Geoscientific Instrumentation, Methods and Data Systems
Geoscientific Instrumentation, Methods and Data Systems
GI
Articles | Volume 14, issue 2
Articles | Volume 14, issue 2
https://doi.org/10.5194/gi-14-183-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gi-14-183-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 2
Research article
 | 
28 Aug 2025
Research article |  | 28 Aug 2025

Introducing a learning tool (QSVI): A QGIS plugin for computing vegetation, chlorophyll, and thermal indices with remote sensing images

Nuray Baş

Viewed

Total article views: 977 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
818 128 31 977 67 70
  • HTML: 818
  • PDF: 128
  • XML: 31
  • Total: 977
  • BibTeX: 67
  • EndNote: 70
Views and downloads (calculated since 24 Mar 2025)
Cumulative views and downloads (calculated since 24 Mar 2025)

Viewed (geographical distribution)

Total article views: 977 (including HTML, PDF, and XML) Thereof 960 with geography defined and 17 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 01 Nov 2025
Download
Short summary
The Quantum Geographic Information System (QGIS) Sentinel Vegetation Indices (QSVI) plugin is an efficient, user-friendly tool designed to calculate key environmental remote sensing indices. Developed using a Python library within the QGIS software, QSVI significantly reduces computation time, exceeding other popular GIS applications. This study demonstrates its effectiveness in processing large datasets, offering a cost-effective solution for environmental monitoring and analysis, which is particularly valuable in educational settings.
Read more
Share