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© 2011

Multispectral Satellite Image Understanding

From Land Classification to Building and Road Detection

Book

Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages I-XVII
  2. Sensors

    1. Front Matter
      Pages 5-5
    2. Cem Ünsalan, Kim L. Boyer
      Pages 1-4
  3. Sensors

    1. Front Matter
      Pages 5-5
    2. Cem Ünsalan, Kim L. Boyer
      Pages 7-15
  4. The Multispectral Information

    1. Front Matter
      Pages 17-17
    2. Cem Ünsalan, Kim L. Boyer
      Pages 19-39
    3. Cem Ünsalan, Kim L. Boyer
      Pages 41-46
  5. Land Use Classification

    1. Front Matter
      Pages 47-47
    2. Cem Ünsalan, Kim L. Boyer
      Pages 49-64
    3. Cem Ünsalan, Kim L. Boyer
      Pages 65-81
    4. Cem Ünsalan, Kim L. Boyer
      Pages 83-98
    5. Cem Ünsalan, Kim L. Boyer
      Pages 99-120
  6. Extracting Residential Regions

    1. Front Matter
      Pages 121-121
    2. Cem Ünsalan, Kim L. Boyer
      Pages 123-129
    3. Cem Ünsalan, Kim L. Boyer
      Pages 131-136
  7. Building and Road Detection

    1. Front Matter
      Pages 137-137
    2. Cem Ünsalan, Kim L. Boyer
      Pages 139-144
    3. Cem Ünsalan, Kim L. Boyer
      Pages 145-176
  8. Summarizing the Overall System

    1. Front Matter
      Pages 177-177
    2. Cem Ünsalan, Kim L. Boyer
      Pages 179-182
  9. Back Matter
    Pages 183-185

About this book

Introduction

Rapid development of remote sensing technology in recent years has greatly increased availability of high-resolution satellite image data.  However, detailed analysis of such large data sets also requires innovative new techniques in image and signal processing.

This important text/reference presents a comprehensive review of image processing methods, for the analysis of land use in residential areas.  Combining a theoretical framework with highly practical applications, making use of both well-known methods and cutting-edge techniques in computer vision, the book describes a system for the effective detection of single houses and streets in very high resolution. 

Topics and features:

  • With a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center
  • Provides end-of-chapter summaries and review questions
  • Presents a detailed review on remote sensing satellites
  • Examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices
  • Investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images
  • Addresses the problem of detecting residential regions
  • Describes a house and street network-detection subsystem
  • Concludes with a summary of the key ideas covered in the book

This pioneering work on automated satellite and aerial image-understanding systems will be of great interest to researchers in both remote sensing and computer vision, highlighting the benefit of interdisciplinary collaboration between the two communities.  Urban planners and policy makers will also find considerable value in the proposed system.

Dr. Cem Ünsalan is an Associate Professor in the Department of Electrical and Electronics Engineering at Yeditepe University, Istanbul, Turkey.  Dr. Kim Boyer is Professor and Head of the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, Troy, NY, USA.

Keywords

Building Detection Change Grading Computer Vision Land Use Classification Remote Sensing Road Detection Satellite Images Vegetation Indices

Authors and affiliations

  1. 1.Electrical and Electronics EngineeringYeditepe UniversityKayisdagiTurkey
  2. 2.Dept. Electrical, Comp. & Systems Eng.Rensselaer Polytechnic InstituteTroyUSA

Bibliographic information

  • Book Title Multispectral Satellite Image Understanding
  • Book Subtitle From Land Classification to Building and Road Detection
  • Authors Cem Ünsalan
    Kim L. Boyer
  • Series Title Advances in Computer Vision and Pattern Recognition
  • Series Abbreviated Title Advs Comp. Vision, Pattern Recognition
  • DOI https://doi.org/10.1007/978-0-85729-667-2
  • Copyright Information Springer-Verlag London Limited 2011
  • Publisher Name Springer, London
  • eBook Packages Computer Science Computer Science (R0)
  • Hardcover ISBN 978-0-85729-666-5
  • Softcover ISBN 978-1-4471-2656-0
  • eBook ISBN 978-0-85729-667-2
  • Series ISSN 2191-6586
  • Series E-ISSN 2191-6594
  • Edition Number 1
  • Number of Pages XVIII, 186
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Image Processing and Computer Vision
    Pattern Recognition
  • Buy this book on publisher's site

Reviews

From the reviews:

“The authors write that their aims were the proposal of a novel automated end-to-end system to analyze multispectral satellite images and to emphasize how many research problems in remote sensing applications are waiting to be solved by the computer vision community. Well, the book satisfies both these goals. … it represents a good reference book, even a milestone, for teaching multispectral image understanding to students and/or young researchers.” (Primo Zingaretti, IAPR Newsletter, Vol. 34 (3), July-August, 2012)