Object and Pattern Recognition in Remote Sensing

Object and Pattern Recognition in Remote Sensing

Modelling and Monitoring Environmental and Anthropogenic Objects and Change Processes

Stefan Hinz, Andreas Braun, Martin Weinmann

Extract from Foreword by Professor Christian Heipke, ISPRS President 2016–2020. Institut für Photogrammetrie und GeoInformation (IPI), Leibniz Universität Hannover

‘...an excellent overview of the current state-of-the-art in photogrammetry and remote sensing. ... of high relevance to students and other people wanting to learn about photogrammetry and remote sensing. ... I congratulate the authors...’

  • A comprehensive account of the subject covering both concepts and applications
  • Written by a team of international experts

 

Print edition: £90.00
978-184995-128-9
234 × 156mm
352 pages
liberally illustrated with over 120 photographs, charts, and line diagrams, colour throughout
Hardback
Quantity:
PDF Edition: £84.50
978-184995-556-0

Fully automated interpretation and understanding of remotely sensed data by a computer has been a challenge for many decades, and many approaches have been developed over the years. Significant advances in knowledge-based image understanding, machine learning and artificial intelligence has led to this topic being the focus of much research in recent years.

This book highlights the different theoretical and application-oriented aspects and potential solutions to the topic of automated remote sensing data analysis. Thereby, both classical knowledge-based as well as modern machine learning-oriented concepts are described. A field such as this is specialized and dynamic and also interdisciplinary and multilayered.  Written by an international team of experts, the book has therefore been split into parts dealing with the concepts and applications, and the focus is on elucidating the complementarity of different lines of research rather than providing the complete set of scientific approaches.

Part A of this book gives 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 sketches recent trends in automatic analysis of remote sensing data.

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