TY  - BOOK
AU  - Dave,  Bindi Satyam (DP3111)
AU  - Mohan, Shiv (Guide)
TI  - Multi-temporal C-band polarimetric SAR data for agricultural crop classification (Softcopy is also available)
U1  - Ph.D. TH-0062 
PY  - 2017///
N1  - CONTENTS
Undertaking i
Certificate iii
Acknowledgement v 
Abstract vii
Table of Contents x
List of Figures xiii
List of Tables xviii
Abbreviations xx
1 Introduction                                      1
1.1 Background and state of art 1
1.2 Scope and Objectives.9
1.3 Overview of Dissertation 10
2 Microwave Remote Sensing                             12
2.1 Introduction to Microwave Remote Sensing 12
2.1.1 Advantages of Microwave Remote Sensing 14
2.1.2 Factors affecting radar returns 14
2.2 Imaging Radar 20
2.3 Synthetic Aperture Radar 23
2.4 Radar Polarimetry 23
2.4.1 Radar Polarimetry concepts 23
2.4.2 Theory of Radar Polarimetry 25
2.4.2.1 Introduction to EM waves and their properties 25
2.4.2.2 The Polarization Ellipse 25
2.4.2.3 The Polarization State 27
2.4.3 Concepts of Full, Dual and Hybrid Polarimetry 28
2.4.4 Backscattering Coefficient of Various Land Features 31
2.5 Image Classification 34
2.5.1 Supervised Maximum Likelihood classification35
2.5.2 Supervised Wishart Classification37
Multi-Temporal C-band Polarimetric SAR Data for Agricultural Crop Classificationxi
3 Polarimetric Parameters 38
3.1 Polarization Amplitude Ratio 38
3.1.1 Co-polarized Amplitude Ratio 38
3.1.2 Cross polarized Amplitude Ratio 39
3.2 Total Power (Span) 39
3.3 Entropy, Anisotropy, Alpha (HAα)39
3.4 Radar Vegetation Index (RVI) 40
4 Polarimetric Decomposition Theorems 42
4.1 Backscattered Waves 42
4.2 The Scattering matrix 43
4.3 The Covariance and Coherency Matrices 44
4.4 Polarimetric Target Decomposition 46
4.4.1 Coherent Decomposition Theorems 47
4.4.1.1 Pauli’s Decomposition Theorem 48
4.4.2 Incoherent Decomposition Theorems 49
4.4.2.1 Freeman Durden’s Three Component Decomposition Theorem 51
4.4.2.2 Eigen Vector Based (H/A/α) Decomposition theorem53
5 Study Area, Data Used and Methodology 56
5.1 Study Area 56
5.2 Data Used 60
5.3 Ground Truth Data Collection 62
5.4 Methodology 66
6 Results and Discussions 71
6.1 Multi-temporal and Multi-polarimetric data analysis 71
6.1.1 Vegetation and Land Feature Discrimination using Multi-temporal/date stack in
HH, HV and VV Polarization71
6.1.1.1 Temporal Profile of major Kharif Crops and other land uses in HH and HV
polarization 73
6.1.2 Crop type and surrounding landuse discrimination using Temporal Multi-
Polarimetric Data 77
Multi-Temporal C-band Polarimetric SAR Data for Agricultural Crop Classification xii
6.1.3 Classification accuracy assessment of full, dual and hybrid polarimetric data 79
6.2 Evaluation of various polarimetric parameters for crop type and surrounding landuse
classification 85
6.2.1 Span (Total Power) Analysis 85
6.2.2 Radar Vegetation Index (RVI) Analysis 88
6.2.3 Eigen Values Analysis 90
6.2.4 Polarization Amplitude Ratio Analysis 92
6.2.5 Classification accuracy evaluation of Polarimetric parameters 95
6.3 Temporal Change in Scattering behaviour of various crop types and surrounding
landuse based on polarimetric decomposition theorems 96
6.3.1 Freeman Durden Decomposition Analysis 96
6.3.2 Pauli Decomposition Analysis 99
6.3.3 HAα (Entropy, Anisotropy, Alpha) Decomposition analysis.101
6.3.3.1 Entropy (H) 101
6.3.3.2 Anisotropy (A).103
6.3.3.3 Alpha angle (α)104
6.3.4 Classification accuracy for Polarimetric decompositions 106
6.4 Comparing and validating results of Full polarimetric, Dual and Hybrid polarimetric
SAR data, Polarimetric parameters and Decomposition techniques108
7 Conclusion 111
References 115

ER  -