Visual interpretation of satellite imagery for hotspot dust sources identification

Abstract

Identifying dust sources using remotely sensed satellite imagery is one of the most effective ways of studying dust emission and dynamics. Even though complex algorithms and sophisticated models that take advantages of different data sources have been developed, human knowledge and experiences are key factors in the accurate dust sources identification. Visual interpretation of satellite imagery (VISI) is essentially influenced by interpreters' subjective judgment. Meanwhile, the capabilities of VISI are not comprehensively explained in the literature. Therefore, this study performed an experimental VISI to identify hotspot dust sources (HDS) in the Tigris and Euphrates basin (TEB) involves a variety of active sources of global dust emission. In this regard, the characteristics of various satellite sensors including spatial, temporal, and spectral resolutions, swath width, free availability, and length of archive time were explored. Accordingly, the MODIS-Terra/Aqua was qualified as the best sensor for HDS identification. By visual interpretation of 27,239 MODIS images, a total of 10,422 HDSs was identified in TEB in the 2000–2021 period. The research findings revealed that the interpreter's proficiency in using specific VISI keys, knowledgeability about the geoenvironment, and familiarity with the study area can significantly reduce subjectivity and increase the accuracy of HDS identification.