Bidirectional reflectance distribution function (BRDF) effects are a persistent issue for the analysis of vegetation in airborne imaging spectroscopy data, especially when mosaicking results from adjacent flightlines. With the advent of large airborne imaging efforts from NASA and the US National Ecological Observatory Network (NEON), there is increasing need for methods that are both flexible and automatable across numerous images with diverse land cover. FlexBRDF corrects for BRDF effects in groups of flightlines, with key user-selectable features including kernel selection, land cover stratification (we employ NDVI), and use of a reference solar zenith angle (SZA). We demonstrate FlexBRDF using a series of nine long (150-400 km) AVIRIS-Classic flightlines collected on 22 May 2013 over Southern California, where rough terrain, diverse land cover, and a wide range of solar illumination yield significant BRDF effects, and then test the approach on additional AVIRIS-Classic data from California, AVIRIS-Next Generation data from the Arctic and India, and NEON imagery from Wisconsin. Based on comparisons of overlap areas between adjacent flightlines, correction algorithms built from multiple flightlines concurrently performed better than corrections built for single images (RMSE improved up to 2.3% and mean absolute deviation 2.5%). Standardization to a common SZA among a group of flightlines also improved performance. While BRDF corrections tailored to individual sites may be preferred for local studies, FlexBRDF is compatible with bulk processing of large datasets covering diverse land cover needed for calibration/validation of forthcoming spaceborne imaging spectroscopy missions.