A remote sensing approach for measuring climatic change effects on snow cover dynamics

Abstract

Climate change (CC) is significantly impacting the snow cover of the European Alps, compromising hydrological cycles, water stock for agricultural and civil supply, winter tourism. This study investigates Snow Cover Changes (SCC) in the Western Italian Alps (Piemonte and Valle d'Aosta regions) from 2000 to 2023, using MODIS satellite data. In particular, MOD10A1 images were processed in Google Earth Engine to derive daily snow cover, integral snow cover area (iSCA), snow persistence (SP), and mean daily snowed area (MDSA). Ground data from 96 snowmeter stations were used to validate the satellite-derived SP. The analysis of SCC was performed by quantifying long-term trends of MDSA at the pixel level. The normalized trend (nT) index represents the percentage change rate in snow-covered area per yearly mean snow event. It was mapped showing different spatial patterns of SCC in the study area. Results reveal an altitudinal gradient in nT, with the higher snow cover reduction occurring in lowland and within main valley areas, reaching -5 % below 1000 m a.s.l. and -1.8 % between 1000–1500 m a.s.l. These findings highlight the vulnerability of snow resources due to CC, impacting water availability, winter sports, and regional economies. This study can support adaptation strategies and sustainable resource management in the Western Alps by mapping critical areas where CC effects on snow must be mitigated.