Advancing Global Food Security and SDGs with Machine Learning and Earth Observations
Also on Zoom- https://umd.zoom.us/j/96718034173?pwd=clNJRks5SzNUcGVxYmxkcVJGNDB4dz09
Satellite Earth observation (EO) data is rapidly gaining interest in the AI community due to the massive datasets involved as well as the opportunities for using AI and EO data to address urgent challenges related to climate change, the environment, agriculture and food security, and humanitarian needs. However there are currently many challenges for developing AI systems that use EO data for practical applications, namely, there are limited public labeled datasets, a lack of harmonization across labels and source data, and existing algorithms do not account for geographic context. In this talk, I'll present some of the approaches we are developing to address these challenges to create AI+EO systems that can be integrated into real-world applications for advancing global food security and other sustainable development goals.