Abstract
This paper discusses the development of PyGeoRS, a Python-based QGIS plugin designed to automate remote sensing tasks for environmental mapping using Landsat 8 and 9 data. PyGeoRS simplifies complex processes using data from Landsat 8 and 9 satellites, facilitating tasks such as Principal and Independent Component Analysis, band ratios, indices calculation, false-color image generation, and Optimum Index Factor calculation. A key advantage of PyGeoRS is its ability to significantly enhance processing speed, offering a 40–60% improvement compared to other remote sensing software, which optimizes workflow efficiency. Additionally, as an open-access tool, PyGeoRS broadens the availability of advanced remote sensing capabilities to users with varying levels of access to technology. While this version supports only Landsat data, future expansions are planned to include additional sensors, further extending PyGeoRS’s applicability in remote sensing and mapping tasks.
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No datasets were generated or analysed during the current study.
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Acknowledgements
We would like to express our sincere gratitude to Mr. Riad MARZOUKI for his invaluable technical assistance during the development of PyGeoRS. His support and expertise greatly contributed to the successful completion of this project.
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This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
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AM: conceptualization, methodology, software, data curation, writing – original draft. AD: supervision, writing – review & editing, validation.
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During the preparation of this work the authors used ChatGPT in order to check for grammatical / spelling errors and to further enhance the text. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.
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Communicated by Hassan Babaie
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Marzouki, A., Dridri, A. PyGeoRS: a QGIS plugin for automating landsat data processing in environmental mapping. Earth Sci Inform 18, 58 (2025). https://doi.org/10.1007/s12145-024-01522-0
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DOI: https://doi.org/10.1007/s12145-024-01522-0