Lyons (2026) speclib: Federated Spectral Signature Library

Identification

• Journal: Open MIND
• Year: 2026
• Date: 2026-04-02
• Authors: Chris Lyons
• DOI: 10.5281/zenodo.19390679

Research Groups

• Commonwealth of Kentucky

Short Summary

This paper introduces speclib, a federated spectral signature library platform designed to aggregate reflectance spectra from various sources, including USGS, ECOSTRESS, ASTER/JPL, and EMIT L2B, alongside specialized Kentucky-focused collections like invasive species data.

Objective

• To develop and release a federated spectral signature library platform that aggregates diverse reflectance spectra for remote sensing applications.

Study Configuration

• Spatial Scale: Regional (Kentucky) for specialized collections, integrating global/regional satellite data sources.
• Temporal Scale: Ongoing, as a software platform for continuous data aggregation and access.

Methodology and Data

• Models used: Software platform for data aggregation and management.
• Data sources: USGS Spectral Library v7, ECOSTRESS, ASTER/JPL, EMIT L2B, and Kentucky-focused collections (including invasive species spectral data).

Main Results

• Release of speclib, a federated spectral signature library software platform.
• Successful aggregation of reflectance spectra from major satellite missions (ECOSTRESS, ASTER, EMIT) and established libraries (USGS).
• Integration of unique, localized spectral collections, such as those for invasive species in Kentucky.

Contributions

• Provides a novel, unified, and federated access point for diverse spectral signature libraries, simplifying data discovery and utilization.
• Enhances the utility of spectral data by combining global satellite observations with specific regional and ground-based collections.
• Facilitates research and applications in remote sensing, particularly for regional environmental monitoring and invasive species detection.

Funding

• Not specified in the provided text.

Citation

@article{Lyons2026speclib,
  author = {Lyons, Chris},
  title = {speclib: Federated Spectral Signature Library},
  journal = {Open MIND},
  year = {2026},
  doi = {10.5281/zenodo.19390679},
  url = {https://doi.org/10.5281/zenodo.19390679}
}