Spatiotemporal patterns of outdoor artificial nighttime lights exposure in the Republic of Korea between 1995 and 2010.

Author:Kim, Minho
 
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Introduction

Since Thomas Edison invented the electric light bulb in 1879, artificial lighting has been used to ensure personal safety and security through the associated reductions in crimes (Clarke 2008; Welsh and Farrington 2008) and to extend the length of daily work and recreational activities (Doll, Muller, and Morley 2006; Chepesiuk 2009). In the modem world, artificial nighttime lighting is emitted from various sources including streetlights, buildings, bridges, towers, sporting facilities, and airports (Holker et al. 2010). Bright light at night (LAN) dramatically increases in developed countries with high population densities (Reiter et al. 2007), and it could be an environmental health problem in terms of light pollution (Barducci et al. 2003; Berg 2009). Light pollution can be defined as ovemsed and unwanted artificial lights that alter the ambient light levels of the night environment (Cinzano, Falchi, and Elvidge 2001; Claudio 2009; Gallaway, Olsen, and Mitchell 2010).

Outdoor artificial LAN as an environmental pollution has been realized by astronomy communities because bright sky glow makes ground-based observations of stars and other celestial bodies more difficult (Riegel 1973). Because of this issue, the International Dark-Sky Association, a nonprofit organization, was established in 1988 to preserve and protect the nighttime environment as well as the heritage of dark skies through environmentally responsible outdoor lighting (IDA 2012). Outdoor artificial LAN also has negative effects on wildlife ecosystems. According to a recent review paper (Longcore and Rich 2004), excessive nighttime lighting have been found to alter the ecological functions of wildlife such as orientation, foraging, reproduction, migration, and communication.

In addition to the astronomical and ecological aspects, light pollution has a potential association with human health by disturbing normal biological nighttime functions such as the secretion of melatonin as well as the rise of cortisol levels, which impact the lowering of core body temperature for healthy sleep (Spivey 2010). Melatonin is a hormone that regulates a balanced physiological condition in humans (Pauley 2004). It secretes only during darkness and is suppressed with optic exposure to bright light (Pauley 2004; Spivey 2010). Endogenous melatonin in humans is known to influence biological functions or processes such as sleep, mood, cancer, immune response, and aging (Brzezinski 1997).

Light pollution has been hypothesized to disrupt human circadian rhythms that would suppress nocturnal melatonin production and increase the rates of certain cancers particularly in developed countries (Kerenyi, Pandula, and Feuer 1990; Stevens and Rea 2001; Schemhammer and Schulmeister 2004; Stevens 2005; Reiter et al. 2009; Stevens 2009a). In 2009, the American Medical Association recognized light pollution as a public health issue of concern and adopted a resolution to reduce exposures caused by outdoor artificial lighting (Spivey 2010).

Outdoor artificial light pollution at nights would be an environmental issue with negative health outcomes mainly in developed countries, but it might also be a concern in developing countries with high population densities. Nevertheless, there were few studies reporting historical changes in the degree of light pollution incorporated with population-based analysis for such nations. Taking this into account, we present the spatiotemporal changes of outdoor LAN exposure across the Republic of Korea (ROK), a developing country in Asia, between 1995 and 2010. In addition, we provide the demographic characteristics of population, focusing on gender and age, which would be affected by nighttime light exposure for each period.

Materials and methods

Data

Ground-based observation provides high accuracy for assessing the degree of light pollution, but this approach cannot cover large spatial areas at regional, continental, and global scales (Barducci et al. 2003). As an alternative, a satellite-based approach avoids the spatial limitations of ground-based observation. Currently, the US Air Force Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) is the only sensor that collects global outdoor nighttime lights data. The National Geophysical Data Center (NGDC) of the US National Oceanic and Atmospheric Administration (NOAA) provides time-series DMSP OLS images (Elvidge et al. 2007). DMSP OLS imagery has been used in a wide variety of study areas such as urbanization (Lo 2002), population and socioeconomic estimation (Welch 1980; Sutton et al. 2001; Doll, Muller, and Morley 2006; Gallaway, Olsen, and Mitchell 2010), and human health (Kloog et al. 2008, 2010; Bauer et al. 2013).

The global coverage data of annual-average DMPS OLS stable lights are available from 1992. The DMSP OLS imagery represents outdoor artificial nighttime illuminations emitted from cities, towns, and other sites with persistent lighting. It records the levels of light emission in digital numbers (DN) that range from 1 to 63 (darkest to brightest). The DN values of DMSP OLS imagery were employed as a spatial proxy to nighttime light pollution in this research, that is, outdoor LAN level.

In the ROK, the Population and Housing Census (PHC) is conducted every fifth year as a nationwide complete enumeration survey to help national governments establish socioeconomic development plans and private sectors formulate management plans. The PHC survey data include total population and demographic information such as gender and age over the smallest administration unit, called Eup-Myeon-Dong (EMD). Based on the PHC data, we identified the total population of 44,553,700 and the EMD units of 3750 in 1995. Meanwhile, the total population of 47,990,700 and the EMD units of 3470 were included in the 2010 PHC survey data. The two EMD-level census data were incorporated in this research to characterize the demographic patterns of exposed populations with a major focus on gender and age.

Data collection and analysis

Time-series DMSP OLS nighttime imageries have been acquired from six satellites of F-10, F-12, F-14, F-15, F-16, and F-l 8 (Elvidge et al. 2014), and the annual stable lights of human settlements have been derived from one of the satellites for a target year. DMSP OLS scans the nighttime surface of the Earth with the ground footprint of 5 x 5 km at nadir and the quantization of 6 bit (Elvidge et al. 2013). The annual stable light imagery is produced with all the available DMSP OLS composites for a target year.

Unfortunately, DMSP OLS does not have an onboard intercalibration system, which helps the direct comparison of the DNs of light emission from one year to another. However, Elvidge et al. (2014) provided intercalibration coefficients from a second-order regression model for individual DMSP OLS images from 1992 to 2012 in recent years.

We downloaded two DMPS OLS images, that is, one for 1995 and the other for 2010, from NOAA NGDC website (http://ngdc.noaa.gov/eog/dmsp/downloadV4composites...

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