Scientists taking to the sky to track global poverty
Posted August 30, 2016
A group of Stanford researchers is using satellite imagery and artificial intelligence to track poverty reduction efforts around the world.
By combining those satellite images with machine learning — the ability for machines to learn things without being programmed to — scientists hope to collect data that could help the U.N. achieve its 2030 goal to eradicate poverty in a cheap and efficient manner.
Collecting that data in the past has been difficult for a number of reasons.
"Most countries don't collect much data, and scaling up traditional household survey-based data collection efforts would be expensive," Stanford researchers explain in a short video explaining the project.
But the researchers suggest that by using "less conventional data sources," such as algorithms and satellite imagery, they can put together an "accurate, inexpensive and scalable method for estimating consumption expenditure and asset wealth."
By combining high-resolution satellite images of different countries taken during the day and at night, researchers believe they can learn more about communities living in poverty and develop plans to specifically address each of their needs.
Those images are also helpful for finding features that are usually associated with economically developed communities, like roads, farms and cities.
Those features are then used to predict how wealthy or poor a particular area is, and from there, researchers and advocacy groups can decide how to best serve that community. So far, the team has looked at five countries in Africa — Nigeria, Uganda, Tanzania, Malawi and Rwanda.
"We find that our method does a good job predicting the distribution of poverty," the researchers said in the video. "Since it's cheap and scalable, it could be used to map poverty around the world, helping aid organizations to distribute funds more efficiently and policymakers to enact and evaluate policies more effectively."
The United Nations estimates that 836 million people around the world live in extreme poverty and that the highest poverty rates tend to be in "small, fragile and conflict-affected countries."
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