Mapping Agricultural Fields of the World with RasterFlow

Agriculture depends on timely, reliable insight into what’s happening on the ground: what’s being planted, what’s being harvested, and how fields evolve over time. The Fields of The World (FTW) project was created to support exactly this mission, by building a fully open ecosystem of labeled data, software, standards and models to create a reliable global map of agricultural field boundaries using AI and Earth Observation (EO) data. Contributing to this effort, Wherobots processed petabytes of satellite imagery to create seamless global imagery mosaics and produce global maps at 10 meter resolution of agricultural boundaries. In this presentation we'll cover how Wherobots RasterFlow works to scale models like Fields of the World and the applications it unlocks. Ryan Avery is a Senior ML Engineer at Wherobots, where he works on batch processing and inference systems. His work on RasterFlow enables transforming optical, radar, and high resolution satellite and aerial imagery into meaningful insights using computer vision and earth observation models. He's passionate about making environmental monitoring accurate, efficient, and within reach for organizations looking to protect and understand Earth. * Wherobots - https://wherobots.com * Connect with Ryan on LinkedIn - https://www.linkedin.com/in/ryan-avery-75b165a8/ #FiftyOne #Voxel51 #ComputerVision