Getting Started

Installation

From PyPI

pip install eq-insar

From Source

git clone https://github.com/kcieslik/eq-insar.git
cd eq-insar
pip install .

Optional Dependencies

Install extras for additional features:

# Visualization (matplotlib)
pip install eq-insar[viz]

# GeoTIFF export (rasterio)
pip install eq-insar[geotiff]

# NetCDF export (netCDF4)
pip install eq-insar[netcdf]

# All optional dependencies
pip install eq-insar[all]

# Development (pytest, coverage)
pip install eq-insar[dev]

Quick Start

Generate a Single Interferogram

from eq_insar import generate_synthetic_insar, plot_displacement_components

# Mw 6.0 thrust earthquake with Sentinel-1 geometry
result = generate_synthetic_insar(
    Mw=6.0,
    strike_deg=30,
    dip_deg=45,
    rake_deg=90,          # thrust fault
    depth_km=10,
    satellite='sentinel1',
    orbit='ascending'
)

# Access the data
los_displacement = result['los_displacement']  # (height, width) array
wrapped_phase = result['wrapped_phase']        # (height, width) array
unwrapped_phase = result['unwrapped_phase']    # (height, width) array

# Visualize (requires matplotlib)
fig = plot_displacement_components(result)

Generate Time Series for ML Training

from eq_insar import generate_timeseries

result = generate_timeseries(
    Mw=6.0,
    satellite='sentinel1',
    n_pre=5,      # pre-event frames (noise only)
    n_event=1,    # event frames (signal + noise)
    n_post=5      # post-event frames (noise only)
)

X = result['timeseries']  # (11, height, width)
y = result['labels']      # binary segmentation masks

Batch Generation for ML Pipelines

from eq_insar import generate_training_batch, batch_to_arrays

batch = generate_training_batch(
    n_samples=100,
    Mw_range=(5.0, 7.0),
    satellite='sentinel1',
    seed=42
)

X, y = batch_to_arrays(batch)
# X: (100, T, H, W) - input time series
# y: (100, T, H, W) - segmentation labels

Fault Geometry Convention

EQ-INSAR uses the Aki & Richards (2002) convention:

Parameter	Range	Description
Strike	0-360deg	Clockwise from North
Dip	0-90deg	From horizontal
Rake	-180 to 180deg	Slip direction

Rake angle meanings:

• 0deg — Left-lateral strike-slip
• 90deg — Thrust/reverse
• +/-180deg — Right-lateral strike-slip
• -90deg — Normal fault

Supported Satellites

Satellite	Band	Wavelength	Default Incidence	Agency
Sentinel-1	C	5.5 cm	33deg	ESA
ALOS-2	L	22.9 cm	35deg	JAXA
TerraSAR-X	X	3.1 cm	35deg	DLR
COSMO-SkyMed	X	3.1 cm	35deg	ASI
RADARSAT-2	C	5.5 cm	35deg	CSA
NISAR	L	23.8 cm	35deg	NASA/ISRO
SAOCOM	L	23.5 cm	35deg	CONAE
ENVISAT	C	5.6 cm	23deg	ESA
ICEYE	X	3.1 cm	30deg	ICEYE

from eq_insar import list_satellites, get_satellite

# List all satellites
print(list_satellites())

# Get specific satellite configuration
sentinel1 = get_satellite('sentinel1')
print(f"Wavelength: {sentinel1.wavelength_m * 100:.2f} cm")

Next Steps

• Browse the API Reference for detailed function documentation
• Check out the Examples for Jupyter notebooks