Skip to content

Synthetic Aperture Radar Polarimetry

Spend $50 to get a free DVD!

ISBN-10: 1118115112

ISBN-13: 9781118115114

Edition: 2011

Authors: Jakob J. van Zyl

Shipping box This item qualifies for FREE shipping.
Blue ribbon 30 day, 100% satisfaction guarantee!
what's this?
Rush Rewards U
Members Receive:
Carrot Coin icon
XP icon
You have reached 400 XP and carrot coins. That is the daily max!

Description:

This book describes the application of polarimetric synthetic aperture radar to earth remote sensing based on research at the NASA Jet Propulsion Laboratory (JPL). This book synthesizes all current research to provide practical information for both the newcomer and the expert in radar polarimetry. The text offers a concise description of the mathematical fundamentals illustrated with many examples using SAR data, with a main focus on remote sensing of the earth. The book begins with basics of synthetic aperture radar to provide the basis for understanding how polarimetric SAR images are formed and gives an introduction to the fundamentals of radar polarimetry. It goes on to discuss more advanced polarimetric concepts that allow one to infer more information about the terrain being imaged. In order to analyze data quantitatively, the signals must be calibrated carefully, which the book addresses in a chapter summarizing the basic calibration algorithms. The book concludes with examples of applying polarimetric analysis to scattering from rough surfaces, to infer soil moisture from radar signals.
Customers also bought

Book details

Copyright year: 2011
Publisher: John Wiley & Sons, Incorporated
Publication date: 11/15/2011
Binding: Hardcover
Pages: 312
Size: 6.50" wide x 9.50" long x 1.00" tall
Weight: 1.408
Language: English

Note From The Series Editor
Foreword
Preface
Acknowledgments
Authors
Synthetic Aperture Radar (Sar) Imaging Basics
Basic Principles Of Radar Imaging
Radar Resolution
Radar Equation
Real Aperture Radar
Synthetic Aperture Radar
Radar Image Artifacts And Noise
Range And Azimuth Ambiguities
Geometric Effects And Projections
Signal Fading And Speckle
Summary
Basic Principles Of Sar Polarimetry
Polarization of Electromagnetic Waves
Mathematical Representations of Scatterers
Implementation of a Radar Polarimeter
Polarization Response
Optimum Polarizations
General (Bistatic) Case
Backscatter (Monostatic) Case
Special Case: Single Scatterer in Backscatter (Monostatic) Case
Special Case: Multiple Scatterers with Reflection Symmetry
A Numerical Example
Contrast Enhancement
Numerical Example
Image Example
Summary
Advanced Polarimetric Concepts
Vector-Matrix Duality of Scatterer Representation
Eigenvalue- and Eigenvector-Based Polarimetric Parameters
Parameters Used to Describe Randomness in Scattering
Alpha Angle
Decomposition of Polarimetric Scattering
Scattering Decomposition in the Incoherent Case Using Orthonormal Bases
Model-Based Scattering Decomposition in the Incoherent Case
Image Classification
Supervised Classification
Physics-Based Unsupervised Classification
Combined Unsupervised and Bayes Classification Algorithms
Polarimetric SAR Interferometry
Summary
Polarimetric Sar Calibration
Polarimetric Radar System Model
Cross Talk Estimation and Removal
Copolarized Channel Imbalance Calibration
Absolute Radiometric Calibration
Effect of Topography on Scattering Area
Effect of Topography on Antenna Pattern Corrections
AIRSAR Image Example
Faraday Rotation
Summary
Applications: Measurement Of Surface Soil Moisture
Surface Electrical and Geometrical Properties
Geometrical Properties
Electrical Properties
Penetration Depth
Soil Moisture Profile
Scattering from Bare Rough Surfaces
First-Order Small-Perturbation Model
The Integral Equation Model
Example Bare Surface Soil Moisture Inversion Models
The First-Order Small-Perturbation Model
Algorithm Proposed by Oh et al. (1992)
Algorithm Proposed by Dubois et al.
Algorithm Proposed by Shi etal. (1997)
Comparison of the Performance of Bare Surface Inversion Models
Parameterizing Scattering Models
Inverting the IEM Model
Scattering from Vegetated Terrain
Scattering from the Vegetation Layer (Scattering Path 1)
Backscatter from the Underlying Ground Surface (Scattering Path 4)
Double-Reflection Scattering (Scattering Paths 2 and 3)
Simulation Results
Effect of the Angle of Incidence
Effect of Cylinder Radius
Effect of Cylinder Moisture
Radar Vegetation Index
Effect of Soil Moisture
Inverting for Soil Moisture: the Data Cube
Time Series Estimation of Soil Moisture
Summary
Appendixes
Tilted Small Perturbation Model Details
Bistatic Scattering Matrix Of A Cylinder With Arbitrary Orientation
Nomenclature
Index