The proposed work will develop solutions for utilizing multi-agent unmanned aircraft systems (UAS) for monitoring, reporting, and verification of SOC and SWC in agricultural settings. To achieve this we will:1. Develop novel UAS systems and sensors for providing initial estimates of SOC/SWC.2. Design novel UAS controllers, and mechanisms capable of soil extraction, and insertion of SWC probes.3. Develop machine learning algorithms to predict key soil properties from sensed data; and predict carbon content from atmospheric readings from the UASs.4. Build smart sampling algorithms to task UASs with optimal locations and sampling strategies to reduce uncertainty in SOC/SWC estimates.5. Expand our existing smart sampling software into a package for easy use with ESRI software commonly used by USDA.6. Regularly evaluate the above objectives at local representative facilities in collaboration with our science experts.