Using Advanced Land Imager (ALI) and Landsat Thematic Mapper (TM) for the Detection of the Invasive Shrub Lonicera maackii in Southwestern Ohio Forests

Abstract

We tested how accurately image data from the Advanced Land Imager (ALI) sensor vs. the Landsat Thematic Mapper (TM) predict the land cover of Lonicera maackii in the forest understory, taking advantage of this invasive shrub's extended leaf retention in the fall when the canopy is leafless. Percent cover of L. maackii in 20 woodlots in southwestern Ohio was regressed on values for spectral vegetation indices (SVIs) derived for each image. The land cover of L. maackii was best explained by the Simple Ratio (SR) using TM data (R ² = 0.537). The regression results for SVIs from TM vs. ALI suggest that the ALI image was acquired too late in the fall to accurately detect this invasive shrub.