SURFACE WATERBODY DETECTION FROM SATELLITE IMAGERY USING U-NET

Surface Waterbody Detection from Satellite Imagery Using U-Net: A Deep Learning Framework for Automated Analysis is a definitive guide for leveraging advanced deep learning techniques to detect and monitor surface water bodies from satellite images. This book introduces the U-Net architecture a powerful deep learning model to automate the analysis of satellite imagery enabling precise detection of waterbodies across diverse terrains and conditions.With a focus on practical applications the book provides an in-depth walkthrough of the entire process including data preprocessing model training validation and performance evaluation using real-world datasets. It addresses key challenges such as handling noisy data low-resolution imagery and scalability for large-scale analyses.Whether you are a researcher data scientist or environmental analyst this book equips you with the tools and insights needed to tackle real-world problems in environmental monitoring disaster management and resource planning. With detailed code examples practical case studies and a look into emerging trends it empowers you to harness the potential of AI in satellite imagery analysis.