This book highlights the different theoretical and application-oriented aspects and potential solutions to the subject of automated remote sensing data analysis. Fully automated interpretation and understanding of remotely sensed data by a computer has been a challenge for decades, and many approaches have been developed over the years. The field is specialized and dynamic and also interdisciplinary and multilayered. Significant advances in knowledge-based image understanding, machine learning and artificial intelligence have led to it being the focus of much research in recent years. Written by an international team of experts, the book deals with both concepts and applications and focuses on elucidating the complementarity of different lines of research rather than providing the complete set of scientific approaches. Both classical knowledge-based as well as modern machine learning-oriented concepts are described. Part A provides insight into the basic theories and concepts of feature extraction, image understanding and the respective assessment strategies as well as into geometric, radiometric and sensor-related fundamentals of remote sensing technology. Part B focuses on various scientific and practical applications of remote sensing data analysis. These range from the automatic detailed reconstruction of complex 3D environments to visual tracking of objects in image sequences as well as monitoring natural and anthropogenic long-term processes on a regional scale. Part C covers recent trends in automatic analysis of remote sensing data.
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