This research was funded by the Spanish Government projects RTI2018-098048B-100 (PiMetAn) and PID2021-1257830B-100 (DICHOSO). Equipment was funded by Spanish Government Infraestructure projects EQC2018-004446-P, EQC2018-004275-P and EQC2019-005721. This research has been supported by the Grant CNS2023-143630 funded by MICIU/AEI/10.13039/501100011033 and by European Union Next Generation EU/PRTR. A. Román, staff hired under the Generation D initiative, promoted by Red.es, an organisation attached to the Ministry for Digital Transformation and the Civil Service, for the attraction and retention of talent through grants and training contracts, financed by the Recovery, Transformation and Resilience Plan through the European Union's Next Generation funds. BFM is supported by a RYC2021-031321-I grant funded by MCIN/AEI/10.13039/501100011033 and by the European Union Next-GenerationEU/PRTR. This work represents a contribution to Polar CSIC-HUBs.

This repository contains the original raw data captured with a hyperspectral sensor mounted on a drone, as well as the reprocessed spectral library of red snow algal blooms from several locations on Livingston Island (South Shetland Islands, Antarctica). It also includes custom-developed code for data processing/handling and for scaling the methodology to its application using Sentinel-2 satellite data. These datasets were collected during the second Antarctic campaign of the PiMetAn project in 2022 and were used to obtain the results published in Román et al. 2025 (DOI: available soon). This information has been essential for determining the true spatial extent of these snow algal blooms across the entire South Shetland Islands archipelago, which potentially lowers surface albedo and accelerates coastal snow and ice melt.

Peer reviewed