Permafrost, defined as perpetually frozen soil, characterizes most of the Arctic terrestrial surface and it is overlayed by an active layer that melts seasonally. The global warming is triggering an earlier snow melting and a related reduction in average snow cover extent in the spring with a consequent lengthening of the Snow-Off period and exposure of land surface to the effect of solar radiation. The spatial pattern of the Land Surface Temperature (LST) and its general increases, change with a different rate according to the vegetation surface types and the associated mid-summer albedo. The immediate consequence can be observed in the annual variability of permafrost thawing and in the direct impact on the tundra biome in terms of greening process and above all, on the permafrost itself, which stores tons of carbon. The permafrost Active Layer Thickness (ALT) has reached an ever-increasing annual average. The geospatial model here presented estimates the permafrost ALT over the entire Arctic in the last 20 years and it is based on the spatial and temporal oscillations measured by satellite based Essential Variables (EVs) associated with the Thermal State of Permafrost (TSP). The model integrates the climate components such as the LST and the mid-summer Albedo, with the structural and functional descriptors of Arctic tundra biome such as the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). The Arctic tundra region has been divided in two subzones: the first characterized by less structured vegetation, mainly mosses and lichens, the second by grass and shrubs. The ALT biogeographical variability is obtained by building a linear regression model between the EVs and the ALT data provided by the Circumpolar Active Layer Monitoring (CALM) field measurements for each subzone. For the mosses and lichens subzone, ALT average has been estimated to increase of 5 cm in twenty years, instead for the grass and shrubs subzone, the estimated ALT average has been increased of 2 cm. Although a general average ALT increase has been estimated over the whole tundra region, with rates up to 2 cm/year, the areas which encounter the highest thickening rates, partially overlap with the areas where a vegetation persistence and a potential greening phenomenon have been estimated to occur, along the boreal tree line.
Moreover, remote sensing technologies, including satellite imagery and airborne sensors, are valuable for large-scale ALT estimation. Satellite data, such as those from the Moderate Resolution Imaging Spectroradiometer (MODIS), can provide information on land surface temperatures and vegetation indices that are related to ALT dynamics. Infrared thermography is also used to identify areas with varying active layer depths. Once field measurements and remote sensing data are collected, spatial interpolation techniques can be applied to extrapolate ALT measurements across the Arctic tundra. Methods like kriging, regression modeling, or geostatistical techniques can help generate continuous ALT maps, highlighting spatial patterns and variability.
