The Facebook artificial intelligence (AI) researchers have created the world’s most detailed population density maps for Bangladesh and the Asia Pacific.
Using its machine-learning capabilities, Facebook developed the maps to help relief agencies and health organisations better assist people in need.
The social media giant said in a statement they did not use any Facebook data in the project, and the census and satellite data used contain no personally identifiable information.
The map for Bangladesh can be downloaded on Facebook’s page on Humanitarian Data Exchange.
“Facebook is working closely with key non-profit and research partners to use AI and big data to address large-scale social, health and infrastructure challenges in Asia and accelerate achievement of the sustainable development goals,” it said.
Facebook partners with Columbia University’s Center for International Earth Science Information Network or CIESIN (http://www.ciesin.org/) to ensure that this effort leverages the best available administrative data for all countries involved.
By combining these publicly and commercially available datasets with Facebook’s AI capabilities, Facebook has created population maps that are three times more detailed than any other source.
The high resolution population density maps will show an estimate of the number of people living within 30-meter grid tiles, and include the number of children under five, as well as the number of women of reproductive age, and other helpful demographics.
Those maps can improve how nonprofits do their work, how researchers learn, and how policies are developed.
Building data products from non-personal data sources like satellite imagery and census data allows Facebook to share its data science and compute power with the world while protecting privacy, bdnews24.com reported.
High-resolution satellite imagery already exists for much of the world.
However, prior to Facebook’s mapping project, it would have required countless hours for volunteers to comb through millions of square miles of pictures to identify which contained a tiny town or remote village.
The Facebook team used AI to solve that problem, efficiently crunching through data at a petabyte scale.
For example, the computer vision system examined 11z.5 billion individual images to determine whether they contained a building. The team found approximately 110 million building locations in just a few days.
“These maps showcase the power of collaboration between Facebook and top research institutions like Columbia University to combine public data sources and machine learning to empower more data-driven humanitarian projects around the globe,” said Alex Pompe, a research manager at Facebook.
