InSAR-derived seasonal subsidence rates reflect spatial soil moisture patterns in Arctic lowland permafrost regions

Abstract. The identification of spatial soil moisture patterns is of high importance for various applications in high latitude permafrost regions, but challenging with common remote sensing approaches due to high landscape heterogeneity. Seasonal thawing and freezing of near-surface soil lead to subsidence-heave cycles in the presence of ground ice, which can exhibit magnitudes of several centimeters. Our investigations document higher Sentinel-1 InSAR seasonal subsidence rates for locations with higher near-surface soil moisture compared to dryer ones. Based on this, we demonstrate that the relationship of thawing degree days – a measure of seasonal heating – and subsidence signals can be interpreted to assess spatial variations of near-surface soil moisture. A range of challenges, however, need to be addressed. We discuss the implications of using different sources of temperature data for deriving thawing degree days on the results. Atmospheric effects must be considered, as simple spatial filtering can suppress large-scale permafrost-related subsidence signals and lead to the underestimation of displacement values, making GACOS-corrected results preferable for the tested sites. Seasonal subsidence rate retrieval which considers these aspects provides a valuable tool for distinguishing between wet and dry landscape features, which is relevant for permafrost degradation monitoring in Arctic lowland permafrost regions. Spatial resolution constraints, however, remain for smaller typical permafrost features which drive wet versus dry conditions such as high and low centred polygons.