Department of Physical Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran


Light pollution is generally referred to as an unplanned increase in artificial lighting and the result is a change in light levels. Population growth and the rapid expansion of urbanization and industrialization can be a factor in increasing light pollution in Iran. Therefore, monitoring night light changes and determining areas with high light pollution is essential and can provide a new approach for environmental planners to use it to manage light pollution at the national and provincial levels. There are several tools for evaluating changes in night light, including operational linear satellite scanning data related to the Meteorological Defense Satellite Program (DMSP / OLS). These data not only help assess the severity of light pollution, but can also be used as a tool for pollution risk management and risk zoning. This study tries to analyze the spatial-temporal pattern of artificial light and light pollution in Iran between 1996 and 2013 by processing DMSP / OLS data and detects critical sources of light pollution. Night light data were used in six time periods (1996, 2001, 2004, 2006, 2011 and2013).  The changes in night light and the intensity of light pollution on a national scale evaluated. Besides the relationship between the relative population density changes in each province and its effect on the changes in night light were analyzed in this research. The results show an increase in night light as well as conversion of low-brightness areas with high-brightness areas during study periods across the country. In addition, the provinces of Tehran and Alborz were identified as the provinces with the highest levels of light pollution in the country, and followed by Khuzestan, Isfahan, Bushehr and Fars. Increasing relative density and unbalanced distribution of population, migration and its intensification between 1996 and 2011 are the main factors in the increase light pollution in the country and also the concentration of maximum light pollution in some provinces. 


Akiyama, Y., 2012. Analysis of light intensity data by the DMSP/OLS satellite image using existing spatial data for monitoring human activity in Japan. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, I-2, XXII ISPRS Congress, Melbourne, Australia, v. 25.

Aubrecht, C., Elvidge, C.D., Longcore, T., Rich, C., Safran, J., Strong, A.E., Eakin, C.M., Baugh, K.E., Tuttle, B.T., Howard, A.T. & Erwin, E.H., 2008. A global inventory of coral reef stressors based on satellite observed nighttime lights. Geocarto International, 23(6), 467-479.

Brahmandzadeh, D. & Rezaei Ghahroudy, Z., 2014. Investigation of the trend of electricity changes in different sectors. Statistics, 6, 33-29 (In Persian).

Baugh, K., Elvidge, C.D., Ghosh, T. & Ziskin, D., 2010. Development of a 2009 stable lights product using DMSP-OLS data. Proceedings of the Asia-Pacific Advanced Network, 30(0), 114.

Bennie, J., Duffy, J.P., Davies, T.W., Correa-Cano, M.E. & Gaston, K.J., 2015. Global trends in exposure to light pollution in natural terrestrial ecosystems, Remote Sensing, 7(3), 2715-2730.

Chalkias, C., Petrakis, M., Psiloglou, B. & Lianou, M., 2006. Modelling of light pollution in suburban areas using remotely sensed imagery and GIS. Journal of Environmental Management, 79(1), 57-63.

Chen, X. & Nordhaus, W.D., 2011. Using luminosity data as a proxy for economic statistics. Proceedings of the National Academy of Sciences, 108(21), 8589-8594.

Cinzano, P., Falchi, F. & Elvidge, C.D., 2001. The first world atlas of the artificial night sky brightness. Monthly Notices of the Royal Astronomical Society, 328(3), 689-707.

Cinzano, P., Falchi, F., Elvidge, C.D. & Baugh, K.E., 2000. The artificial night sky brightness mapped from DMSP satellite Operational Linescan System measurements. Monthly Notices of the Royal Astronomical Society, 318(3), 641-657.

Croft, T.A., 1973. Burning waste gas in oil fields. Nature, 245, 375-376.

Dobson, J.E., Bright, E.A., Coleman, P.R., Durfee, R.C. & Worley, B.A., 2000. LandScan: a global population database for estimating populations at risk. Photogrammetric Engineering and Remote Sensing, 66(7), 849-857.

Doll, C.H., Muller, J.P. & Elvidge, C.D., 2000. Night-time imagery as a tool for global mapping of socioeconomic parameters and greenhouse gas emissions. AMBIO:Journal of the Human Environment, 29(3), 157-162.

Dominoni, D.M., Quetting, M. & Partecke, J., 2013. Long-term effects of chronic light pollution on seasonal functions of European blackbirds (Turdus merula). PLoS One, 8(12), e85069.

Elvidge, C., Baugh, K., Hobson, V., Kihn, E., Kroehl, H., Davis, E. & Cocero, D., 1997. Satellite inventory of human settlements using nocturnal radiation emissions: a contribution for the global toolchest, Global Change Biology, 3(5), 387-395.

Elvidge, C.D., Baugh, K.E., Safran, J.M., Tuttle, B.T., Howard, A.T., Hayes, P.J. & Erwin, E.H., 2005. Preliminary results from nighttime lights change detection. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36(8), 1-4.

Falchi, F., Cinzano, P., Elvidge, C.D., Keith, D.M. & Haim, A., 2011. Limiting the impact of light pollution on human health. Journal of Environmental Management, 92(10), 2714-2722.

Fuller, D.O. & Fulk, M., 2000. Comparison of noaa-avhrr and DMSP-OLS for operational fire monitoring in kalimantan, Indonesia. International Journal of Remote Sensing, 21, 181-187.

Fardad, M. & Yousefi, M., 2001. Assessment of light pollution, study and zoning of its environmental effects using remote sensing and GIS techniques. The 5th National Conference and Specialized Exhibition of Environmental Engineering, Tehran on November 4th (In Persian).

Forghani, M. & Abbaspour, R.A., 2004. Exploration and modeling of spatial corrections-images of DMSP / OLS satellite images and census data in GIS environment. 21th Geomatics National Conference Tehran on May 25th (In Persian).

Han, P., Huang, J., Li, R., Wang, L., Hu, Y., Wang, J. & Huang, W., 2014. Monitoring trends in light pollution in China based on nighttime satellite imagery. Remote Sensing, 6(6), 5541-5558.

He, C., Ma, Q., Liu, Z. & Zhang, Q., 2014. Modeling the spatiotemporal dynamics of electric power consumption in Mainland China using saturation-corrected DMSP/OLS nighttime stable light data. International Journal of Digital Earth, 7(12), 993-1014.

Kohiyama, M., Hayashi, H., Maki, N., Higashida, M., Kroehl, H.W., Elvidge, C.D. & Hobson, V.R., 2004. Early damaged area estimation system using DMSP-OLS night-time imagery. International Journal of Remote Sensing, 25(11), 2015-2036.

Kumar, P., Sajjad, H., Joshi, P.K., Elvidge, C.D., Rehman, S., Chaudhary, B.S., Tripathy, B.R., Singh, J. & Pipal, G., 2019. Modeling the luminous intensity of Beijing, China using DMSP-OLS night-time lights series data for estimating population density. Physics and Chemistry of the Earth, Parts A/B/C, 109, 31-39.

Longcore, T. & Rich, C., 2004. Ecological light pollution. Frontiers in Ecology and the Environment, 2(4), 191-198.

Lo, C.P., 2002. Urban indicators of China from radiance‐calibrated digital DMSP‐OLS nighttime images. Annals of the Association of American Geographers, 92(2), 225-240.

Mohajerani, A.A., 2010. Inconsistency in the spatial distribution of Iran's population. Population, 71, 46-63 (In Persian).

Nizeyimana, E.L., Petersen, G.W., Imhoff, M.L., Sinclair Jr, H.R., Waltman, S.W., Reed-Margetan, D.S., Levine, E.R. & Russo, J.M., 2001. Assessing the impact of land conversion to urban use on soils with different productivity levels in the USA. Soil Science Society of America Journal, 65(2), 391-402.

Pun, C.S.J. & So, C.W., 2012. Night-sky brightness monitoring in Hong Kong. Environmental Monitoring and Assessment, 184(4), 2537-2557.

Raap, T., Pinxten, R. & Eens, M., 2015. Light pollution disrupts sleep in free-living animals. Scientific Reports, 5(1), 1-8.

Pauley, S.M., 2004. Lighting for the human circadian clock: recent research indicates that lighting has become a public health issue. Medical Hypotheses, 63(4), 588-596.

Sutton, P., Roberts, D., Elvidge, C. & Melj, H., 1997. A comparison of nighttime satellite imagery and population density for the continental united states. Photogrammetric Engineering and Remote Sensing, 63, 1303-1313.

Sutton, P.C. & Costanza, R., 2002. Global estimates of market and non-market values derived from nighttime satellite imagery, land cover, and ecosystem service valuation. Ecological Economics, 41(3), 509-527.

Shi, K., Chen, Y., Yu, B., Xu, T., Yang, C., Li, L., Huang, C., Chen, Z., Liu, R. & Wu, J., 2016. Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data. Applied Energy, 184, 450-463.

Taranian, Z., 2014. Article 68 of the Fifth Development Plan Law and the role of the Statistics Center of Iran in its implementation. Statistics, 2 (5), 10-3.

Yu, B., Shu, S., Liu, H., Song, W., Wu, J., Wang, L. & Chen, Z., 2014. Object-based spatial cluster analysis of urban landscape pattern using nighttime light satellite images: A case study of China. International Journal of Geographical Information Science, 28(11), 2328-2355.

Zhang, Q. & Seto, K.C., 2011. Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/OLS nighttime light data. Remote Sensing of Environment, 115(9), 2320-2329.