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Retrogressive Thaw Slumps (RTS) are cryogenic landforms that occur as a result of ice-rich permafrost thawing and ground ice melting. This phenomenon leads to changes in the local environment and carbon emissions. RTS passes different stages of activity: active, stabilized, and ancient. Stages can be determined based on their proportion within a particular RTS. In this study, we analyzed the spectral properties of RTS landforms using satellite imagery in the vicinity of Vaskiny Dachi research station, Yamal Peninsula, West Siberia. High-resolution ortho-mosaics were collected from UAV surveys in 2021 and were used to map different landform classes associated with RTS, including wet mud, dry mud, stabilized, ancient, and undisturbed tundra. Surface reflectance values were extracted for each class within RTS using multispectral Sentinel-2, Landsat 8, and PlanetScope imagery (10m, 30m, and 3m spatial resolution, respectively). The results of the study showed that Sentinel-2 and PlanetScope images in true color were sufficient for visual interpretation of the variability within RTS and false color composites (NIR-R-G) allowed the best visual detail. All classes were found to be distinguishable at different wavelengths based on the Sentinel-2 image, with spectral separation especially present in the NIR and SWIR bands. Spectral differences between ancient and stabilized classes were not noticeable in the lower spatial resolution Landsat images or in the 4-band PlanetScope images. The highest within-class variance was found in the wet mud and dry mud classes. High-resolution satellite imagery can be used to visually interpret the variability within RTS and distinguish between the different stages based on their spectral properties, allowing a better assessment of temporal RTS dynamics. Further data collection is needed to improve the accuracy of RTS landform class delineation. This work was partially funded by the Russian Science Foundation grant #22-27-00644.