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Remote Sensing Image Analysis: Including the Spatial Domain

  • Book
  • © 2004

Overview

Editors:
  1. Steven M. De Jong

    1. Department of Physical Geography, Faculty of Geosciences, Utrecht University, The Netherlands

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  2. Freek D. Van der Meer

    1. Department of Physical Geography, Faculty of Geosciences, Utrecht University, The Netherlands
      Department of Earth Systems Analysis, International Institute for Geo-Information Science and Earth Observation (ITC), Enschede, The Netherlands

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  • Follow-up to the previous publication Imaging Spectrometry - Basic Principles and Prospective Applications (2001) by the same Editors
  • Shift from spectrally based techniques to spatial-based approaches
  • Includes supplementary material: sn.pub/extras

Part of the book series: Remote Sensing and Digital Image Processing (RDIP, volume 5)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xv
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  2. Basics of Remote Sensing

    • Steven M. de Jong, Freek D. van der Meer, Jan G.P.W Clevers
    Pages 1-15

  3. Spatial Variability, Mapping Methods, Image Analysis and Pixels

    • Steven M. de Jong, Edzer J. Pebesma, Freek D. van der Meer
    Pages 17-35

  4. Sub-Pixel Methods in Remote Sensing

    • Giles M. Foody
    Pages 37-49

  5. Resolution Manipulation and Sub-Pixel Mapping

    • Peter M. Atkinson
    Pages 51-70

  6. Multiscale Object-Specific Analysis (MOSA): An Integrative Approach for Multiscale Landscape Analysis

    • Geoffrey J. Hay, Danielle J. Marceau
    Pages 71-92

  7. Variogram Derived Image Texture for Classifying Remotely Sensed Images

    • Mario Chica-Olmo, Francisco Abarca-Hernández
    Pages 93-111

  8. Merging Spectral and Textural Information for Classifying Remotely Sensed Images

    • Süha Berberoglu, Paul J. Curran
    Pages 113-136

  9. Contextual Image Analysis Methods for Urban Applications

    • Peng Gong, Bing Xu
    Pages 137-152

  10. Pixel-Based, Stratified and Contextual Analysis of Hyperspectral Imagery

    • Freek D. van der Meer
    Pages 153-180

  11. Variable Multiple Endmember Spectral Mixture Analysis for Geology Applications

    • Klaas Scholte, Javier García-Haro, Thomas Kemper
    Pages 181-200

  12. A Contextual Algorithm for Detection of Mineral Alteration Halos with Hyperspectral Remote Sensing

    • Harald van der Werff, Arko Lucieer
    Pages 201-210

  13. Image Segmentation Methods for Object-based Analysis and Classification

    • Thomas Blaschke, Charles Burnett, Anssi Pekkarinen
    Pages 211-236

  14. Multiscale Feature Extraction from Images Using Wavelets

    • Luis M.T. de Carvalho, Fausto W. Acerbi Jr, Jan G.P.W. Clevers, Leila M.G. Fonseca, Steven M. de Jong
    Pages 237-270

  15. Contextual Analyses of Remotely Sensed Images for the Operational Classification of Land Cover in United Kingdom

    • Robin M. Fuller, Geoff M. Smith, Andy G. Thomson
    Pages 271-290

  16. A Contextual Approach to Classify Mediterranean Heterogeneous Vegetation using the Spatial Reclassification Kernel (SPARK) and DAIS7915 Imagery

    • Raymond Sluiter, Steven M. de Jong, Hans van der Kwast, Jan Walstra
    Pages 291-310

  17. Back Matter

    Pages 311-359
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Keywords

About this book

Remote Sensing image analysis is mostly done using only spectral information on a pixel by pixel basis. Information captured in neighbouring cells, or information about patterns surrounding the pixel of interest often provides useful supplementary information. This book presents a wide range of innovative and advanced image processing methods for including spatial information, captured by neighbouring pixels in remotely sensed images, to improve image interpretation or image classification. Presented methods include different types of variogram analysis, various methods for texture quantification, smart kernel operators, pattern recognition techniques, image segmentation methods, sub-pixel methods, wavelets and advanced spectral mixture analysis techniques. Apart from explaining the working methods in detail a wide range of applications is presented covering land cover and land use mapping, environmental applications such as heavy metal pollution, urban mapping and geological applications to detect hydrocarbon seeps.

The book is meant for professionals, PhD students and graduates who use remote sensing image analysis, image interpretation and image classification in their work related to disciplines such as geography, geology, botany, ecology, forestry, cartography, soil science, engineering and urban and regional planning.

Editors and Affiliations

  • Department of Physical Geography, Faculty of Geosciences, Utrecht University, The Netherlands

    Steven M. De Jong, Freek D. Van der Meer

  • Department of Earth Systems Analysis, International Institute for Geo-Information Science and Earth Observation (ITC), Enschede, The Netherlands

    Freek D. Van der Meer

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