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Remote Sensing Image Analysis: Including The Spatial Domain

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Cover of 'Remote Sensing Image Analysis: Including The Spatial Domain'

Table of Contents

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    Book Overview
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    Chapter 1 Basics of Remote Sensing
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    Chapter 2 Spatial Variability, Mapping Methods, Image Analysis and Pixels
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    Chapter 3 Sub-Pixel Methods in Remote Sensing
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    Chapter 4 Resolution Manipulation and Sub-Pixel Mapping
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    Chapter 5 Multiscale Object-Specific Analysis (MOSA): An Integrative Approach for Multiscale Landscape Analysis
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    Chapter 6 Variogram Derived Image Texture for Classifying Remotely Sensed Images
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    Chapter 7 Merging Spectral and Textural Information for Classifying Remotely Sensed Images
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    Chapter 8 Contextual Image Analysis Methods for Urban Applications
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    Chapter 9 Pixel-Based, Stratified and Contextual Analysis of Hyperspectral Imagery
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    Chapter 10 Variable Multiple Endmember Spectral Mixture Analysis for Geology Applications
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    Chapter 11 A Contextual Algorithm for Detection of Mineral Alteration Halos with Hyperspectral Remote Sensing
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    Chapter 12 Image Segmentation Methods for Object-based Analysis and Classification
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    Chapter 13 Multiscale Feature Extraction from Images Using Wavelets
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    Chapter 14 Contextual Analyses of Remotely Sensed Images for the Operational Classification of Land Cover in United Kingdom
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    Chapter 15 A Contextual Approach to Classify Mediterranean Heterogeneous Vegetation using the Spatial Reclassification Kernel (SPARK) and DAIS7915 Imagery
Attention for Chapter 12: Image Segmentation Methods for Object-based Analysis and Classification
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Chapter title
Image Segmentation Methods for Object-based Analysis and Classification
Chapter number 12
Book title
Remote Sensing Image Analysis: Including The Spatial Domain
Published by
Springer, Dordrecht, January 2004
DOI 10.1007/978-1-4020-2560-0_12
Book ISBNs
978-1-4020-2559-4, 978-1-4020-2560-0
Authors

Thomas Blaschke, Charles Burnett, Anssi Pekkarinen

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 2%
Unknown 61 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 24%
Student > Ph. D. Student 10 16%
Researcher 8 13%
Student > Doctoral Student 4 6%
Student > Bachelor 3 5%
Other 9 15%
Unknown 13 21%
Readers by discipline Count As %
Environmental Science 12 19%
Earth and Planetary Sciences 12 19%
Computer Science 9 15%
Agricultural and Biological Sciences 5 8%
Engineering 5 8%
Other 4 6%
Unknown 15 24%