The broader impact/commercial potential of this I-Corps project will be across multiple industries that can benefit from regular monitoring of changes on the Earth's surface. Changes such as droughts, floods, deforestation, urbanization, and grain supply (acreage and yields) fluctuations have considerable impact on businesses as well as the environment. For example, it is estimated that US lost approximately 23 billion dollars due to drought in 2012. This I-Corps project will make use of vast amounts of satellite data to provide accurate, timely and actionable insights about these changes to customers in various industries such as commodity trading, crop insurance, and precision agriculture, pasture management. Our ability to track these changes at a global scale will also improve our understanding of the impact of climate and human induced changes on various ecosystems.
This I-Corps project uses machine learning algorithms that analyze vast amounts of satellite imagery datasets to provide near real time as well as historical information about various changes on the Earth's surface. These algorithms were developed through various federal research grants which includes three NSF grants. Data products created using these algorithms have been validated to improve the state-of-the-art in several earth science applications such as forest fire mapping, surface water dynamics, palm oil plantation mapping, and crop mapping. The analytics technology is more generally applicable to other domains with similar underlying data characteristics. The commercial-use prototype will be developed with commodity traders providing expert feedback on their most meaningful use-cases.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
