Comparison of Sentinel-2, Landsat, and Airborne Imagery for Identification of Cotton Fields for Boll Weevil Eradication

Early identification of cotton fields is important for advancing the boll weevil eradication program in Texas. Our previous work demonstrated that both submeter airborne and 10-m Sentinel-2 satellite images were effective for this purpose. In this study, Sentinel-2 and 30-m Landsat images were compared with airborne imagery for identifying cotton fields before or when cotton plants start to bloom. Over 400 pairs of airborne color and near-infrared images were acquired on 17 June 2020 over a 10 km by 11 km study area near College Station, Texas. Among all the images from Sentinel-2, Landsat 7 and Landsat 8, two cloud-free satellite scenes were identified for the area within a week of the airborne acquisition; one Sentinel-2 scene acquired on 10 June and one Landsat 7 scene acquired on 16 June 2020. The airborne images from the study area were mosaicked into one orthomosaic with a spatial resolution of 0.5 m. The airborne mosaic and the two satellite images were each classified into different crops and cover types using multiple classification techniques. Accuracy assessment were performed to compare the classifications maps with ground surveyed field maps. Preliminary results showed that both Sentinel-2 and Landsat imagery, in conjunction with the maximum likelihood classifier, was feasible and accurate for distinguishing cotton from other crops early in the season. The results and methodologies from this study provide boll weevil eradication program managers with a tool to identify cotton fields over large geographic areas during vegetative development and blooming stages.