Radar Remote Sensing

9.

SAR Data Processing Workflow

9.1.

Data Preprocessing

9.1.1.

Data Import and Format Handling

9.1.1.1.

Standard Formats

9.1.1.2.

Metadata Extraction

9.1.1.3.

Quality Assessment

9.1.2.

Radiometric Preprocessing

9.1.2.1.

Radiometric Calibration

9.1.2.1.1.

Calibration Constants

9.1.2.1.2.

Antenna Pattern Correction

9.1.2.1.3.

Range Spreading Loss

9.1.2.2.

9.1.2.2.1.

Thermal Noise Subtraction

9.1.2.2.2.

System Noise Characterization

9.1.3.

Geometric Preprocessing

9.1.3.1.

Orbit State Vector Processing

9.1.3.2.

Timing Corrections

9.1.3.3.

Geometric Calibration

9.2.

Image Enhancement

9.2.1.

Speckle Filtering

9.2.1.1.

Adaptive Filters

9.2.1.1.1.

9.2.1.1.2.

9.2.1.1.3.

9.2.1.2.

Non-Local Filters

9.2.1.2.1.

Non-Local Means

9.2.1.2.2.

9.2.1.3.

Wavelet-Based Filters

9.2.2.

9.2.2.1.

Spatial Multi-Looking

9.2.2.2.

Temporal Multi-Looking

9.2.2.3.

Resolution Considerations

9.3.

Geometric Correction

9.3.1.

Terrain Correction

9.3.1.1.

Range-Doppler Terrain Correction

9.3.1.2.

DEM Requirements

9.3.1.3.

Layover and Shadow Masking

9.3.2.

Orthorectification

9.3.2.1.

9.3.2.2.

Resampling Methods

9.3.2.3.

Accuracy Assessment

9.3.3.

9.3.3.1.

Coordinate Transformation

9.3.3.2.

9.3.3.3.

Geographic Reference Systems

9.4.

Information Extraction

9.4.1.

Feature Extraction

9.4.1.1.

Statistical Features

9.4.1.1.1.

First-Order Statistics

9.4.1.1.2.

Second-Order Statistics

9.4.1.1.3.

Higher-Order Statistics

9.4.1.2.

Textural Features

9.4.1.2.1.

Gray Level Co-occurrence Matrix

9.4.1.2.2.

Local Binary Patterns

9.4.1.2.3.

9.4.1.3.

Polarimetric Features

9.4.1.3.1.

Decomposition Parameters

9.4.1.3.2.

Polarimetric Indices

9.4.1.3.3.

Scattering Mechanisms

9.4.2.

Classification Methods

9.4.2.1.

Pixel-Based Classification

9.4.2.1.1.

Maximum Likelihood

9.4.2.1.2.

Support Vector Machines

9.4.2.1.3.

9.4.2.2.

Object-Based Classification

9.4.2.2.1.

9.4.2.2.2.

Object Features

9.4.2.2.3.

Rule-Based Classification

9.4.2.3.

Deep Learning Approaches

9.4.2.3.1.

Convolutional Neural Networks

9.4.2.3.2.

Transfer Learning

9.4.2.3.3.

Data Augmentation

9.4.3.

Change Detection

9.4.3.1.

Pre-Processing for Change Detection

9.4.3.2.

Change Detection Methods

9.4.3.2.1.

Image Differencing

9.4.3.2.2.

Change Vector Analysis

9.4.3.2.3.

Post-Classification Comparison

9.4.3.3.

Coherence Change Detection

9.4.3.4.

Multi-Temporal Analysis

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10. Applications in Earth System Science