Jan. 7 (UPI) — To more strategically allocate resources, set agenda priorities and track the progress of economic initiatives in the developing world, the United Nations is turning to satellite imagery.
Researchers at Aarhus University in Denmark have developed methods for quantifying economic living conditions at the household level using high resolution satellite images.
“Based on high-resolution satellite images, we can very precisely assess the status of poverty at household level in rural areas in developing countries,” Jens-Christian Svenning, a professor and researcher at Aarhus, said in a news release.
Using satellite images of portions of rural Kenya as a proof-of-concept test, scientists used several factors to estimate economic living conditions on local farms. Researchers identified the size of buildings, the size of uncultivated fields and the length of the growing season.
When they compared their analysis with on-the-ground data, scientists determined satellite image analysis can account for 62 percent of the variation in local economic conditions. The research team detailed their work in a study published Monday in the journal Proceedings of the National Academy of Science.
Though not as accurate as the data collected through household surveys and individual interviews, researchers think satellite image analysis can serve as a cost-effective supplement when assessing socio-economic development across the developing world.
“The use of satellite images makes it much, much cheaper to keep track of how far we are in reaching the United Nations’ goals for sustainable development,” said Gary R. Watmough, who now works at the University of Edinburgh. “If conventional assessments of the households’ economic conditions were used, the cost would be more than $250 billion.”
Researchers think that by refining their analysis of satellite data and combining it with on-the-ground observations, they can more accurately track poverty and economic growth at the local level.
“The method that we have developed is designed to analyze the satellite images in a way that takes into account that people have access to and use different resources in the landscape at different levels,” Svenning said. “Some use the area just around their house, while others use the common areas of a village. When we use space data with a socio-ecological insight, we capture the financial status, and in this way, also the development in an area much better than we have previously been able to.”