Object-Based Image Analysis

1. Front Matter

   Pages I-XVII

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2. Why object-based image analysis

   1. Front Matter

      Pages 1-1

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   2. Object-based image analysis for remote sensing applications: modeling reality – dealing with complexity

      • S. Lang

      Pages 3-27

   3. Progressing from object-based to object-oriented image analysis

      • M. Baatz, C. Hoffmann, G. Willhauck

      Pages 29-42

   4. An object-based cellular automata model to mitigate scale dependency

      • D. J. Marceau, N. Moreno

      Pages 43-73

   5. Geographic Object-Based Image Analysis (GEOBIA): A new name for a new discipline

      • G. J. Hay, G. Castilla

      Pages 75-89

   6. Image objects and geographic objects

      • G. Castilla, G. J. Hay

      Pages 91-110

3. Multiscale representation and object-based classification

   1. Front Matter

      Pages 111-111

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   2. Using texture to tackle the problem of scale in land-cover classification

      • P. Corcoran, A. Winstanley

      Pages 113-132

   3. Domain-specific class modelling for one-level representation of single trees

      • D. Tiede, S. Lang, C. Hoffmann

      Pages 133-151

   4. Object recognition and image segmentation: the Feature Analyst® approach

      • D. Opitz, S. Blundell

      Pages 153-167

   5. A procedure for automatic object-based classification

      • P.R. Marpu, I. Niemeyer, S. Nussbaum, R. Gloaguen

      Pages 169-184

   6. Change detection using object features

      • I. Niemeyer, P.R. Marpu, S. Nussbaum

      Pages 185-201

   7. Identifying benefits of pre-processing large area QuickBird imagery for object-based image analysis

      • T. Lübker, G. Schaab

      Pages 203-219

   8. A hybrid texture-based and region-based multi-scale image segmentation algorithm

      • A. Tzotsos, C. Iosifidis, D. Argialas

      Pages 221-236

   9. Semi-automated forest stand delineation using wavelet based segmentation of very high resolution optical imagery

      • F.M.B. Van Coillie, L.P.C. Verbeke, R.R. De Wulf

      Pages 237-256

   10. Quality assessment of segmentation results devoted to object-based classification

       • J. Radoux, P. Defourny

       Pages 257-271

4. Automated classification, mapping and updating: forest

   1. Front Matter

      Pages 273-273

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   2. Object-based classification of QuickBird data using ancillary information for the detection of forest types and NATURA 2000 habitats

      • M. Förster, B. Kleinschmit

      Pages 275-290

   3. Estimation of optimal image object size for the segmentation of forest stands with multispectral IKONOS imagery

      • M. Kim, M. Madden, T. Warner

      Pages 291-307

This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).

• Change detection
• GIS
• Geoinformationssysteme
• IKONOS
• Monitoring
• Object-based image analysis
• classification
• digital elevation model
• ecosystem
• geoinformatics
• image analysis
• image processing
• remote sensing
• satellite
• vegetation
• remote sensing/photogrammetry
• landscape/regional and urban planning

• Universität Salzburg Zentrum für Geoinformatik, 5020 Salzburg, Austria

  Thomas Blaschke, Stefan Lang

• Foothills Facility for Remote Sensing & GIScience, University of Calgary, Calgary T2N 1N4, Canada

  Geoffrey J. Hay

Policies and ethics