vhrharmonize: VHR Satellite Imagery Preprocessing Library

Overview

vhrharmonize is an open-source Python library and CLI suite for preprocessing very high resolution (VHR) satellite imagery into analysis-ready products. Current supported end-to-end workflows: WorldView-3 B1 imagery. Additional providers and sensors (for example, Planet) will be added.

Features

• Atmospheric correction workflows (Py6S default, FLAASH optional backend)
• RPC orthorectification (Orthority)
• Pansharpening (Orthority)
• Optional cloud masking (OmniCloudMask)
• Pairwise alignment (coregix)
• Relative Radiometric Normalization (spectralmatch)
• WorldView scene discovery, IMD parsing, and standardized metadata mapping
• CLI and library-first interfaces
• Automated SLURM processing for distributed High Performance Computing processing

Installation

See the installation docs for detailed installation instructions or simply install like this:

conda create -n vhrharmonize -c conda-forge gdal python=3.11
conda activate vhrharmonize
pip install "vhrharmonize[defaults]"

Getting Started

For an overview of using the library see the quickstart docs. The CLI can be usd by passing in arguments from a yaml file like this one configs/example.worldview.yml and running:

vhr-worldview --config-yaml example.worldview.yml

Or pass in arguments directly from the command line:

vhr-worldview \
  --input-file-glob "/data/worldview/**/*.TIF" \
  --output-dir ../../processed \
  --run-alignment \
  --alignment-fixed-image /data/reference.tif

For detailed arguments use:

vhr-worldview --help
vhr-fetch-modis-water-vapor --help
vhr-flaash --help
vhr-cloudmask-raster --help
vhr-pansharpen-orthos --help
vhr-align-image-pair --help
vhr-orthorectification --help
vhr-radiometric-normalization --help
vhr-py6s --help

To use on a super computer (slurm):

vhr-hpc prepare --config configs/example.hpc.yml # Create staged HPC/provider/slurm files
vhr-hpc upload --config configs/1.staged.hpc.yml # Upload required files
vhr-hpc start --config configs/1.staged.hpc.yml # Submit the job
vhr-hpc status --config configs/1.staged.hpc.yml # Print logs and job status
vhr-hpc download --config configs/1.staged.hpc.yml # Download declared outputs

# Other commands:
vhr-hpc stop --config configs/1.staged.hpc.yml # Cancel the submitted job
vhr-hpc close --config configs/1.staged.hpc.yml # Close the SSH multiplex connection

# Or all together:
vhr-hpc prepare --config configs/example.hpc.yml && vhr-hpc upload --config configs/1.staged.hpc.yml && vhr-hpc start --config configs/1.staged.hpc.yml && vhr-hpc status --config configs/1.staged.hpc.yml

# Helpful commands:
# Create preview image and download
conda install gdal
gdal raster resize --size 1%,1% -r average --co TILED=YES --co COMPRESS=DEFLATE "input.tif" "preview.tif"
rsync -avP user@ip:preview.tif .preview.tif

Contributing

We welcome all contributions! We appreciate any feedback, suggestions, or pull requests to improve this project. See the contributing docs.

License

This project is licensed under the MIT License. See the LICENSE for details.