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.
Table of Contents:
Part A: Methodology Introduction; Object, data and sensor modelling; Feature extraction from images and point clouds: Fundamentals, advances and trends; A short survey on supervised classification in remote; Context-based classification; Toward a framework for quality assessment in remote sensing applicationsPart B: Application From raw 3D point clouds to semantic objects; Traffic extraction and characterization from optical remote sensing data; Object extraction in image sequences; A process-based model approach to predict future land-use changes and link biodiversity with soil erosion in Chile; Interferometric SAR Image analysis for 3D building reconstruction; Detection and classification of collapsed buildings after a strong earthquake by means of laser scanning and image analysis; A settlement process analysis in coastal Benin - confronting scarce data availability in developing countriesPart C: Conclusion Benchmarking - a basic requirement for effective performance evaluation; Remote sensing and computer vision image analysis: summary and recent trends
About the Author :
Professor Stefan Hinz, Director of the Institute of Photogrammetry & Remote Sensing, Karlsruhe Institute of Technology, Germany.
Dr. Andreas Braun, Institute for Regional Science Karlsruhe Institute of Technology, Germany.
Professor Martin Weinmann, Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, Germany.
