According to the analysis of application to CALIOP, an acceptable classification result of clean marine, desert dust, clean continental, and polluted dust can be achieved, and the self-validation accuracies of desert dust and clean continental is over 80%, but the crosstalk between polluted continental and biomass burning is too serious to be distinguished. The main reason is that the two aerosol models (polluted continental and biomass burning) used in CALIOP have similar compositions.34 Moreover, the lidar ratio assigned to these two kinds of aerosols are similar, 70 sr at 532 nm and 40 sr at 1064 nm for smoke, and 70 sr at 532 nm and 30 sr at 1064 nm for polluted continental.31 Thus, the overlapping area of polluted continental and smoke is very large in the optical features space. On the other hand, the CALIOP retrieval algorithm uses a decision tree, which takes into account not only the measured optical feature but also aerosol location, height, and surface type to classify aerosol layers into six types. Therefore, the serious crosstalk between polluted continental and smoke is not a surprise. Since polluted continental and biomass burning almost overlap in the current optical feature space and the separation of them cannot be realized only through these optical features, we combine them under the label “urban” to perform the classification processing. That is, we classify aerosol samples into five catalogs (clean marine, desert dust, combined urban, clean continental, and polluted dust) according to CALIOP data. The results of strict self-validation accuracies of classification into five catalogs with a rejection decision after an optimized decision threshold is adopted are shown in Fig. 11. As one can see, the reidentification results are quite acceptable when aerosols are classified into five categories.