Supraglacial Lakes on Baltoro Glacier (Pakistan) for the period 2016 to 2022

The two publications “Seasonal evolution of supraglacial lakes on Baltoro Glacier from 2016 to 2020” (Wendleder et al., 2021) and “Basal Sliding and Hydrological Drainage at Baltoro Glacier, Pakistan” (Wendleder et al., 2024) focus on the supraglacial lakes on the Baltoro Glacier, Pakistan. The first publication explains the semi-automatic method (including Random forest classification and harmonization of the time series) for classifying the supraglacial lakes. The approach uses multi-temporal and multi-sensor summer time series from 2016 to 2020 based on optical (Sentinel-2 and PlanetScope) and Synthetic Aperture Radar (SAR; Sentinel-1 and TerraSAR-X) remote sensing data. Furthermore, the publication gives a first insight how the seasonal evolution of the supraglacial lakes vary over the years. The second publication extends the time series to 2022 and analyses the impact of glacial and climatic variables on the glacier surface velocity. Following interim and final results of the two publications are published here: 1) land cover classification (LCC) based on Sentinel-2 Multi Spectral Instrument (MSI) L2A (atmospheric correction applied with MAJA (MACCS ATCOR Joint Algorithm, release 4.2)) using the Random forest classification (section 3.2 in Wendleder et al., 2021) 2) supraglacial lakes (SGL) based on Sentinel-2 L2A MAJA data derived from the Random forest classification with subsequent filtering (section 3.2 in Wendleder et al., 2021) 3) local distribution and duration (day of onset and disappearing in day of year) the supraglacial lakes (section 4.4 and Figure 6 in Wendleder et al., 2021) and the seasonal evolution based on Sentinel-1 and 2, PlanetScope, and TerraSAR-X (section 4.5 and Figure 7 in Wendleder et al., 2021) 4) temporal relationship of the supraglacial lakes, runoff-index, surface velocity, air temperature, precipitation, and snowmelt (section 4.1 and Figure 2 in Wendleder et al., 2024).