Innovative AI and Satellite Technology Tackles Illegal Manure Spreading in Wisconsin

In an era of rapid technological advancements, artificial intelligence (AI) and satellite imagery are now being employed to address a pressing environmental concern in Wisconsin: illegal manure spreading on snow-covered fields. This groundbreaking approach, developed by researchers at Stanford University’s Regulation, Evaluation, and Governance Lab, promises a new way to monitor agricultural practices that pose risks to water quality, public health, and the environment.During the winter months, when the ground is frozen or covered in snow for up to 140 days, the risk of manure runoff increases significantly. This runoff can lead to water contamination, pathogen spread, algae blooms, and fish deaths. The state of Wisconsin has set strict regulations on manure spreading during this period, typically prohibiting the practice in February and March, unless exemptions are obtained.The Stanford team’s model utilizes near-daily satellite images from the Planet satellite and data company, which captures Earth’s entire landmass using over 150 orbiters. These images allow the model to identify instances of manure spreading against the stark backdrop of snow-covered fields. In a recent study, the model predicted between 700 to 1,200 instances of potentially prohibited manure spreading, shedding light on the challenges of enforcement and monitoring by state authorities.Despite the promise of this technology, challenges remain in achieving high accuracy due to the limited winter imagery available for training the model and difficulties in distinguishing manure spreading from other winter activities. The Department of Natural Resources (DNR) has begun integrating some of these findings into their compliance and enforcement efforts, although the complexity and time-intensive nature of verifying satellite detections have prompted discussions about the most effective use of such technology.