Abstract
A compact light detection and ranging (LiDAR) system is used for the purpose of aerosols profile measurements
by identifying the aerosol scattering ratio as function of the altitude. These color plots can be treated as images
with high intensities referring to high scattering ratios and low intensities referring to low scattering ratios. In this
paper, we explore the clustering of these plots into homogeneous regions via unsupervised clustering techniques
such as fuzzy techniques and evaluate their performance on this type of data. We introduce a new clustering
technique to work efficiently on this type of images and compare its results against the regular techniques. By
capturing different aerosols profiles at different times, we are able to describe the aerosol existence structure in
the area of our interest.