دانلود کتاب رادار -تحلیل داده‌های سنجش از دور با هوش مصنوعی

In modern technologies, incorporating remote sensing with artificial intelligence (AI) plays a significant role in Earth observations. Radio detection and ranging (RADAR) is a one-of-a-kind technology that allows all-weather remote sensing services. With this focus, this book explores the potential applications and advanced algorithms of RADAR-based remote sensing. This book guides researchers, scientists, teachers, and students in monitoring and managing Earth’s resources. This multidisciplinary book explores the recent advancements and applications of AI-driven RADAR-based remote sensing. The introductory chapter comprehensively covers the fundamental principles and science of RADAR-based remote sensing. It also includes the fundamentals of collecting, analyzing, and interpreting remotely sensed images. This chapter is followed by the evolution of RADAR-based remote sensing, that is, synthetic aperture radar (SAR) and scatterometry. It further highlights the potential applications of active and passive microwave remote sensing with the integration of AI. Then, it is followed by various challenges associated with AI-driven RADAR remote sensing. This book also explores multisource data fusion techniques to enhance image interpretation and to integrate the features of the SAR/scatterometer with the optical dataset for improvement in accuracy. It also involves classification and change detection applications in extracting essential information. Furthermore, deep learning and machine learning approaches expand the applicability range of RADAR-based remote sensing by providing object-level detection and solving complex problems. It also explores the role of the Internet of things (IoT) in remote sensing for real-time data collection and analysis. The book comprises various environmental monitoring sensors for accurate monitoring and prediction analysis. With the involvement of AI, emerging applications of RADAR-based remote sensing are also discussed, such as crop growth monitoring, weed management, yield estimation, real-time monitoring of soil moisture, classification of crop species, and weather patterns. This book also highlights the monitoring of urban infrastructure and its impact on agricultural land. Moreover, it also covers disaster management via continuous soil moisture monitoring with RADAR-based remote sensing. The book concludes that emerging AI-enabled RADAR applications in real-time scenarios provide the future scope of RADAR remote sensing with AI. This book is a reference to researchers, scientists, students, and stakeholders to explore the potential of AI-enabled RADAR applications in real-time scenarios. With real-world case studies, it offers insights into mapping different crops, smart irrigation, pest control, and crop yield prediction analysis. Moreover, it delivers comprehensive knowledge of RADAR-based remote sensing in improving precision agricultural practices.