Satellites might be able to help stamp out global poverty by indicating where help is needed most, according to a team of U.S. researchers.

The images from satellites could help governments and charities trying to fight poverty but lacking precise, reliable information on where poor people are living and what they need, said the researchers, based at Stanford University in California.

Eradicating extreme poverty, measured as people living on less than $1.25 U.S. a day, by 2030 is among the sustainable development goals that U.N. member states adopted in 2015.

The Stanford team used a computer algorithm to create a self-updating world map that recognizes signs of poverty through a process called machine learning, a type of artificial intelligence, said Marshall Burke, assistant professor in Stanford’s Department of Earth System Science. Results of the two-year research effort have been published in the journal Science.

“The computer learns to find a lot of things that we think are correlated to poverty, like roads, urban areas, farmlands and waterways,” Burke said.

Burke said the team plans to create a worldwide poverty map that would be publicly available online.

“We hope our data will be directly useful by governments around the world … to more effectively target their programs,” Burke said.

Researchers are increasingly looking for different ways to use satellites to fight today’s problems, including, for example, spotting illegal fishing fleets in the ocean and predicting natural disasters.