A GRASS GIS Scripting Framework for Monitoring Changes in the Ephemeral Salt Lakes of Chotts Melrhir and Merouane, Algeria

Automated classification of satellite images is a challenging task that enables the use remote sensing data for environmental modeling Earth’s landscapes. In this document, we implement GRASS GIS-based framework discriminating land cover types to identify changes in endorheic basins ephemeral salt lakes Chott Melrhir and Merouane, Algeria; employ embedded algorithms image processing. This study presents dataset nine Landsat 8–9 OLI/TIRS obtained from USGS 9-year period, 2014 2022. The were analyzed detect water levels experience temporal fluctuations; these are dry most time fed with during rainy periods. unsupervised was performed using GIS through several modules: ‘i.cluster’ used generate classes; ‘i.maxlik’ maximal likelihood discriminant analysis, auxiliary modules, such as ‘i.group’, ‘r.support’, ‘r.import’, etc., used. document includes technical descriptions scripts processing detailed comments on functionalities modules. results include identified variations within Algerian part Sahara over period (2014–2022), series multispectral classified GIS. main strengths high speed, accuracy, effectiveness programming codes monitoring. presented GitHub repository, which contains serves reference interpretation monitoring arid semi-arid areas Africa.