Proposed algorithm for the identification of glacier cover from Sentinel-2A images

In Peru, there are 20 glacial mountain ranges that in almost 60 years have lost 54% of their glacial coverage. The accelerated glacial recession due to climate change raises the need to know the levels of retraction of the glacier surface efficiently and reliably. During the preparation of the last inventory by the National Institute for Research in Glaciers and Mountain Ecosystems (INAIGEM), it was identified that carrying out the inventory faces challenges, such as differentiating between temporary snow and glacier ice, especially in areas with complex meteorological characteristics. like the Cordillera Blanca (Peru). Due to the Peruvian Andes’ geographical and climatic complexity, satellite images usually show cloudiness and temporary snow, even in the dry season (April to November). In this way, the objective is to obtain an ideal image with annual glacier coverage with minimal snow reflecting the current glacier surface. For this, the script "Normalized Differentiated Snow Index - minimum NDSI" was developed, which analyzed the Sentinel-2A image catalog of the year 2020 and delimited the glaciers of the Huascarán and Huandoy systems in the Cordillera Blanca.

The proposed methodology aims to evaluate the techniques for generating glacier cover, which allows the proposed objective to get the minimum glacier area. Three glacier cover generation techniques were evaluated: mosaic, medium, and minimum. For the mosaic and average reductions, the algorithm applied a cloud filter to the Sentinel-2A image set and calculated the NDSI for the month that was lowest in the historical average from Landsat 5, 7, and 8 images (1990-2020), applying a threshold of 0.4 and exporting the results with mean and mosaic reduction, respectively. While the minimum NDSI was calculated annually (2020) from Sentinel-2A images, with a cloud filter to which the reduction by minimums is applied, within the same area of interest, applying the threshold of 0.4 and exporting the results in raster format. Finally, the three results were evaluated in terms of the percentage of overestimation concerning glacier coverage in 2016.

The results reveal that the Huascarán and Huandoy glacier systems present a lower NDSI value during August and October, with standard deviations of 0.12 and 0.14, respectively. The glacier cover generated by the minimum NDSI was compared in the percentage of overestimation (m2) concerning 2016 with the average and mosaic NDSI, finding as a result that the minimum glacier cover, for the year 2020, evidences a lower percentage of temporal snow in the Huascarán system between 157.12% and 76.84% less than the filtering methods: average and mosaic. Likewise, in the Huandoy system, there is evidence of a lower percentage of temporary snow between 205.91% and 191.65% less than the average and mosaic methods. Finally, it is necessary to indicate that the developed algorithm has improved the obtaining of glacier coverage from the inventory developed by INAIGEM and reduces the overestimation of glacier coverage due to temporary snow.