Water in oil (WO) and oil in water (OW) emulsions from marine oil spills have different physical properties, volume concentrations, and spectral characteristics. Identification and quantification of these different types of oil emulsions are important for oil spill response and post-spill assessment. While the spectral characteristics of WO and OW emulsions have been presented in previous studies including Part I of this series, their application to airborne and satellite imagery is further demonstrated here. Using AVIRIS and Landsat observations, we firstly show that false color Red-Green-Blue composite images from Landsat-like sensors (R: 1677 nm, G: 839 nm, B: 660 nm) are effective in differentiating WO and OW emulsions as they show reddish and greenish colors, respectively, in such composite images. This is a consequence of the relative difference in the reflectance of WO and OW emulsions at 1677 and 839 nm, which is not impacted by the presence of medium-strength sunglint or the surface heterogeneity within medium-resolution pixels (e.g., 30 m). Based on image statistics, a decision tree method is proposed to classify oil type, and oil quantification is further attempted, with results partially validated through spectral analysis and spatial coherence test. The numerical mixing experiments using AVIRIS pixels further indicate that the SWIR bands might be used to develop linear unmixing models in the future once the coarse-resolution oiled pixels are first classified to WO and OW types, and 1295 nm is the optimal wavelength to perform spectral unmixing of mixed coarse-resolution pixels.