Around the world, imaging spectroscopy (hyperspectral imaging) has been successfully applied to mapping surface minerals over small areas. In this paper, we examine one challenge to reliably mapping surface mineral composition over large areas: the impacts of atmospheric artefacts in reflectance spectra on mineral identification. To examine these impacts, we use a set of Airborne Visible and Infrared Imaging Spectrometer-Classic (AVIRISc) data collected over ~30,000 sq. km of southern California (SoCal) in 2018. The AVIRISc2018 SoCal reflectance data showed residual atmospheric contamination in wavelength regions at the edges of strong water vapor absorption features: 1.44-1.5 µm, 1.75-1.8 µm, and 2.35-2.5 µm. These three regions of atmospheric residuals affect identification and discrimination of mineral absorption features, especially when mineral abundances are low and spectral features are weak. Of these three regions, improving atmospheric correction of imaging spectrometer data in the 2.35-2.5 µm region will result in the most enhancement in mineral identification, discrimination, and mapping. An additional region near 2.2 µm affects phyllosilicate mineral identification. The cause of the distorted reflectance in this region is still being investigated.