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InSARHub

InSARHub is a modular Python framework for automated InSAR and time-series processing.

The primary goal of this package is to provide a streamlined and user-friendly InSAR processing experience across multiple satellite products.

Table of Contents

Web UI

InSARHub includes a self-hosted web interface that covers the full InSAR workflow — from scene search and download through interferogram processing to time-series analysis.

insarhub-app

Open http://localhost:8000 to access the UI.

Features

Panel What it does
Search & Download Draw an AOI on the map, search Sentinel-1 SLC stacks, download scenes and precise orbit files
Processor Build and edit the interferogram pair network with quality scoring; view S1 coherence decay maps; submit to HyP3; monitor and download results
Analyzer Run MintPy time-series analysis step by step; edit the network post-ingest; inspect diagnostic overview layers
Results Viewer Overlay the velocity map on the basemap; click any pixel to plot its displacement time series

All data stays on your machine — InSARHub runs a local FastAPI server and delivers a modern React frontend directly in your browser.

See the Web UI documentation for a full walkthrough.

InSARHub Web UI Pair Network Editor

Installation

InSARHub can be installed using Conda:

conda install insarhub -c conda-forge

Pip:

conda install gdal -c conda-forge
pip install insarhub

From source:

git clone https://github.com/jldz9/InSARHub.git
cd InSARHub
conda env create -f environment.yml -n insarhub_dev 
conda activate insarhub_dev
pip install -e .

Requirements

  • Python >=3.11,<3.13
  • numpy <2.0
  • proj >=9.4
  • gdal >=3.8
  • sqlite >=3.44
  • mintpy
  • asf_search
  • colorama
  • contextily
  • dem_stitcher
  • hyp3_sdk
  • rasterio >=1.4
  • sentineleof
  • pyproj
  • fastapi
  • uvicorn
  • python-multipart

Usage

Downloader:

from insarhub import Downloader
  • View available downloaders

    Downloader.available()
  • Create downloader

    dl = Downloader.create('S1_SLC',
                            intersectsWith=[-113.05, 37.74, -112.68, 38.00],
                            start='2020-01-01',
                            end='2020-12-31',
                            relativeOrbit=100,
                            frame=466,
                            workdir='path/to/dir')
  • Search

    results = dl.search()
  • Filter

    filter_result = dl.filter(start='2020-02-01')
  • Select interferogram pairs

    from insarhub.utils import plot_pair_network
    pairs, baselines, scene_bperp = dl.select_pairs(dt_max=96, pb_max=150)
    fig = plot_pair_network(pairs, baselines, scene_bperp)
    fig.show()
  • Download

    dl.download()

Processor:

from insarhub import Processor
  • View available processors

    Processor.available()
  • Create Processor

    processor = Processor.create('Hyp3_InSAR', workdir='/your/work/path', pairs=pairs)
  • Submit Jobs

    jobs = processor.submit()
  • Refresh Jobs

    jobs = processor.refresh()
  • Download Succeeded Jobs

    processor.download()

Analyzer

from insarhub import Analyzer
  • View available analyzers

    Analyzer.available()
  • Create Analyzer

    analyzer = Analyzer.create('Hyp3_SBAS', workdir="/your/work/dir")
  • Prepare data

    analyzer.prep_data()
  • Run time-series analysis

    analyzer.run()

CLI

InSARHub includes a command-line interface for running the full pipeline without writing Python code, suitable for HPC batch jobs and scripted workflows.

insarhub <command> [options]

End-to-end example

# Search scenes and select interferogram pairs
insarhub downloader -N S1_SLC \
    --AOI -113.05 37.74 -112.68 38.00 \
    --start 2020-01-01 --end 2020-12-31 \
    --stacks 100:466 \
    -w /data/bryce \
    --select-pairs

# Submit pairs to HyP3 (auto-reads stack_p*_f*.json from workdir subfolders)
insarhub processor -N Hyp3_InSAR  -w /data/bryce submit

# Wait for jobs and download results automatically
insarhub processor -w /data/bryce watch

# Run MintPy time-series analysis
insarhub analyzer -N Hyp3_SBAS -w /data/bryce run

Commands

Command Description
insarhub downloader Search scenes, select interferogram pairs, and download data
insarhub processor Submit and manage InSAR processing jobs
insarhub analyzer Run time-series analysis on processed interferograms
insarhub utils Helper utilities (pair selection, network plot, SLURM, ERA5, clip)

Use insarhub <command> --help for full option details, or see the CLI Reference.

Documentation

InSARHub documentation

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A modular Python framework for automated InSAR and time-series processing.

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