13284nam 22009133 450 991047345600332120231110232324.03-030-56504-1(CKB)4100000011807252(MiAaPQ)EBC6531842(Au-PeEL)EBL6531842(OCoLC)1244535943(oapen)https://directory.doabooks.org/handle/20.500.12854/67916(PPN)254719422(EXLCZ)99410000001180725220210901d2021 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierPolarimetric Synthetic Aperture Radar Principles and ApplicationSpringer Nature2021Cham :Springer International Publishing AG,2021.©2021.1 online resource (304 pages)Remote Sensing and Digital Image Processing ;v.253-030-56502-5 Intro -- Foreword -- Preface -- Pioneering Space-Borne SAR Interferometry -- Organising Airborne Polarimetric SAR Campaigns and Scientific Studies -- Dialoguing with POLinSAR Scientists and Training the Next Generation -- Pioneering Space-Borne SAR Polarimetric Interferometry -- Future Missions -- From Science to Applications -- Outlook -- In Memoriam -- Contents -- Symbols -- 1: Basic Principles of SAR Polarimetry -- 1.1 Theory of Radar Polarimetry -- 1.1.1 Wave Polarimetry -- 1.1.1.1 Electromagnetic Waves and Wave Polarization Descriptors -- 1.1.1.2 Totally and Partially Polarized Waves -- 1.1.1.3 Change of Polarization Basis -- 1.1.2 Scattering Polarimetry -- 1.1.2.1 The Scattering Matrix -- 1.1.2.2 Scattering Polarimetry Descriptors -- 1.1.2.3 Partial Scattering Polarimetry -- 1.1.2.4 Change of Polarization Basis -- 1.1.2.5 Scatterers Characterization by Single, Dual, Compact and Full Polarimetry -- 1.2 SAR Data Statistical Description and Speckle Noise Filtering -- 1.2.1 One-Dimensional Gaussian Distribution -- 1.2.2 Multidimensional Gaussian Distribution -- 1.2.3 The Wishart Distribution -- 1.2.4 The Polarimetric Covariance and Coherency Matrix -- 1.2.5 The Polarimetric Coherence -- 1.2.6 Polarimetric Speckle Noise Filtering -- 1.2.6.1 PolSAR Speckle Noise Filtering Principles -- 1.2.6.2 PolSAR Speckle Noise Filtering Alternatives -- 1.3 Polarimetric Scattering Decomposition Theorems -- 1.3.1 Coherent Scattering Decomposition Techniques -- 1.3.1.1 The Pauli Decomposition -- 1.3.2 Incoherent Scattering Decompositions Techniques -- 1.3.2.1 Three-Component Freeman Decomposition -- 1.3.2.2 Four-Component Yamaguchi Decomposition -- 1.3.2.3 Non-negative Eigenvalue Decomposition -- 1.3.2.4 Eigenvector-Eigenvalue-Based Decomposition -- 1.3.2.5 The Touzi Target Scattering Decompositions -- 1.4 Polarimetric SAR Interferometry.1.4.1 SAR Interferometry -- 1.4.2 Algorithms for Optimum Interferogram Generation -- 1.4.3 Model-Based Polarimetric SAR Interferometry -- 1.4.3.1 PolInSAR for Bare Surface Scattering -- 1.4.3.2 PolInSAR for Random Volume Scattering -- 1.4.3.3 PolInSAR Two-Layer Combined Surface and Random Volume Scattering -- 1.5 Polarimetric SAR Tomography -- 1.5.1 TomoSAR and PolTomoSAR as Spectral Estimation Problems: Non-model-Based Adaptive Solutions -- 1.5.2 Model-Based PolTomoSAR -- 1.5.3 Coherence Tomography -- References -- 2: Forest Applications -- 2.1 Introduction -- 2.2 Forest Classification -- 2.2.1 Land Cover Classification in Tropical Lands Using PolSAR -- 2.2.1.1 Introduction, Motivation and Literature Review -- 2.2.1.2 Methodology -- 2.2.1.3 Experimental Results -- 2.2.1.4 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 2.2.2 Forest Mapping and Classification Using Polarimetric and Interferometric Data -- 2.2.2.1 Introduction, Motivation and Literature Review -- 2.2.2.2 Methodology -- 2.2.2.3 Experimental Results -- 2.2.2.4 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 2.2.3 Detection of Fire Scars -- 2.2.3.1 Introduction, Motivation and Literature Review -- 2.2.3.2 Methodology -- 2.2.3.3 Experimental Results -- 2.2.3.4 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 2.3 Forest Height Estimation -- 2.3.1 Introduction, Motivation and Literature Review -- 2.3.2 Methodology -- 2.3.2.1 Random-Volume-Over-Ground Inversion -- 2.3.2.2 Non-volumetric Decorrelation Contributions -- 2.3.3 Experimental Results -- 2.3.4 Comparison with Single/Dual Polarimetric Data -- 2.3.5 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions.2.4 Forest Vertical Structure Estimation Using Multi-baseline Polarimetric SAR Acquisitions -- 2.4.1 Polarimetric SAR Tomography -- 2.4.1.1 Introduction, Motivation and Literature Review -- 2.4.1.2 Methodology -- 2.4.1.3 Experimental Results -- 2.4.1.4 Comparison with Single/Dual Polarization Data -- 2.4.1.5 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 2.4.2 Estimation of Vegetation Structure Parameters -- 2.4.2.1 Introduction, Motivation and Literature Review -- 2.4.2.2 Methodology -- 2.4.2.3 Experimental Results -- 2.4.2.4 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 2.5 Biomass Estimation -- 2.5.1 Biomass Estimation: A Review -- 2.5.1.1 Introduction, Motivation -- 2.5.1.2 Methodology -- 2.5.1.2.1 Direct Biomass Estimation -- 2.5.1.2.2 Model-Based Estimation -- 2.5.1.2.3 Allometric Biomass Estimation -- 2.5.1.3 Experimental Results -- 2.5.1.4 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 2.5.2 Biomass Estimation from Semi-empirical Relationships -- 2.5.2.1 Introduction, Motivation and Literature Review -- 2.5.2.2 Methodology -- 2.5.2.3 Experimental Results -- 2.5.2.4 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 2.6 Summary -- References -- 3: Agriculture and Wetland Applications -- 3.1 Introduction -- 3.2 Crop Type Mapping -- 3.2.1 Evaluation of C-Band Polarimetric SAR for Crop Classification -- 3.2.1.1 Introduction, Motivation and Literature Review -- 3.2.1.2 Methodology -- 3.2.1.3 Experimental Results -- 3.2.1.4 Comparison with Single-/Dual-Polarisation Data -- 3.2.1.5 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 3.2.2 Crop Classification Using Multitemporal L- and C-Band Airborne Polarimetric SAR.3.2.2.1 Introduction, Motivation and Literature Review -- 3.2.2.2 Methodology -- 3.2.2.3 Experimental Results -- 3.2.2.4 Comparison with Single-/Dual-Polarisation Data -- 3.2.2.5 Discussion on the Role of Polarimetry on the Maturity of the Application and Conclusions -- 3.3 Soil Moisture Estimation Under Vegetation Using SAR Polarimetry -- 3.3.1 Introduction, Motivation and Literature Review -- 3.3.2 Methodology -- 3.3.3 Experimental Results -- 3.3.4 Comparison with Single-/Dual-Pol Data -- 3.3.5 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusion -- 3.4 Crop Phenology Estimation Using SAR Polarimetry -- 3.4.1 Introduction, Motivation and Literature Review -- 3.4.2 Methodology -- 3.4.3 Experimental Results -- 3.4.3.1 Analysis -- 3.4.3.1.1 Cereals -- 3.4.3.1.2 Canola -- 3.4.3.1.3 Field Pea -- 3.4.3.2 Retrieval Algorithms -- 3.4.3.3 Results and Validation -- 3.4.3.3.1 Wheat -- 3.4.3.3.2 Oat -- 3.4.3.3.3 Barley -- 3.4.4 Comparison with Single-/Dual-Polarisation Data -- 3.4.5 Discussion on Role of Polarimetry, on the Maturity of the Application and Conclusions -- 3.5 Wetland Observation -- 3.5.1 C-Band Polarimetric Time Series for Delineating and Monitoring Seasonal Dynamics of Wetlands -- 3.5.1.1 Introduction, Motivation and Literature Review -- 3.5.1.2 Methodology -- 3.5.1.3 Experimental Results -- 3.5.1.4 Comparison with Single-/Dual-Polarisation Data -- 3.5.1.5 Discussion on the Role of Polarisation, on the Maturity of the Application and Conclusions -- 3.5.2 Tropical Wetland Characterisation with Polarimetric SAR -- 3.5.2.1 Introduction, Motivation and Literature Review -- 3.5.2.2 Methodology -- 3.5.2.3 Experimental Results -- 3.5.2.4 Comparison with Single-/Dual-Polarisation Data -- 3.5.2.5 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions.3.5.3 Subarctic Peatland Characterisation and Monitoring -- 3.5.3.1 Introduction, Motivation and Literature Review -- 3.5.3.2 Experimental Results -- 3.5.3.2.1 La Baie des Mines -- Peatland Hydrology Characteristics for Bog-Fen Discrimination -- Application of the Touzi Decomposition to Polarimetric ALOS Data: Required Processing Window Size for Unbiased ICTD -- Analysis of the ALOS Acquisitions -- Peatland Subsurface Water Flow Monitoring Using Polarimetric May and November ALOS Acquisitions: Multi-polarisation Versus Pol... -- 3.5.3.2.2 Wapusk National Park -- 3.5.3.3 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 3.5.3.4 Acknowledgement -- 3.6 Monitoring Change Detection Produced by Tsunamis and Earthquakes by Using a Fully Polarimetric Model-Based Decomposition -- 3.6.1 Introduction, Motivation and Literature Review -- 3.6.2 Methodology -- 3.6.3 Experimental Results -- 3.6.4 Comparison with Single-/Dual-Polarisation Data -- 3.6.5 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions -- 3.7 Summary (Table 3.13) -- References -- 4: Cryosphere Applications -- 4.1 Introduction -- 4.2 Land Ice Extinction Estimation Using PolInSAR -- 4.2.1 Introduction, Motivation, and Literature Review -- 4.2.2 Methodology -- 4.2.3 Experimental Results -- 4.2.4 Comparison with Single/Dual Polarisation Data -- 4.2.5 Discussion on the Role of Polarimetry, on the Maturity of the Application, and Conclusions -- 4.3 Snow Water Equivalent Retrieval -- 4.3.1 Introduction, Motivation, and Literature Review -- 4.3.2 Methodology -- 4.3.2.1 Polarimetric Decomposition for Snow-Covered Areas -- 4.3.2.2 Snow Water Equivalent Retrieval Algorithm -- 4.3.3 Experimental Results -- 4.3.4 Comparison with Single/Dual Polarisation Data.4.3.5 Discussion on the Role of Polarimetry, on the Maturity of the Application and Conclusions.This open access book focuses on the practical application of electromagnetic polarimetry principles in Earth remote sensing with an educational purpose. In the last decade, the operations from fully polarimetric synthetic aperture radar such as the Japanese ALOS/PalSAR, the Canadian Radarsat-2 and the German TerraSAR-X and their easy data access for scientific use have developed further the research and data applications at L,C and X band. As a consequence, the wider distribution of polarimetric data sets across the remote sensing community boosted activity and development in polarimetric SAR applications, also in view of future missions. Numerous experiments with real data from spaceborne platforms are shown, with the aim of giving an up-to-date and complete treatment of the unique benefits of fully polarimetric synthetic aperture radar data in five different domains: forest, agriculture, cryosphere, urban and oceans.Remote Sensing and Digital Image Processing Geographical information systems (GIS) & remote sensingbicsscOther technologies & applied sciencesbicsscTeaching of a specific subjectbicsscAgricultural sciencebicsscForestry & silviculture: practice & techniquesbicsscUrban & municipal planningbicsscRemote Sensing/PhotogrammetrySignal, Image and Speech ProcessingScience EducationAgricultureForestryUrban Geography / Urbanism (inc. megacities, cities, towns)Digital and Analog Signal ProcessingUrban Geography and UrbanismEarth Remote SensingPolSARproRadar PolarimetryRadar Polarimetry ToolboxSynthetic Aperture RadarOpen AccessGeographical information systems & remote sensingImaging systems & technologySignal processingTeaching of a specific subjectScience: general issuesAgricultural scienceForestry & silviculture: practice & techniquesUrban & municipal planningGeographical information systems (GIS) & remote sensingOther technologies & applied sciencesTeaching of a specific subjectAgricultural scienceForestry & silviculture: practice & techniquesUrban & municipal planningHajnsek Irena1023231Desnos Yves-Louis1023232MiAaPQMiAaPQMiAaPQBOOK9910473456003321Polarimetric Synthetic Aperture Radar2430794UNINA