Flight Considerations and Hyperspectral Image Classifications for Dryland Vegetation Management from a Fixed-wing UAS

Unmanned Aerial Systems (UAS)-based hyperspectral remote sensing capabilities developed
by the Idaho National Lab and Boise Center Aerospace Lab were tested via demonstration
flights that explored the influence of altitude on geometric error, image mosaicking, and
dryland vegetation classification. The motivation for this study was to better understand the
challenges associated with UAS-based hyperspectral data for distinguishing native grasses
such as Sandberg bluegrass (Poa secunda) from invasives such as burr buttercup (Ranunculus
testiculatus) in a shrubland environment. The test flights successfully acquired usable
flightline data capable of supporting classifiable composite images. Unsupervised