Although passive microwave remote sensing has been widely used for snow depth (SD)
retrieval, its coarse spatial resolution has led to large uncertainties in various applications …

In nearly all reservoirs, storage capacity is steadily lost due to trapping and accumulation of
sediment. Despite critical importance to freshwater supplies, reservoir sedimentation rates …

To better understand the interactions between C-band radar waves and snow, a tower-
based experiment was set up in the Idaho Rocky Mountains for the period of 2021–2023 …

The spatial and temporal variation of the seasonal snowpack in mountain regions is
recognized as a clear knowledge gap for climate, ecology and water resources applications …

Seasonal snow plays a crucial role in society and understanding trends in snow depth and
mass is essential for making informed decisions about water resources and adaptation to …

Snow dynamics play a critical role in the climate system, as they affect the water cycle,
ecosystems, and society. In climate modelling, the representation of the amount and extent …

Satellite image time series in the optical and infrared spectrum suffer from frequent data
gaps due to cloud cover, cloud shadows, and temporary sensor outages. It has been a long …

Snow interacts with its environment in many ways and thus has a highly heterogeneous
spatial and temporal variability. Therefore, modeling snow variability is difficult, especially in …

The volume of unlabelled Earth observation (EO) data is huge, but many important
applications lack labelled training data. However, EO data offers the unique opportunity to …

Abstract Information on snow depth and its spatial distribution is important for numerous
applications, including natural hazard management, snow water equivalent estimation for …