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Optical Remote Sensing

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Cover of 'Optical Remote Sensing'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Hyperspectral Data Compression Tradeoff
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    Chapter 3 Reconstructions from Compressive Random Projections of Hyperspectral Imagery
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    Chapter 4 Integrated Sensing and Processing for Hyperspectral Imagery
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    Chapter 5 Color Science and Engineering for the Display of Remote Sensing Images
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    Chapter 6 An Evaluation of Visualization Techniques for Remotely Sensed Hyperspectral Imagery
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    Chapter 7 A Divide-and-Conquer Paradigm for Hyperspectral Classification and Target Recognition
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    Chapter 8 The Evolution of the Morphological Profile: from Panchromatic to Hyperspectral Images
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    Chapter 9 Decision Fusion of Multiple Classifiers for Vegetation Mapping and Monitoring Applications by Means of Hyperspectral Data
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    Chapter 10 A Review of Kernel Methods in Remote Sensing Data Analysis
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    Chapter 11 Exploring Nonlinear Manifold Learning for Classification of Hyperspectral Data
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    Chapter 12 Recent Developments in Endmember Extraction and Spectral Unmixing
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    Chapter 13 Change Detection in VHR Multispectral Images: Estimation and Reduction of Registration Noise Effects
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    Chapter 14 Effects of the Spatial Enhancement of Hyperspectral Images on the Distribution of Spectral Classes
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    Chapter 15 Fusion of Optical and SAR Data for Seismic Vulnerability Mapping of Buildings
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Title
Optical Remote Sensing
Published by
Springer Berlin Heidelberg, March 2011
DOI 10.1007/978-3-642-14212-3
ISBNs
978-3-64-214211-6, 978-3-64-214212-3
Editors

Prasad, Saurabh, Bruce, Lori M., Chanussot, Jocelyn

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 1%
Australia 1 1%
Mexico 1 1%
China 1 1%
United States 1 1%
Unknown 84 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 29%
Student > Master 15 17%
Researcher 12 13%
Student > Bachelor 5 6%
Student > Doctoral Student 4 4%
Other 17 19%
Unknown 10 11%
Readers by discipline Count As %
Engineering 26 29%
Computer Science 16 18%
Earth and Planetary Sciences 14 16%
Environmental Science 8 9%
Physics and Astronomy 6 7%
Other 8 9%
Unknown 11 12%