CITATION.cff

cff-version: 1.2.0
message: "If you use this software, please cite both the software and the algorithm paper below."
title: "SpiPy: Python implementation of SPIRES snow property inversion"
authors:
  - family-names: Bair
    given-names: Ned
    email: edwardbair@ucsb.edu
    affiliation: "University of California, Santa Barbara"
    orcid: "https://orcid.org/0000-0002-7654-3210"  # Update with actual ORCID if available
  - family-names: Griessbaum
    given-names: Niklas
    affiliation: "Leidos, Inc."
    orcid: "https://orcid.org/0000-0000-0000-0000"  # Update with actual ORCID if available
version: 0.2.0
date-released: 2024-11-06
repository-code: "https://github.com/edwardbair/SpiPy"
url: "https://github.com/edwardbair/SpiPy"
license: MIT  # Update if different
keywords:
  - remote sensing
  - snow properties
  - spectral unmixing
  - satellite imagery
  - MODIS
  - Sentinel-2
  - Landsat
abstract: >
  SpiPy is a Python implementation of SPIRES (SPectral Inversion of REflectance from Snow),
  a spectral unmixing algorithm for analyzing snow reflectance data from satellite imagery.
  It retrieves snow properties (grain size, dust concentration, fractional snow-covered area)
  using lookup tables generated from Mie-scattering theory. This implementation features a
  hybrid Python/C++ architecture achieving 3000x speedup over pure Python implementations.
preferred-citation:
  type: article
  title: "Snow Property Inversion From Remote Sensing (SPIReS): A Generalized Multispectral Unmixing Approach With Examples From MODIS and Landsat 8 OLI"
  authors:
    - family-names: Bair
      given-names: E. H.
    - family-names: Stillinger
      given-names: T.
    - family-names: Dozier
      given-names: J.
  journal: "IEEE Transactions on Geoscience and Remote Sensing"
  volume: 59
  issue: 9
  start: 7270
  end: 7284
  year: 2021
  doi: 10.1109/TGRS.2020.3040328