Hyperspectral Remote Sensing Fundamentals and Practices

• Main Author: Pu, Ruiliang
• Format: eBook
• Language: English
• Published: Milton Routledge 2017; CRC Press; Taylor & Francis Group
• Edition: 1
• Series: Remote Sensing Applications Series
• Subjects: absorption; data; diagnostic; ENVIROnetBASE; ENVIRONMENTALSCIENCEnetBASE; features; Geology; Geology - Earth Sciences; GEOnetBASE; high; imaging; Land use; measurements; Natural resources; reflectance; Remote Sensing; resolution; SCI-TECHnetBASE; Spectral imaging; spectrum; STMnetBASE; ASD FieldSpec; Hyperspectral Image Data; Data Sets; LiDAR Data; Hyperspectral Imaging; Hrs; Diagnostic Absorption Features; PC Band; Spectral Unmixing; Hyperspectral Sensor; AVIRIS Sensor; Pci Geomatics; Atmospheric Correction; Hyperspectral Data; AVIRIS Image; Chla Concentration; Surface Reflectance Spectra; AOT; Aerosol Optical Depth; MTCI; End Member Spectra; AVIRIS Data; Imaging Spectrometer; Hyperspectral Data Sets; AC Method
• ISBN: 1138747173; 1498731597; 9781138747173; 9781498731591
• DOI: 10.1201/9781315120607

Advanced imaging spectral technology and hyperspectral analysis techniques for multiple applications are the key features of the book. This book will present in one volume complete solutions from concepts, fundamentals, and methods of acquisition of hyperspectral data to analyses and applications of...

Table of Contents:

• 6.7.10 Spectrum Processing Routines (SPECPR)
• 3.3.7 HySI (HyperSpectral Imager, IMS-1 satellite) -- 3.3.8 Medium-Resolution Imaging Spectrometer (MERIS), ESA ENVISAT Satellite -- 3.3.9 Moderate-Resolution Imaging Spectroradiometer (MODIS), Terra/Aqua Satellites -- 3.3.10 Environmental Mapping and Analysis Program (EnMAP) -- 3.3.11 Fluorescence Explorer (FLEX) -- 3.3.12 Hyperspectral Imager Suite (HISUI) -- 3.3.13 Hyperspectral Infrared Imager (HyspIRI) -- 3.3.14 Multisensor Microsatellite Imager (MSMI) -- 3.3.15 Hyperspectral Precursor and Application Mission (PRISMA) -- 3.4 Summary -- References -- Chapter 4: Hyperspectral Image Radiometric Correction -- 4.1 Introduction -- 4.2 Atmospheric Effects -- 4.2.1 Atmospheric Refraction -- 4.2.2 Atmospheric Scattering -- 4.2.3 Atmospheric Absorption -- 4.2.4 Atmospheric Transmittance -- 4.3 Correcting Radiometric Errors Induced by Sensors/Systems -- 4.3.1 Introduction to Radiometric Errors Caused by Sensors/Systems -- 4.3.2 De-Striping -- 4.3.3 Correcting Smile- and Keystone-Induced Errors -- 4.4 Atmospheric Correction Methods -- 4.4.1 Introduction to Atmospheric Correction -- 4.4.2 Empirical/Statistical Methods -- 4.4.2.1 The Empirical Line Calibration (ELC) -- 4.4.2.2 Internal Average Reflectance (IAR) and Flat Field Correction (FFC) -- 4.4.3 Radiative Transfer Methods -- 4.4.3.1 Atmospheric Correction Now (ACORN) -- 4.4.3.2 Atmospheric Correction (ATCOR) -- 4.4.3.3 Atmosphere Removal (ATREM) -- 4.4.3.4 Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) -- 4.4.3.5 High-Accuracy Atmospheric Correction for Hyperspectral Data (HATCH) -- 4.4.3.6 Imaging Spectrometer Data Analysis System (ISDAS) -- 4.4.3.7 Comparison -- 4.4.4 Relative Correction Methods -- 4.5 Techniques for Estimating Atmospheric Water Vapor and Aerosols -- 4.5.1 Atmospheric Water Vapor -- 4.5.1.1 Narrow/Wide (N/W) Technique
• 5.8.3.1 Linear SVM for a Separable Case -- 5.8.3.2 Linear SVM for a Nonseparable Case -- 5.8.3.3 Nonlinear SVM: Kernel Method -- 5.8.3.4 SVMs for Multiclass Classification -- 5.9 Summary -- References -- Chapter 6: Hyperspectral Data Processing Software -- 6.1 Introduction -- 6.2 ENVI -- 6.2.1 Atmospheric Correction -- 6.2.2 Building a 3D Image Cube and Plotting Spectral Curve -- 6.2.3 Data Transformation -- 6.2.4 End-Member Determination and Extraction -- 6.2.5 Spectral Unmixing -- 6.2.6 Target Detection -- 6.2.7 Mapping and Discriminant Methods -- 6.2.8 Vegetation Analysis and Suppression -- 6.3 ERDAS IMAGINE -- 6.3.1 IMAGINE Spectral Analysis Workstation -- 6.3.2 Anomaly Detection -- 6.3.3 Target Detection -- 6.3.4 Material Mapping -- 6.3.5 Material Identification -- 6.3.6 Atmospheric Adjustment -- 6.4 IDRISI -- 6.4.1 Hyperspectral Signature Development -- 6.4.2 Hyperspectral Image Classification -- 6.4.3 Extraction of Absorption Features -- 6.5 PCI Geomatics -- 6.5.1 Data Visualization -- 6.5.2 Atmospheric Correction -- 6.5.3 Hyperspectral Unmixing and Mapping -- 6.6 TNTmips -- 6.6.1 Hyperspectral Explorer Tool -- 6.6.2 Atmospheric Correction -- 6.6.3 Hyperspectral Image Transformation -- 6.6.4 Hyperspectral Unmixing and Mapping -- 6.7 Other Minor Software Tools and Programs for Processing Hyperspectral Data -- 6.7.1 DARWin -- 6.7.1.1 Set Smoothing Filter Width -- 6.7.1.2 EZ-ID Quick Material Identification Tool -- 6.7.1.3 Vegetation Indices -- 6.7.2 Hyperspectral Image Processing and Analysis System (HIPAS) -- 6.7.3 Imaging Spectrometer Data Analysis Systems (ISDAS) -- 6.7.4 Integrated Software for Imagers and Spectrometers (ISIS) -- 6.7.5 MATLAB® -- 6.7.6 MultiSpec -- 6.7.7 Optical Real-Time Adaptive Spectral Identification System (ORASIS) -- 6.7.8 Processing Routines in IDL for Spectroscopic Measurements (PRISM) -- 6.7.9 SPECMIN
• Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Foreword -- Preface -- Acknowledgments -- Author -- Introduction -- Chapter 1: Overview of Hyperspectral Remote Sensing -- 1.1 Concepts of Imaging Spectroscopy -- 1.1.1 Spectroscopy -- 1.1.2 Imaging Spectroscopy -- 1.1.3 Hyperspectral Remote Sensing -- 1.1.4 Differences between Hyperspectral and Multispectral Imaging -- 1.1.5 Absorption Features and Diagnostic Spectral Features -- 1.2 Development of Hyperspectral Remote Sensing -- 1.3 Overview of Hyperspectral Remote Sensing Applications -- 1.3.1 Geology and Soils -- 1.3.2 Vegetation and Ecosystems -- 1.3.3 The Atmosphere -- 1.3.4 Coastal and Inland Waters -- 1.3.5 Snow and Ice Hydrology -- 1.3.6 Environmental Hazards -- 1.3.7 Urban Environments -- 1.4 Perspective of Hyperspectral Remote Sensing -- 1.5 Summary -- References -- Chapter 2: Field Spectrometers and Plant Biology Instruments for HRS -- 2.1 Non-Imaging Field Spectrometers -- 2.1.1 Introduction -- 2.1.2 Principles of Field Spectroscopy and General Guidelines on Field Techniques -- 2.1.2.1 Principles of Field Spectroscopy -- 2.1.2.2 General Guidelines on Field Technique -- 2.1.3 Field Spectrometers -- 2.1.3.1 ASD Field Spectroradiometers -- 2.1.3.2 SVC (GER) Field Spectroradiometers -- 2.1.3.3 Spectral Evolution Field Spectroradiometers -- 2.1.3.4 SpectraScan Spectroradiometers -- 2.1.3.5 Ocean Optical Spectrometers -- 2.2 Plant Biology Instruments for HRS -- 2.2.1 Introduction -- 2.2.2 Plant Biology Instruments -- 2.2.2.1 Instruments for Measuring Leaf Area and Leaf Area Index -- 2.2.2.2 Instruments for Measuring Photosynthesis and fPAR -- 2.2.2.3 Instruments for Measuring Chlorophyll Content -- 2.3 Summary -- References -- Chapter 3: Imaging Spectrometers, Sensors, Systems, and Missions -- 3.1 Working Principles of Imaging Spectrometry
• 4.5.1.2 Continuum Interpolated Band Ratio (CIBR) -- 4.5.1.3 Three-Band Ratioing (3BR) -- 4.5.1.4 Linear Regression Ratio (LIRR) -- 4.5.1.5 Atmospheric Pre-Corrected Differential Absorption (APAD) -- 4.5.2 Atmospheric Aerosols -- 4.5.2.1 Dark Dense Vegetation (DDV) Technique -- 4.5.2.2 Aerosol Optical Thickness at 550 nm (AOT at 550 nm) -- 4.6 Summary -- References -- Chapter 5: Hyperspectral Data Analysis Techniques -- 5.1 Introduction -- 5.2 Spectral Derivative Analysis -- 5.3 Spectral Similarity Measures -- 5.3.1 Cross-Correlogram Spectral Matching (CCSM) -- 5.3.2 Spectral Angle Matching (SAM) -- 5.3.3 Euclidian Distance (ED) -- 5.3.4 Spectral Information Divergence (SID) -- 5.4 Spectral Absorption Features and Wavelength Position Variables -- 5.4.1 Four-Point Interpolation -- 5.4.2 Polynomial Fitting -- 5.4.3 Lagrangian Technique -- 5.4.4 IG Modeling -- 5.4.5 Linear Extrapolation -- 5.5 Spectral Vegetation Indices -- 5.6 Hyperspectral Transformation and Feature Extraction -- 5.6.1 Principal Components Analysis (PCA) -- 5.6.2 Signal-to-Noise Ratio-Based Image Transforms -- 5.6.2.1 Maximum Noise Fraction (MNF) Transform -- 5.6.2.2 Noise-Adjusted Principal Component Transform -- 5.6.3 Independent Component Analysis -- 5.6.4 Canonical Discriminant Analysis (CDA) -- 5.6.5 Wavelet Transform -- 5.7 Spectral Mixture Analysis (SMA) -- 5.7.1 Traditional Spectral Unmixing Modeling Techniques -- 5.7.2 Artificial Neural Networks Solution to LSM -- 5.7.3 Multiple End-Member Spectral Mixture Analysis (MESMA) -- 5.7.4 Mixture-Tuned Matched Filtering Technique (MTMF) -- 5.7.5 Constrained Energy Minimization (CEM) -- 5.7.6 End-Member Extraction -- 5.7.6.1 Pixel Purity Index (PPI) -- 5.7.6.2 N-Finder -- 5.8 Hyperspectral Image Classifications -- 5.8.1 Segment-Based Multispectral Classifiers -- 5.8.2 Artificial Neural Networks (ANN) -- 5.8.3 Support Vector Machines
• 3.1.1 Whiskbroom Imaging Spectrometry -- 3.1.2 Pushbroom Imaging Spectrometry -- 3.2 Airborne Hyperspectral Sensors/Systems -- 3.2.1 Advanced Airborne Hyperspectral Imaging Sensor (AAHIS) -- 3.2.2 Airborne Imaging Spectrometer (AIS) -- 3.2.3 Airborne Imaging Spectrometer for Different Applications (AISA) -- 3.2.4 Advanced Solid-State Array Spectroradiometer (ASAS) -- 3.2.5 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) -- 3.2.6 Compact Airborne Spectrographic Imager (CASI) -- 3.2.7 Compact High-Resolution Imaging Spectrograph Sensor (CHRISS) -- 3.2.8 Digital Airborne Imaging Spectrometers (DAIS 7915, 16115) -- 3.2.9 Fluorescence Line Imager (FLI) -- 3.2.10 Hyperspectral Digital Imagery Collection Experiment (HYDICE) -- 3.2.11 Hyperspectral Mapper (HyMap) -- 3.2.12 HyperSpectral Cameras (HySpex) -- 3.2.13 Infrared Imaging Spectrometer (ISM) -- 3.2.14 Modular Airborne Imaging Spectrometer (MAIS) -- 3.2.15 Modular Imaging Spectrometer Instrument (MISI) -- 3.2.16 Multispectral Infrared Camera (MUSIC) -- 3.2.17 Probe-1 -- 3.2.18 Reflective Optics System Imaging Spectrometer (ROSIS) -- 3.2.19 SWIR Full Spectrographic Imager (SFSI) -- 3.2.20 Spatially Modulated Imaging Fourier Transform Spectrometer (SMIFTS) -- 3.2.21 TRW Imaging Spectrometers (TRWIS) -- 3.2.22 Variable Interference Filter Imaging Spectrometer (VIFIS) -- 3.2.23 Wedge Imaging Spectrometer (WIS) -- 3.3 Spaceborne Hyperspectral Sensors/Missions -- 3.3.1 Advanced Responsive Tactically Effective Military Imaging Spectrometer (ARTEMIS), TacSat-3 Satellite -- 3.3.2 Compact High-Resolution Imaging Spectrometer (CHRIS), PROBA Satellite -- 3.3.3 Fourier Transform Hyperspectral Imager (FTHSI), MightySat II Satellite -- 3.3.4 Global Imager (GLI), NASDA ADEOS-II Satellite -- 3.3.5 HJ-A/HSI (Hyperspectral Imager, HJ-1A Satellite) -- 3.3.6 Hyperion (Hyperspectral Imager, EO-1 Satellite)