insarhub 0.1.1

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

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

• Installation
• Requirements
• Usage
• CLI
• Documentation

Installation

InSARHub can be installed using Conda:

conda install insarhub -c conda-forge

Pip:

pip install insarhub
conda install gdal

From source:

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

Requirements

• Python >=3.11
• 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

Usage

Downloader:

from insarhub import Downloader

• View available downloaders

  Downloader.available()
  

• Create downloader

  s1 = 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')
  

• 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 Sucessed 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 pairs_p*_f*.json from workdir subfolders)
insarhub processor submit -w /data/bryce

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

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

Commands

Command	Description
insarhub downloader	Search scenes, select pairs, and download data
insarhub processor submit	Submit interferogram pairs to HyP3
insarhub processor watch	Poll HyP3 and download results when complete
insarhub analyzer run	Prepare data and run MintPy SBAS analysis
insarhub utils clip	Clip HyP3 zip contents to an AOI
insarhub utils select-pairs	Select pairs from a saved search GeoJSON
insarhub utils plot-network	Plot interferogram network
insarhub utils slurm	Generate a SLURM batch script
insarhub utils era5-download	Download ERA5 weather data for tropospheric correction

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

Documentation

InSARHub documentation