Skewness-Based Classification and Environmental Indication of Spectral Probability Distribution of Global Closed Connected Waters

Abstract

Optical types of waters are important indicators of water quality and watershed environment. In this study, we proposed a novel classification approach that is based on water’s spectral probability distribution (SPD) in satellite images. Using the Landsat-8 images, we processed 690 global water bodies and their SPDs were then classified into seven types in terms of their skewness (SK). We analyzed the statistical features of these water types and their relationships with some environmental factors. The results show that if water bodies are clearer, simpler, more in their raw status, and having less interaction with humans, then their SPD SK is more positive, while if they are more complex, turbid, and highly interacted with human activities, then their SPD SK is more negative. Our study demonstrates that SPD is a good optical parameter and hence with more potential to indicate the quality and environmental properties of water bodies.