Remote Sensing Image Analysis: Including the Spatial Domain

Remote Sensing Image Analysis: Including the Spatial Domain

Paperback(Softcover reprint of the original 1st ed. 2004)

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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.

Product Details

ISBN-13: 9789401740616
Publisher: Springer Netherlands
Publication date: 05/31/2013
Series: Remote Sensing and Digital Image Processing , #5
Edition description: Softcover reprint of the original 1st ed. 2004
Pages: 359
Product dimensions: 6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

Ch 1 - Basics of Remote Sensing
Steven M. de Jong, Freek D. van der Meer & Jan G.P.W. Clevers
Ch 2 – Spatial Variability, Mapping Methods, Image Analysis and Pixels
Steven M. de Jong, Edzer J. Pebesma & Freek D. van der Meer
Ch 3 - Sub-Pixel Methods in Remote Sensing
Giles M. Foody
Ch 4 – Resolution Manipulation and Sub-Pixel Mapping
Peter M. Atkinson
Ch 5 – Multiscale Object-Specific Analysis (MOSA): An Integrative Approach for Multiscale Landscape Analysis
Geoffrey J. Hay & Danielle J. Marceau
Ch 6 – Variogram Derived Image Texture for Classifying Remotely Sensed Images
Mario Chica-Olmo & Francisco Abara-Hernandez
Ch 7 – Merging Spectral and Textural Information for Classifying Remotely Sensed Images
Süha Berberoglu & Paul J. Curran
Ch 8 – Contextual Image Analysis Methods for Urban Applications
Peng Gong & Bing Xu
Ch 9 – Pixel-Based, Stratified and Contextual Analysis of Hyperspectral Imagery
Freek D. van der Meer
Ch 10 – Variable Multiple Endmember Spectral Mixture Analysis for Geology Applications
Klaas Scholte, Javier Garcia-Haro & Thomas Kemper
Ch 11 – A Contextual Algorithm for Detection of Mineral Alteration Halos with Hyperspectral Remote Sensing
Harald van der Werff & Arko Lucieer
Ch 12 – Image Segmentation Methods for Object-Based Analysis and Classification
Thomas Blaschke, Charles Burnett & Anssi Pekkarinen
Ch 13 – Multiscale Feature Extraction from Images Using Wavelets
Luis M.T. deCarvalho, Fausto W. Acerbi Jr., Jan G.P.W. Clevers, Leila M.G. Fonseca & Steven M. de Jong
Ch 14 – Contextual Analysis of Remotely Sensed Images for the Operational Classification of Land Cover in the United Kingdom
Robin M. Fuller, Geoff M. Smith & Andy G. Thomson
Ch 15 – 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

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