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Object-Based Image Analysis

Spatial Concepts for Knowledge-Driven Remote Sensing Applications

  • Book
  • © 2008

Overview

Editors:
  1. Thomas Blaschke

    1. Universität Salzburg Zentrum für Geoinformatik, 5020 Salzburg, Austria

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  2. Stefan Lang

    1. Universität Salzburg Zentrum für Geoinformatik, 5020 Salzburg, Austria

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  3. Geoffrey J. Hay

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

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  • Discusses means, technologies and approaches related to the processing and analysis of multi-sensor, multi-resolution data with a focus on the generation, modelling and classification of objects
  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes in Geoinformation and Cartography (LNGC)

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Table of contents (43 chapters)

  1. Front Matter

    Pages I-XVII
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  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
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Keywords

About this book

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).

Editors and Affiliations

  • 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

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