07.2024].
- Al-Rashidi M.S., Yassin M.F., Alhajeri N.S., Malek M.J.: Gaseous air pollution background estimation in urban, suburban, and rural environments. Arabian Journal of Geosciences, vol. 11, 2018, 59. https://doi.org/10.1007/s12517-017-3369-2.
- Ivanovski M., Alatič K., Urbancl D., Simonič M., Goričanec D., Vončina R.: Assessment of air pollution in different areas (urban, suburban, and rural) in Slovenia from 2017 to 2021. Atmosphere, vol. 14, no. 3, 2023, 578.
- Dudek-Mańkowska S., Grochowski M., Sitnik K.: Changes in the Characteristics of Suburbanization in the Warsaw Metropolitan Area in the First Decades of the 21st Century. Sustainability, vol. 16, no. 11, 2024, 4827. https://doi.org/10.3390/su16114827.
- GUS, Bank Danych Lokalnych, [on-line:] https://bdl.stat.gov.pl/bdl/start [access: 24.07.2024].
- Silva C.: Auckland’s urban sprawl, policy ambiguities and the periurbanisation to Pukekohe. Urban Science, vol. 3, no. 1, 2018, 1. https://doi.org/10.3390/urbansci3010001.
- Bueno-Suárez C., Coq-Huelva D.: Sustaining what is unsustainable: A review of urban sprawl and urban socioenvironmental policies in North America and Western Europe. Sustainability, vol. 12, no. 11, 2020, 4445. https://doi.org/10.3390/su12114445.
- Zhang L., Shu X., Zhang L.: Urban sprawl and its multidimensional and multiscale measurement. Land, vol. 12, no. 3, 2023, 630. https://doi.org/10.3390/land12030630.
- Shi, Y., Zhou L., Guo X., Li J.: The multidimensional measurement method of urban sprawl and its empirical analysis in Shanghai metropolitan area. Sustainability, vol. 15, no. 2, 2023, 1020. https://doi.org/10.3390/su15021020.
- Górecki T.: Podstawy statystyki z przykładami w R. Wydawnictwo BTC, Legionowo 2011.
- Weisberg S.: YeoJohnson power transformations 2001, [on-line:] https://www.stat.umn.edu/arc/yjpower.pdf [access: 30.05.2024].
- Riani M., Atkinson A.C., Corbellini A.: Automatic robust Box–Cox and extended Yeo–Johnson transformations in regression. Statistical Methods & Applications, vol. 32, no. 1, 2023, 75–102.
- Stanisz, A.: Przystępny kurs statystyki: z zastosowaniem STATISTICA PL na przykładach z medycyny, Statsoft Polska, Kraków (1998).
- Li J., Xu Y., Cui W., Ji M., Su B., Wu Y., Wang J.: Investigation of nighttime light pollution in Nanjing, China by mapping illuminance from field observations and Luojia 101 imagery. Sustainability, vol. 12, no. 2, 2020, 681. https://doi.org/10.3390/su12020681.
- Estrada García R., García Gil M., Acosta L., Bará S., Sánchez De Miguel A., Zamorano Calvo J.: Statistical modelling and satellite monitoring of upward light from public lighting. Lighting Research & Technology, vol. 48, no. 7, 2016, pp. 810–822. http://dx.doi.org/10.1177/1477153515583181.
- Novak T., Gasparovsky D., Becak P., Sokansky K.: Modelling of large light sources radiation to the upper hemisphere – obtrusive light. [in:] Proceedings of the 29th CIE SESSION, Washington, DC, USA, June 14–22, 2019, 2019, pp. 1684–1693. http://dx.doi.org/10.25039/x46.2019.PO171.
- Zielińska-Dąbkowska K.M.: Urban city lights. Light pollution as one of the effects of incorrectly designed external illumination. How can a successful lighting masterplan diminish its impact?, 2014, [on-line:] https://mostwiedzy.pl/en/publication/urban-city-lights-light-pollution-as-one-of-the-effects-of-incorrectly-designed-external-illuminatio,160714-1 [access: 30.05.2024].
- Wallner S.: Usage of vertical fisheyeimages to quantify urban light pollution on small scales and the impact of LED conversion. Journal of Imaging, vol. 5, no. 11, 2019, 86. https://doi.org/10.3390/jimaging5110086.
- Kolláth Z., Dömény A., Kolláth K., Nagy B.: Qualifying lighting remodelling in a Hungarian city based on light pollution effects. Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 181, 2016, pp. 46–51. https://doi.org/10.1016/j.jqsrt.2016.02.025.
References
Redding S.J.: Suburbanization in the United States 1970–2010. National Bureau of Economic Research, No. w28841, 2021.
Cocheci R.-M., Alexandru-Ionut P.: Assessing the Negative Effects of Suburbanization: The Urban Sprawl Restrictiveness Index in Romania’s Metropolitan Areas. Land, vol. 12, no. 5, 2023, 966. https://doi.org/10.3390/land12050966.
Wang H., Shi Y., Zhang A., Cao Y., Liu H..: Does suburbanization cause ecological deterioration? An empirical analysis of Shanghai, China. Sustainability, vol. 9, no. 1, 2017, 124. https://doi.org/10.3390/su9010124.
Hlaváček P., Kopáček M., Horáčková L.: Impact of suburbanisation on sustainable development of settlements in suburban spaces: Smart and new solutions. Sustainability, vol. 11, no. 24, 2019, 7182. https://doi.org/10.3390/su11247182.
Szarek-Iwaniuk P.: A comparative analysis of spatial data and land use/land cover classification in urbanized areas and areas subjected to anthropogenic pressure for the example of Poland. Sustainability, vol. 13, no. 6, 2021, 3070. https://doi.org/10.3390/su13063070.
Brody S.: The characteristics, causes, and consequences of sprawling devel opment patterns in the United States. Nature Education Knowledge, vol. 4, no. 5, 2013, 2.
Jägerbrand A.K.: New framework of sustainable indicators for outdoor LED (light emitting diodes) lighting and SSL (solid state lighting). Sustainability, vol. 7, no. 1, 2015, pp. 1028–1063. https://doi.org/10.3390/su7011028.
Bennie J., Davies T.W., Duffy J.P., Inger R., Gaston K.J.: Contrasting trends in light pollution across Europe based on satellite observed night time lights. Scientific Reports, 4(1), 2014, 3789.
Barua E., Kabir M.N., Islam, M.A.: Monitoring the Trend of Nighttime Light Pollution (NLP) in the Chattogram District, Bangladesh, Using DMSP/OLS and VIIRS Data. Journal of Geovisualization and Spatial Analysis, vol. 8(2), 2024, 31.
Zhou Y., Li X., Asrar G.R., Smith S.J., Imhoff M.: A global record of annual urban dynamics (1992–2013) from nighttime lights. Remote Sensing of Environment, vol. 219, 2018, pp. 206–220. https://doi.org/10.1016/j.rse.2018.10.015.
Zhao M., Zhou Y., Li X., Cao W., He C., Yu B., Li X., Elvidge C., Cheng W., Zhou C.: Applications of satellite remote sensing of nighttime light observations: Advances, challenges, and perspectives. Remote Sensing, vol. 11(17), 2019, 1971. https://doi.org/10.3390/rs11171971.
Lamphar H.: Spatiotemporal association of light pollution and urban sprawl using remote sensing imagery and GIS: a simple method based in Otsu’s algorithm. Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 251, 2020, 107060. https://doi.org/10.1016/j.jqsrt.2020.107060.
Ma T., Zhou C., Pei T., Haynie S., Fan J.: Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: A comparative case study from China’s cities. Remote Sensing of Environment, vol. 124, 2012, pp. 99–107. https://doi.org/10.1016/j.rse.2012.04.018.
Kotarba A.Z.: Zanieczyszczenie światłem w Polsce. Raport 2023, 2023. [on-line] www.lptt.org.pl [access: 24.07.2024].
Bustamante-Calabria M., Sánchez de Miguel A., Martín-Ruiz S., Ortiz J.L., Vílchez J.M., Pelegrina A., García A., Zamorano J., Bennie J., Gaston K.J..: Effects of the COVID19 lockdown on urban light emissions: ground and satellite comparison. Remote Sensing, vol. 13, no. 2, 2021, 258. https://doi.org/10.3390/rs13020258.
Górniak-Zimroz J., Romańczukiewicz K., Sitarska M., Szrek A.: Light-Pollution-Monitoring Method for Selected Environmental and Social Elements. Remote Sensing, vol. 16, no. 5, 2024, 774. https://doi.org/10.3390/rs16050774.
Kyba C.C.M., Ruhtz T., Fischer J., Hölker F.: Cloud coverage acts as an amplifier for ecological light pollution in urban ecosystems. PloS ONE, vol. 6, no. 3, 2011, e17307. https://doi.org/10.1371/journal.pone.0017307.
Pun C.S.J., So C.W., Leung W.Y., Wong C.F.: Contributions of artificial lighting sources on light pollution in Hong Kong measured through a night sky brightness monitoring network. Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 139, 2014, pp. 90–108. https://doi.org/10.1016/j.jqsrt.2013.12.014.
Kocifaj M., Kómar L., Lamphar H., Barentine J., Wallner S.: A systematic light pollution modelling bias in present night sky brightness predictions. Nature Astronomy, vol. 7, no. 3, 2023, pp. 269–279. https://www.nature.com/articles/s41550-023-01916-y.
Jiang B., Li S., Li J., Zhang Y., Zheng Z.: Spatiotemporal dynamics and sensitive distance identification of light pollution in protected areas based on mutisource data: A case study of Guangdong province, China. International Journal of Environmental Research and Public Health, vol. 19, no. 19, 2022, 12662. https://doi.org/10.3390/ijerph191912662.
Nadybal S.M., Collins T.W., Grineski S.E.: Light pollution inequities in the continental United States: A distributive environmental justice analysis. Environmental Research, vol. 189, 2020, 109959. https://doi.org/10.1016/j.envres.2020.109959.
Sun B., Zhang Y., Zhou Q., Gao D.: Streetscale analysis of population exposure to light pollution based on remote sensing and mobile big data – Shenzhen city as a case. Sensors, vol. 20, no. 9, 2020, 2728. https://doi.org/10.3390/s20092728.
Zheng H., Gui Z., Wu H., Song A.: Developing non-negative spatial autoregressive models for better exploring relation between nighttime light images and land use types. Remote Sensing, vol. 12, no. 5, 2020, 798. https://doi.org/10.3390/rs12050798.
Huang C., Ye Y., Jin Y., Liang B.: Research progress, hotspots, and evolution of nighttime light pollution: Analysis based on WOS database and remote sensing data. Remote Sensing, vol. 15, no. 9, 2023, 2305. https://doi.org/10.3390/rs15092305.
Jiang W., He G., Long T., Wang C., Ni Y., Ma R.: Assessing light pollution in China based on nighttime light imagery. Remote Sensing, vol. 9, no. 2, 2017, 135. https://doi.org/10.3390/rs9020135.
Eurostat, Degree of urbanisation, Information on data, [on-line:] https://ec.europa.eu/eurostat/web/degree-of-urbanisation/information-data [access: 24.07.2024].
Eurostat, Degree of urbanisation, Methodology, [on-line:] https://ec.europa.eu/eurostat/web/degree-of-urbanisation/methodology [access: 24.07.2024].
GUS, Funkcjonalne obszary miejskie (FUA), [on-line:] https://stat.gov.pl/statystyka-regionalna/jednostki-terytorialne/unijne-typologie-terytorialne-tercet/funkcjonalne-obszary-miejskie-fua/ [access: 24.07.2024].
GUS, Delimitacja obszarów wiejskich (DOW), [on-line:] https://stat.gov.pl/statystyka-regionalna/jednostki-terytorialne/delimitacja-obszarow-wiejskich-dow-/ [access: 24.07.2024].
Al-Rashidi M.S., Yassin M.F., Alhajeri N.S., Malek M.J.: Gaseous air pollution background estimation in urban, suburban, and rural environments. Arabian Journal of Geosciences, vol. 11, 2018, 59. https://doi.org/10.1007/s12517-017-3369-2.
Ivanovski M., Alatič K., Urbancl D., Simonič M., Goričanec D., Vončina R.: Assessment of air pollution in different areas (urban, suburban, and rural) in Slovenia from 2017 to 2021. Atmosphere, vol. 14, no. 3, 2023, 578.
Dudek-Mańkowska S., Grochowski M., Sitnik K.: Changes in the Characteristics of Suburbanization in the Warsaw Metropolitan Area in the First Decades of the 21st Century. Sustainability, vol. 16, no. 11, 2024, 4827. https://doi.org/10.3390/su16114827.
GUS, Bank Danych Lokalnych, [on-line:] https://bdl.stat.gov.pl/bdl/start [access: 24.07.2024].
Silva C.: Auckland’s urban sprawl, policy ambiguities and the periurbanisation to Pukekohe. Urban Science, vol. 3, no. 1, 2018, 1. https://doi.org/10.3390/urbansci3010001.
Bueno-Suárez C., Coq-Huelva D.: Sustaining what is unsustainable: A review of urban sprawl and urban socioenvironmental policies in North America and Western Europe. Sustainability, vol. 12, no. 11, 2020, 4445. https://doi.org/10.3390/su12114445.
Zhang L., Shu X., Zhang L.: Urban sprawl and its multidimensional and multiscale measurement. Land, vol. 12, no. 3, 2023, 630. https://doi.org/10.3390/land12030630.
Shi, Y., Zhou L., Guo X., Li J.: The multidimensional measurement method of urban sprawl and its empirical analysis in Shanghai metropolitan area. Sustainability, vol. 15, no. 2, 2023, 1020. https://doi.org/10.3390/su15021020.
Górecki T.: Podstawy statystyki z przykładami w R. Wydawnictwo BTC, Legionowo 2011.
Weisberg S.: YeoJohnson power transformations 2001, [on-line:] https://www.stat.umn.edu/arc/yjpower.pdf [access: 30.05.2024].
Riani M., Atkinson A.C., Corbellini A.: Automatic robust Box–Cox and extended Yeo–Johnson transformations in regression. Statistical Methods & Applications, vol. 32, no. 1, 2023, 75–102.
Stanisz, A.: Przystępny kurs statystyki: z zastosowaniem STATISTICA PL na przykładach z medycyny, Statsoft Polska, Kraków (1998).
Li J., Xu Y., Cui W., Ji M., Su B., Wu Y., Wang J.: Investigation of nighttime light pollution in Nanjing, China by mapping illuminance from field observations and Luojia 101 imagery. Sustainability, vol. 12, no. 2, 2020, 681. https://doi.org/10.3390/su12020681.
Estrada García R., García Gil M., Acosta L., Bará S., Sánchez De Miguel A., Zamorano Calvo J.: Statistical modelling and satellite monitoring of upward light from public lighting. Lighting Research & Technology, vol. 48, no. 7, 2016, pp. 810–822. http://dx.doi.org/10.1177/1477153515583181.
Novak T., Gasparovsky D., Becak P., Sokansky K.: Modelling of large light sources radiation to the upper hemisphere – obtrusive light. [in:] Proceedings of the 29th CIE SESSION, Washington, DC, USA, June 14–22, 2019, 2019, pp. 1684–1693. http://dx.doi.org/10.25039/x46.2019.PO171.
Zielińska-Dąbkowska K.M.: Urban city lights. Light pollution as one of the effects of incorrectly designed external illumination. How can a successful lighting masterplan diminish its impact?, 2014, [on-line:] https://mostwiedzy.pl/en/publication/urban-city-lights-light-pollution-as-one-of-the-effects-of-incorrectly-designed-external-illuminatio,160714-1 [access: 30.05.2024].
Wallner S.: Usage of vertical fisheyeimages to quantify urban light pollution on small scales and the impact of LED conversion. Journal of Imaging, vol. 5, no. 11, 2019, 86. https://doi.org/10.3390/jimaging5110086.
Kolláth Z., Dömény A., Kolláth K., Nagy B.: Qualifying lighting remodelling in a Hungarian city based on light pollution effects. Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 181, 2016, pp. 46–51. https://doi.org/10.1016/j.jqsrt.2016.02.025.