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Gaining a Global View of Poverty By Using Satellites

The study of night-time radiance has been an effective means of mapping global issues like economic growth, poverty and inequality for nearly three decades
The study of night-time radiance has been an effective means of mapping global issues like economic growth, poverty and inequality for nearly three decades
  • Most unlit settled land is located in Africa and Asia
  • Developing communities must be located before they can be supplied with aid and infrastructure
  • Light emission maps are an accurate way to detect underdeveloped areas

In a modern, technologically-savvy and overall affluent world it seems unthinkable that so many of the global population live without access to some of the most basic resources. Information from international organisations such as the World Bank and International Energy Agency (IEA) indicates that although the global poverty rate has halved since 2000, nearly one billion people still live without access to reliable and affordable electricity.

And, according to new research from a leading economist at Vienna University of Economics and Business (WU), nearly a fifth of “settled” land around the world has no access to electric lighting.

And how do they know? Well, they mapped it from space.

The study, undertaken by Jesús Crespo Cuaresma, Professor of Macroeconomics at WU, and led by the International Institute for Applied Systems Analysis (IIASA) used light emission maps taken from satellite imagery and discovered most unlit settled land is in either Africa (39 percent) or Asia (23 percent).

According to Cuaresma and his co-researchers, the study of night-time radiance has been an effective means of mapping global issues like economic growth, poverty and inequality for nearly three decades. This is because many developing countries have only rudimentary systems for gathering economic statistics such as household income and consumption – and what statistics they do provide often contain regional blind spots. Night-time radiance studies are a good way of plugging those holes in information about an area’s economic development, Cuaresma says, as the extent to which an area is brightly lit at night (or not) provides an indication of how abundant infrastructure is in the region.

Knowing the precise locations of these unlit, potentially impoverished communities is essential if they are to be provided with the vital aid and infrastructure they need to improve their circumstances. Especially, Cuaresma says, after recent studies have revealed that financial donations sent to developing countries typically flow to the most affluent areas.

However, the researchers believe these past studies have run into difficulties. Their findings indicate that past attempts to link nocturnal brightness with economic predictors such as GDP work well in nations or areas with significant lighting, but are problematic when people try to apply them to impoverished areas with little or no light.

“Whereas previous work has focused more on the relationship between lit areas and economic development, we found that it actually also works the other way around and that unlit areas are a good indicator of poverty. By identifying those unlit areas, we can target interventions for poverty alleviation,” says IIASA Strategic Initiatives Programme Director, Steffen Fritz.

So how is their study different? According to the report authors, new advancements in monitoring technology have helped make attempts to detect unlit settlements more accurate.

The VIIRS DNB satellite sensor was launched in 2012, capturing infrared pictures of the entire Earth every night, and its improved accuracy over its predecessor (the DMSP) allows for the analysis of night-time radiance at the neighbourhood scale.

In addition to this, developments in the World Settlement Footprint (WSF), the most detailed worldwide inventory of human settlements that has ever existed, mean it is possible to estimate the amount of global infrastructure that exists with no detectable light emissions.

The result is that Cuaresma and his colleagues successfully mapped data from unlit areas to estimate the economic development of around 2.4 million households across 49 countries in Africa, Asia, and the Americas, with an accuracy of 87 percent.

“The novel methods we are developing in this study will prove important for measuring poverty at a granular level. They can be used to monitor poverty dynamics and design effective strategies to improve the income levels of the poorest households in developing countries,” says Cuaresma.

The researchers also found that government agencies tend to prioritise increasing access to electricity in urban rather than rural areas. However, targeting regions outside the scope of large towns and cities has a more significant impact on levels of household income, health and education.

The United Nations’ Sustainable Development Goals (SDG) include “access to affordable, reliable, sustainable and modern energy for all”, but the authors of this study believe governments and industries are not moving swiftly enough to keep pace with expected population growth.

Projections for sub-Saharan Africa alone indicate that 300 million people will be living in extreme poverty by 2030, and the impacts of the Covid pandemic could add up to an additional 115 million people on top, the researchers say. And with studies also showing society overall cares less about the environment as we get older, on top of other concerns such as a spiralling cost of living, the time for governments to act to identify communities in need is surely now.

Cuaresma and his co-authors believe that studies like theirs will be useful in tracking the progression of developing countries as they improve access to infrastructure and developed nations as they reduce their light-energy consumption.

The study already found noticeable patches of darkness in photo-imagery of developed countries, particularly in Europe. The researchers believe this could be due to several reasons, including conscientious attempts to conserve energy costs, or because the time at which the satellite passed overhead was gone midnight.

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