The study analyzes the variability over time of the Snow Line Altitude (SLA) and its correspondence with the Equilibrium Line Altitude (ELA) in four glaciers of the Southern Patagonian Icefield (SPI): Perito Moreno, Upsala, Viedma and De los Tres. Using Google Earth Engine and Landsat satellite imagery, an automated algorithm based on the Otsu image segmentation method was developed to analyze the 1985–2023 time series to obtain the Snow Cover Ratio (SCR) and subsequently estimate the SLA using the ALOS World 3D DSM. The study employed the near infrared (NIR) and shortwave infrared (SWIR) bands of Landsat images, with the SCR and subsequently the SLA determined using only the NIR band, as well as a band ratio between the NIR/SWIR bands. The results indicated that the Viedma glacier showed a statistically significant positive trend in SLA elevation, while the other three glaciers showed a stationary behavior with high variability. The SLA calculated using the NIR/SWIR bands tended to be higher compared to the NIR band calculation, especially for the Viedma and Upsala glaciers. Comparisons with previous studies (De Angelis, 2014; Popovnin et al., 1999) and recent glaciological measurements from the Inventario Nacional de Glaciares (2015–2022) showed that the SLA derived from the NIR bands aligned more closely with the aforementioned works.