Snow cover is an essential climate variable directly affecting the Earth’s energy balance. Snow cover has a number of important physical properties that exert an influence on global and regional energy, water and carbon cycles. Surface
temperature is highly dependent on the presence or absence of snow cover, and temperature trends have been shown to be related to changes in snow cover. Its quantification in a changing climate is thus important for various environmental and economic impact
assessments. Identification of snowmelt processes could significantly support water management, flood prediction and prevention.
Remote sensing provides a good understanding of snow cover and enable snow cover information to be assimilated into hydrological, land surface, meteorological and climate models for predicting snowmelt runoff, snow water resources and to
warn about snow-related natural hazards.
This Special Issue invites and encourages to submit covering all instrumentation/sensors and methodologies/models/algorithms in remote sensing of snow parameters (snow extent, snow depth, snow wetness, snow density, snow water equivalent,
etc.) and applications where remotely-sensed snow information are used for, including, but not limited to:
Remote sensing techniques and methods for snow
Modelling, retrieval algorithms and in-situ measurements of snow parameters
Multi-source and multi-sensor remote sensing of snow
Remote sensing and model integrated approaches of snow
Applications where remotely sensed snow information used for such as weather forecasting, flooding, avalanche, water management, traffic, health and sport, agriculture and forestry, climate scenarios, etc.