The document describes a study that used unmanned aerial system (UAS) thermal and RGB imagery to map soil moisture (SM) levels. Researchers took field observations of SM and then used a k-means algorithm to classify the land use, apparent thermal inertia (ATI) maps to estimate SM, and a green leaf index to identify vegetation. They generated SM maps from the UAS data and compared estimated SM values to observed field measurements, finding a high correlation between the two.