Subpixel Mapping for Remote Sensing Images

283 Pages·2022·56.866 MB·English

by  Peng Wang, Lei Zhang

Subpixel Mapping for
Remote Sensing Images
This book provides readers with a complete overview of subpixel image processing
methods, basic principles, and different subpixel mapping techniques based on single
or multi-shift remote sensing images. Real-life applications are a great resource for
understanding how and where to use subpixel mapping when dealing with different
remote sensing imaging data.
FEATURES
• Provides the fundamentals of subpixel mapping technology and its
applications.
• Discusses in detail the advantages of using different subpixel mapping
techniques based on remote sensing data.
• Summarizes in a systematic way current subpixel mapping methods.
• Highlights authors’ achievements in subpixel mapping technology.
• Includes case studies based on remote sensing data from the United States,
Italy, China, and Cambodia.
This book will be of interest to undergraduate and graduate students majoring in
remote sensing, surveying, mapping, and signal and information processing in
universities and colleges, and it can also be used by professionals and researchers at
different levels in related felds.

Subpixel Mapping for
Remote Sensing Images
Peng Wang and Lei Zhang
Boca Raton London New York
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First edition published 2023
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CRC Press is an imprint of Taylor & Francis Group, LLC
© 2023 Peng Wang and Lei Zhang
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ISBN: 978-1-032-22938-6 (hbk)
ISBN: 978-1-032-24522-5 (pbk)
ISBN: 978-1-003-27908-2 (ebk)
DOI: 10.1201/9781003279082
Typeset in Times
by Apex CoVantage, LLC
Contents
Foreword ................................................................................................................... ix
Preface....................................................................................................................... xi
Authors....................................................................................................................xiii
Chapter 1 Introduction.......................................................................................... 1
1.1 Background and Signifcance...................................................... 1
1.1.1 Background of Subpixel Mapping................................... 1
1.1.2 Signifcance of Subpixel Mapping................................... 4
1.2 Research Status of Subpixel Mapping......................................... 6
1.2.1 Initialize-Then-Optimize Subpixel Mapping.................. 7
1.2.2 Soft-Then-Hard Subpixel Mapping ................................. 8
1.2.3 Other Types of Subpixel Mapping................................... 9
1.2.4 Research Status of Super-Resolution Technology.............11
1.3 Problems in Subpixel Mapping ..................................................12
1.4 Main Research Contents and Chapter Arrangement..................13
References ...........................................................................................15
Chapter 2 Basic Principles of Subpixel Mapping ............................................... 23
2.1 Introduction ............................................................................... 23
2.2 Spectral Unmixing Method....................................................... 23
2.2.1 Linear Spectral Unmixing Model ................................. 23
2.2.2 Non-linear Spectral Unmixing Model........................... 24
2.3 Theoretical Basis of Spatial Correlation ................................... 24
2.4 Processing Flow of Subpixel Mapping...................................... 25
2.4.1 Subpixel Sharpening Method........................................ 25
2.4.2 Class Allocation Method............................................... 28
2.5 Evaluation Method of Subpixel Mapping Accuracy ................. 30
2.6 Summary ....................................................................................33
References .......................................................................................... 34
Chapter 3 Subpixel Mapping Based on Single Remote Sensing Image ..............35
3.1 Introduction ................................................................................35
3.2 Subpixel Mapping Based on Spatial-Spectral
Interpolation ...............................................................................35
3.2.1 Interpolation Problem.................................................... 36
3.2.2 Existing Subpixel Mapping Based on
Interpolation ...................................................................37
3.2.3 Processing Flow of the Proposed Method..................... 38
3.2.4 Experimental Content and Result Analysis................... 40
v
vi Contents
3.3 Subpixel Mapping Based on Hopfeld Neural Network
With More Supervision Information ......................................... 48
3.3.1 Traditional Subpixel Mapping Method Based
on Hopfeld Neural Network.......................................... 48
3.3.2 Hopfeld Neural Network With More Prior
Information.................................................................... 49
3.3.3 Experiment Content and Result Analysis.......................51
3.4 Subpixel Mapping Based on Extended Random Walk...............55
3.4.1 Multi-Scale Segmentation Algorithm ............................55
3.4.2 Extended Random Walk Algorithm...............................57
3.4.3 Class Allocation Method Based on Object Unit.............58
3.4.4 Experimental Content and Result Analysis....................59
3.5 Subpixel Mapping Based on Spatial-Spectral
Correlation for Spectral Imagery .............................................. 64
3.5.1 Spatial Correlation......................................................... 64
3.5.2 Spectral Correlation....................................................... 66
3.5.3 Spatial-Spectral Correlation Implementation .................67
3.5.4 Experimental Content and Result Analysis................... 69
3.6 Summary ....................................................................................81
References .......................................................................................... 82
Chapter 4 Subpixel Mapping Based on Multi-Shift Remote
Sensing Images................................................................................... 85
4.1 Introduction ............................................................................... 85
4.2 Theoretical Basis....................................................................... 85
4.2.1 Multi-Shift Images Problem.......................................... 85
4.2.2 Existing Subpixel Mapping Method Based
on Multi-Shift Images ................................................... 87
4.3 Subpixel Mapping Method Based on Multi-Shift
With Spatial-Spectral Information............................................ 88
4.3.1 Multi-Shift Image With More Spatial-
Spectral Information...................................................... 88
4.3.2 Experiment Content and Result Analysis.......................91
4.4 Subpixel Mapping Based on the Spatial Attraction
Model With Multi-Scale Subpixel Shifted Images ................. 100
4.4.1 Subpixel-Pixel Spatial Attraction Model..................... 100
4.4.2 Subpixel-Subpixel Spatial Attraction Model ................102
4.4.3 Spatial Attraction Model With Multi-Scale
Subpixel Shifted Image ................................................103
4.4.4 Experiment Content and Result Analysis.....................104
4.5 Utilizing Parallel Networks to Produce Subpixel Shifted
Images With Multi-Scale Spatial-Spectral Information
for Subpixel Mapping...............................................................115
4.5.1 Multi-Scale Network and Spatial-Spectral
Network ........................................................................115
Contents vii
4.5.2 Multi-Scale Spatial-Spectral Information....................119
4.5.3 Experimental Content and Result Analysis..................121
4.6 Spatiotemporal Subpixel Mapping by Considering
the Point Spread Function Effect..............................................132
4.6.1 Spatial Dependence......................................................133
4.6.2 Temporal Dependence..................................................135
4.6.3 Spatiotemporal Dependence.........................................136
4.6.4 Experimental Content and Result Analysis..................136
4.7 Summary ..................................................................................142
References .........................................................................................143
Chapter 5 Subpixel Mapping of Remote Sensing Image Based
on Fusion Technology .......................................................................145
5.1 Introduction ..............................................................................145
5.2 Soft-Then-Hard Subpixel Mapping Based on
Pansharpening Technology ......................................................146
5.2.1 Pansharpening Technology ..........................................146
5.2.2 STHSRM-PAN.............................................................148
5.2.3 Experimental Content and Result Analysis..................150
5.3 Subpixel Land Cover Mapping Based on Parallel
Processing Path for Hyperspectral Image................................159
5.3.1 Fusion Path ...................................................................159
5.3.2 Deep Learning Path......................................................161
5.3.3 Dual Processing Path....................................................163
5.3.4 Experimental Content and Result Analysis..................164
5.4 Subpixel Mapping Based on Multi-Source Remote
Sensing Fusion Data for Land Cover Classes...........................175
5.4.1 Data-Level Fusion.........................................................178
5.4.2 Feature Fusion ..............................................................178
5.4.3 Obtaining Mapping Result ...........................................179
5.4.4 Experimental Content and Result Analysis..................180
5.5 Summary ..................................................................................186
References .........................................................................................188
Chapter 6 Remote Sensing Image Subpixel Mapping Based on
Classifcation Then Reconstruction...................................................191
6.1 Introduction ..............................................................................191
6.2 Theoretical Basis......................................................................191
6.2.1 Super-Resolution Algorithm.........................................191
6.2.2 Fully Supervised Information Classifcation
Algorithm .....................................................................193
6.3 Subpixel Mapping Based on MAP Super-Resolution
Reconstruction Then Classifcation..........................................199
viii Contents
6.3.1 Transformed MAP-Based Super-Resolution
Reconstruction..............................................................199
6.3.2 LSSVM Classifcation Algorithm ............................... 203
6.3.3 Experiment Content and Result Analysis.................... 204
6.4 Subpixel Mapping Based on Pansharpening Then
Classifcation ............................................................................219
6.4.1 Implementation Steps...................................................219
6.4.2 Experiment Content and Result Analysis.................... 220
6.5 Summary ................................................................................. 223
References ........................................................................................ 224
Chapter 7 Application of Subpixel Mapping Technology in Remote
Sensing Imaging............................................................................... 227
7.1 Introduction ............................................................................. 227
7.2 Improving Flood Subpixel Mapping for Multispectral
Image by Supplying More Spectral Information..................... 228
7.2.1 Existing SRFIM .......................................................... 228
7.2.2 SRFIM-MSI................................................................. 230
7.2.3 Experiment Content and Result Analysis.....................231
7.3 Subpixel Mapping of Urban Buildings Based in
Multispectral Image With Spatial-Spectral Information .........235
7.3.1 Spaceborne Multispectral Remote
Sensing Image ..............................................................235
7.3.2 Experiment Content and Result Analysis.................... 236
7.4 Multispectral Subpixel Burned-Area Mapping Based
on Space-Temperature Information..........................................241
7.4.1 Space Part.....................................................................241
7.4.2 Temperature Part......................................................... 243
7.4.3 Implementation of STI................................................. 244
7.4.4 Experiment Content and Result Analysis.................... 245
7.5 Summary ................................................................................. 256
References ........................................................................................ 256
Appendix: Abbreviations......................................................................................259
Content Validity ................................................................................................... 265
Index.......................................................................................................................267
Foreword
With the rapid development of the aerospace industry in recent years, remote sensing
science, as a comprehensive technology in the aerospace feld, has been widely and
greatly developed in both theory and application. In particular, the spectral remote
sensing developed in recent years can obtain the spatial information and spectral
information of land cover classes at the same time, realize the real integration of
maps, and provide strong technical support for the aerospace industry. Remote sens-
ing technology has been successfully applied in military, civil, agricultural, marine,
smart city, disaster reduction, and other felds.
As an important research direction of remote sensing technology, remote sensing
image processing directly determines the accuracy and utilization of remote sensing
information. One of the hot issues in remote sensing image processing technology
is how to deal with mixed pixels to improve the spatial resolution of remote sensing
images. Although spectral unmixing technology can obtain the proportion (abun-
dance value) of each class in the mixed pixel, it cannot obtain the specifc spatial
distribution information of each class in the mixed pixel. Subpixel mapping (SPM)
technology, as the subsequent processing of spectral unmixing technology, decom-
poses pixels into smaller subpixels and then obtains thematic mapping with distribu-
tion information of each class at the subpixel scale. SPM, as a potential technology to
obtain land cover classes of spatial distribution information, has attracted more and
more attention.
Combined with the authors’ relatively new research achievements in this technol-
ogy, this book makes a systematic arrangement and detailed explanation and con-
tributes to readers’ understanding, learning, and research of SPM technology. In this
book, the authors compile the important theories and methods about the analysis and
processing stage in the SPM process, involve the complex technical key scientifc
issues such as multi-source information fusion and artifcial intelligence technology,
and put forward many new theories and methods of remote sensing information. It is
fascinating and refreshing to read. I would like to express my warm congratulations.
Professor Yongqi Xue
Academician of China Academy of Sciences
ix