UNIVERSITY PARK, Pa. — On Saturday, Feb. 4, Tamma Carleton, assistant professor of economics at the University of California, Santa Barbara, presented the third lecture in the 29th Ashtekar Frontiers of Science lecture series. This year’s lecture series focuses on how researchers are using and sharing “big data” to address longstanding scientific questions and make important societal contributions. The series is titled “Exploring Open Science and Big Data.”
In her talk, titled “Combining Satellite Imagery with Machine Learning to Address Global Challenges,” Carleton discussed how the combination of satellite imagery and machine learning has begun to transform our ability to map, monitor, and influence many global challenges, ranging from deforestation to poverty eradication to illicit activity. This emerging research area is data intensive and computationally demanding, making participation difficult for many researchers, governments, and nongovernmental organizations.
“The idea is that with machine learning we are basically training computers to do the same thing that our human eye is doing,” Carleton said. “There potentially are things that computers can see in the images that we are not going to be able to predict.”
Carleton is therefore developing tools and methods that use machine learning to extract information from satellite images to help fill the large data gaps that exist for basic economic, social, and environmental indicators, which are highly unequally distributed across the world.
“At home in the United States, we have the American community survey, and we are surveying our populations at least every year,” said Carleton. “Key regions of the world where some of our economic challenges are the largest are places where we're not seeing surveys for over 25 years.”
According to Carleton, in areas of the world where these surveys are scarce, we may be able to use satellite images and translate the imagery to information that can help us solve social, environmental and economic challenges. There are over 700 earth observation satellites that produce over 100 TB of data every single day.
“This massive amount of information that we're collecting from space can help us fill these data gaps and sort of level the playing field by providing a globally comprehensive — at least somewhat and we can talk about a bias — and in some ways objective picture of what's happening across the entire world.”
She then focused on new algorithmic innovations that make this field more accessible to a wider array of users with the aim to democratize access to this powerful new source of global information.