Remote sensing of night lights: A review and an outlook for the future
Introduction
Human society has modified the Earth to such an extent, that the present geological era has been termed as the Anthropocene (Crutzen, 2002). Monitoring human activity from space has largely been directed at mapping land cover and land use changes, such as deforestation (Hansen et al., 2013). Remote sensing of artificial lights, on the other hand, provides a direct signature of human activity. Global images of the Earth at night are now iconic, thanks to NASA media releases such as the “Bright Lights, Big City” (published in Oct 23rd, 2000, https://earthobservatory.nasa.gov/Features/Lights ) or the “Earth at Night” (published in April 12th, 2017, https://earthobservatory.nasa.gov/Features/NightLights ) and other communication channels (Pritchard, 2017).
The availability of artificial lights is often associated with wealth and a modern society (Hölker et al., 2010a; Green et al., 2015). Brighter lights are strongly associated with increased security in the public consciousness, despite little evidence of a causal link. As a result, total installed lighting increased rapidly during the past centuries (Fouquet and Pearson, 2006), and has continued to increase in most countries during recent years (Kyba et al., 2017). An example of recent lighting changes is shown in Fig. 1. Nightscapes change when objects or areas are illuminated for the first time, as in new roads or neighbourhoods, or when lighting technologies change (Fig. 1). As a result, economic development goes in tandem with lighting.
Artificial lights at night can also provide insights on negative impacts, such as disasters (Molthan and Jedlovec, 2013), and armed conflict (Román and Stokes, 2015). The importance of monitoring the Earth at night is also demonstrated by the growing recognition of artificial light as a pollutant (Navara and Nelson, 2007; Hölker et al., 2010b), the development of new lighting sources (such as LEDs, which can increase ecological light pollution; Pawson and Bader, 2014), and the continuing growth in extent and radiance of artificially lit areas (Kyba et al., 2017). Light pollution can be defined as “the alteration of natural light levels in the night environment produced by the introduction of artificial light” (Falchi et al., 2011). Artificial light can alter species abundance or behavior due to changes in their circadian rhythms or due to their attraction to or repulsion from light (ecological light pollution; Longcore and Rich, 2004; Rich and Longcore, 2006), can decrease our ability to observe stars at night (astronomical light pollution), and also leads to negative health impacts to humans through the suppression of melatonin production and insomnia (Hölker et al., 2010b; Falchi et al., 2011; Lunn et al., 2017).
With the development of new space borne, airborne and ground sensors for quantifying light at night, new research opportunities are emerging (Kyba et al., 2015a; Hänel et al., 2018). The first comprehensive review on remote sensing of night lights was published by Doll (2008). Since that time, a variety of new sensors have become available (Fig. 2; Table 1). More recent reviews on remote sensing of night lights have either focused solely on applications of the DMSP/OLS sensor (Elvidge et al., 2009c; Huang et al., 2014; Li and Zhou, 2017), on multi-temporal applications using DMSP/OLS and VIIRS/DNB (Bennett and Smith, 2017), on the various applications of night-time imagery (Li et al., 2016) and on the community of researchers active in this field (Hu et al., 2017). Since the recent review of Zhang et al. (2015b), new sensors, algorithms, and applications have emerged (Zhao et al., 2019). In this paper we therefore aim to provide a comprehensive review on the field of remote sensing of night lights, focusing on the visible spectral range, which is mostly related to artificial lights used by people to light the night so as to extend human activity hours. In our review we cover space borne, airborne, and ground based observations (recently reviewed in Hänel et al., 2018). We cover the historical development of this research area, the available sensors, the current state of the art algorithms for routine data processing, key applications, the differences to daytime remote sensing, upcoming space-based night lights missions, and future research challenges.
Section snippets
Earliest observations of night lights
Historically, technological developments in the energy industry (such as the transition from candles to gas, and later on to kerosene and then to electricity) have led over the past centuries to a gradual decrease in the price of lighting services, and were associated with increases in lighting efficiency and in the consumption of light per capita (Nordhaus, 1996; Fouquet and Pearson, 2006). The foundation of the Edison Electric Light Company can mark the modern era of lighting, and since the
Applications of remote sensing of night lights
In this section, we aim to provide a brief overview of some of the most common applications of night lights data made using the existing and historical sensors. The aim is to demonstrate the breadth of existing studies, and to refer the reader to historical, key, and review papers about each topic. Readers should understand that for each topic, a considerably larger base of scholarship exists, and that not all applications of night lights are reviewed here. For example, we do not review studies
Challenges of night light sensing and the differences between day vs. night sensing in the visible band
There are many challenges associated with observations of visible band light at night, and the remote sensing of socioeconomic parameters on the basis of such data. The most obvious of these are the dramatically reduced radiance and extreme dynamic range of night scenes in comparison to daytime remote sensing. Consider the scene in Fig. 14. During daytime, the light source is the sun, shining from above the atmosphere. In a cloud free scene, rooftops, treetops, and open grassland or water areas
Conclusions
Images of artificial lights at night directly observe human activity from space, and therefore enable a number of remote sensing applications either unique to night light sensing (e.g. monitoring illegal fishing, remotely sensing lighting technologies) or strongly complementing other types of remote sensing (e.g. evaluating the impacts of armed conflicts and disasters and the recovery from them, quantifying temporary and seasonal changes in population, studying urban change). The field of
Acknowledgements
CCMK acknowledges funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 689443 via project GEOEssential, and funding from the Helmholtz Association Initiative and Networking Fund under grant ERC-RA-0031. Some aspects of this manuscript were based upon work from COST Action ES1204 LoNNe (Loss of the Night Network), supported by COST (European Cooperation in Science and Technology). ASdM acknowledges funding from the EMISS@N project (NERC grant
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