The latter being a hot research topic that is repeatedly tackled within the application centric contributions, as well as in the last section on research questions. These nine chapters include specific aspects such as the incorporation of image-texture, key pre-processing steps and quality assessment issues. Consequently, the first five chapters focus on fundamental and conceptual issues, followed by nine chapters on multiscale representation and object-based classification. Our primary goal in this book is to unveil the concept of OBIA as applied within a broad range of remote sensing applications. This volume, we pave the road ahead for the GEOBIA 2008 conference at the University of Calgary, Alberta, Canada. Furthermore, by incorporating a GEOBIA chapter in Because this name debate remains ongoing, we have chosen for this book to build on key OBIA concepts so as to lay out generic foundations for the continued evolution of this diverse community of practice. However, such an association may not be taken for granted by scientists in disciplines such as Computer Vision, Material Sciences or Biomedical Imaging that also conduct OBIA. Indeed, the term OBIA may be too broad for it goes without saying for Remote Sensing scientists, GIS specialist and many ‘environmental’ based disciplines, that ‘their’ image data represents portions of the Earth’s surface. Hay and Castilla argue (in chapter 1.4) that it should be called “Geographic Object-Based Image Analysis” (GEOBIA), as only then will it be clear that it represents a sub-discipline of GIScience. Over the last year, a critical online discussion within this evolving multidisciplinary community – especially, among the editors – has also arisen concerning whether or not Geographic space should be included in the name of this concept. Nevertheless, 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 characteristics and analyses in Earth Observation data (EO). 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.
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 ‘objectoriented image analysis’. 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. Its content is based on select papers from the 1st OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. This book brings together a collection of invited interdisciplinary perspectives on the recent topic of Object-based Image Analysis (OBIA). Typesetting: Camera-ready by the editors Cover design: deblik, Berlin Printed on acid-free paper 9 8 7 6 5 4 3 2 1
in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The use of general descriptive names, registered names, trademarks, etc. Violations are liable to prosecution under the German Copyright Law. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Lecture Notes in Geoinformation and Cartography ISSN: 1863-2246 Library of Congress Control Number: 2008930772 c 2008 Springer-Verlag Berlin Heidelberg This work is subject to copyright. Hay University of Calgary Foothills Facility for Remote Sensing & GIScience 2500 University Dr. Stefan Lang Universit¨at Salzburg Zentrum f¨ur Geoinformatik Schillerstr. Thomas Blaschke Universit¨at Salzburg Zentrum f¨ur Geoinformatik Hellbrunner Str. Object-Based Image Analysis Spatial Concepts for Knowledge-Driven Remote Sensing ApplicationsĮditors Prof.
Lecture Notes in Geoinformation and Cartography Series Editors: William Cartwright, Georg Gartner, Liqiu Meng, Michael P.