Rough Sets for Satellite Image Classification

"Rough Sets for Satellite Image Classification" is a specialized book that focuses on the application of Rough Set Theory in the classification of satellite images. It examines how the quality of the ground truth data, which is crucial for monitoring learning, can be compromised by redundant, inconsistent, or contradictory information. The book provides deep insights into the challenges of data analysis and illustrates how Rough Set Theory can be used as an effective tool to address uncertainties, analyze conflicts, and evaluate data dependencies. A particular emphasis is placed on the classification of land use and land cover, an important topic in landscape ecology. The author, Sonika Jindal, demonstrates the application of this theory using LISS-III images from the Alwar region in India and compares the results with other classification methods. The findings show that Rough Set Theory delivers superior and more accurate results in today's context, where time and precision are critical.