FanInSAR 0.0.1

A fantastic InSAR processing library, in a more pythonic way, to accelerate your InSAR processing workflow.

FanInSAR is a Fancy Interferometric Synthetic Aperture Radar (InSAR) time series analysis library written in Python. It aims to provide a foundational library for the development of InSAR algorithms, facilitating efficient processing of InSAR time series data by offering a Pythonic, fast, and flexible approach. FanInSAR’s high-level API abstracts the complex processing pipeline and conceals the low-level programming details, enabling users to focus on algorithm development. For researchers and developers aiming to rapidly implement their own InSAR algorithms, FanInSAR offers a quick start for their projects.

Highlight Features

• Pythonic: FanInSAR is written in Python and provides a user-friendly API. Its API is designed to be simple and intuitive, by abstracting the complex processing pipeline and concealing the low-level programming details, which allows users to focus on algorithm development. For example, loading data from HyP3 or LiCSAR products is as simple as providing the corresponding home directory. Filtering interferometric pairs can be performed by a time slice, similar to the pandas package.
• Fast: The core computation in FanInSAR is implemented using PyTorch, a high-performance deep learning library. This allows for efficient processing on both CPU and GPU, enabling faster execution.
• Flexible: FanInSAR is designed to be flexible, allowing for customization and extension. Users can easily inherit classes or customize the processing pipeline for their specific needs.

Installation

FanInSAR is a Python package, and requires Python >= 3.8. You can install the latest release of FanInSAR using pip:

pip install git+https://github.com/Fanchengyan/FanInSAR.git

Documentation

The detailed documentation is available at: https://faninsar.readthedocs.io/en/latest/

:warning: Note

FanInSAR is under active development and is currently in the alpha stage. Its API may change in the future until it reaches a stable version.

Citation

Fan, C., & Liu, L. (2024). FanInSAR: A Fancy InSAR time series library, in a Pythonic, fast, and flexible way (0.0.1). Zenodo. https://doi.org/10.5281/zenodo.11398347

@software{fan_2024_11398347,
  author       = {Fan, Chengyan and
                  Liu, Lin},
  title        = {{FanInSAR: A Fancy InSAR time series library, in a 
                   Pythonic, fast, and flexible way}},
  month        = may,
  year         = 2024,
  publisher    = {Zenodo},
  version      = {0.0.1},
  doi          = {10.5281/zenodo.11398347},
  url          = {https://doi.org/10.5281/zenodo.11398347}
}