Researchers at the University at Buffalo say they have developed a new way to create timely and very detailed poverty maps by using computational tools such as cellphone records, data from satellites, and geographic information systems.
Their research focused on the African country of Senegal, which has a high poverty rate.
The researchers examined a dataset consisting of 11 billion calls and texts from more than 9 million Senegalese mobile phone users. The data was anonymized, and captured how, when, where, and with whom people communicated.
The researchers also used a second dataset consisting of satellite imagery, geographic information systems data, and weather station data. They say this dataset offers insight into food security, economic activity, and accessibility to services and other indicators of poverty.
The two datasets were combined using a machine learning-based framework, which was used to create maps detailing the poverty levels of 552 communities in Senegal.
From University at Buffalo News
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