Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 13
Articles | Volume 19, issue 13
https://doi.org/10.5194/gmd-19-5979-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-5979-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 13
Development and technical paper
 | 
13 Jul 2026
Development and technical paper |  | 13 Jul 2026

HyperGas 1.0: a python package for analyzing hyperspectral data for greenhouse gases from retrieval to emission rate quantification

Xin Zhang, Joannes D. Maasakkers, Tobias A. de Jong, Paul Tol, Frances Reuland, Adam R. Brandt, Eric A. Kort, Taylor J. Adams, and Ilse Aben

Viewed

Total article views: 4,695 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,475 2,052 168 4,695 139 195
  • HTML: 2,475
  • PDF: 2,052
  • XML: 168
  • Total: 4,695
  • BibTeX: 139
  • EndNote: 195
Views and downloads (calculated since 11 Jan 2026)
Cumulative views and downloads (calculated since 11 Jan 2026)

Viewed (geographical distribution)

Total article views: 4,695 (including HTML, PDF, and XML) Thereof 4,545 with geography defined and 150 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 02 Aug 2026
Download
Short summary
Reducing emissions of greenhouse gases such as methane and carbon dioxide is essential for addressing climate change. We developed HyperGas, an open tool that uses hyperspectral satellite images to retrieve and detect greenhouse gas plumes. It helps scientists locate emission sources, estimate their strength, and examine uncertainties through an easy workflow and visual app. Our goal is to make tracking human-made emissions more accurate and accessible, supporting better climate monitoring.
Read more
Share