Cotton growth is indeterminate, and it is therefore critical to terminate after the bolls reach a certain level of maturity and fiber reaches a certain level of quality. Failure to obtain such matrices results in discounted prices at sales points being offered to the producers. Producers typically scout their cotton fields to identify the number of cotton boll openings and maturity levels from a few random locations within the entire field. Importantly, these estimates are based on few locations within the entire field and therefore tend to be inaccurately representing boll open or maturity status across entire field when microclimate and soil conditions can significantly vary to impact physiological parameters. Advent of remote sensing technology and data science can be useful in autonomously assessing spatial variations in cotton boll status to minimize losses pertaining to untimed defoliation and harvest. This article describes a UAV-based method for mapping visible lint exposure (% open bolls) using multispectral imagery. The method provides: (1) field-scale maps at 33ft x 33ft resolution with aggregated % open bolls and (2) boll opening trends over time to aid operational decision-making.