Many agronomic decisions in soybean production systems revolve around crop maturity. The primary objective of this research was to evaluate the ability of UAS to determine when soybeans have reached maturity stage sufficient for harvest aid application. A producer typically applies harvest aid chemicals when he or she perceives the crop has reached a critical level of maturity (R6.5) based on a subjective assessment. A convention is to apply harvest aids when 65% of soybean pods reach a mature brown color. The use of UAS allows producers to have whole field coverage and a more objective way of determining when soybeans are mature enough to tolerate late-season harvest aid application without risking yield loss. At the small plot scale, data collection for this project consisted of UAS missions with a multi-rotor aircraft carrying a multi-spectral payload that collected reflectance in five bands (blue, green, red, near infrared, and red edge). UAS missions coincided with in-situ assessment of soybean maturity stage within research plots. Six UAS missions were conducted during the critical timing window (R5.5 to R8), approximately every 4 days. Image processing was conducted using the cloud-based application provided by the payload manufacturer, which returned a radiometrically-corrected orthomosiac image file. From the individual bands, both normalized difference vegetation index (NDVI) and variable atmospherically resistant index (VARI) were calculated using GIS software. Zonal statistics were utilized to obtain average NDVI and VARI values for each small plot for each collection date. Intuitively, NDVI and VARI decrease in tandem with maturity progression of soybean, as plants senesce and green matter dries out, withers, and turns brown. A significant high correlation was seen between decreased index values and increased maturity stage (ρ = -0.82 and -0.79, for NDVI and VARI, respectively). At this time, the study has been scaled up to production fields. A successful outcome would mean a new application for UAS using tools and data products available now at a reasonable cost, making the research outcomes immediately usable by soybean producers.