More than 700 imaging satellites are orbiting the earth, and every day they beam vast oceans of information including data that reflects climate change. However, while the geospatial data could help researchers and policymakers address critical challenges, only those with considerable wealth and expertise can access it. A team based at UC Berkeley has devised a machine learning system to tap the problem-solving potential of satellite imaging, using low-cost, easy-to-use technology that could bring access and analytical power to researchers and governments worldwide.
Researchers have been guided by a common interest in creating an open access tool that democratizes the power of technology, making it usable even by communities and countries that lack resources and advanced technical skill. The system that emerged from the Berkeley-based research is called MOSAIKS, short for Multi-Task Observation using Satellite Imagery & Kitchen Sinks. It ultimately could have the power to analyze hundreds of variables drawn from satellite data from soil and water conditions to housing, health and poverty at a global scale.
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