# Remote Sensing of Environmental Changes in Cold Regions: Methods, Achievements and Challenges
## 4 Challenges and Opportunities  
### Limitations of Current Approaches  
Despite great achievements in cold land remote sensing, comprehensive assessment of both long-term trends and relatively abrupt environmental changes requires quantifying hydrological and ecological variables with greater precision, including clearer delineation of different land components, better accuracy, data consistency, spatial resolution, and temporal sampling.  
Ice--The spatial resolution of satellite gravimetry observations of glaciers and ice sheets are generally very coarse (around 100 km), which limits their ability to precisely detect and locate glacier mass change at finer scales. LIDAR-based measurements of glacier elevations are of high accuracy (decimeter level) but with relatively poor spatial coverage, which consequently requires data interpolation and extrapolation for applications over large areas. For monitoring glacier movement, feature tracking fails when low coherence occurs in fast moving glaciers or over prolonged time intervals between observations.  
Snow--Snow covered area is mainly derived using optical sensors onboard polar-orbiting or geostationary satellites. However, it is still challenging to distinguish between clouds and snow in satellite optical snow mapping. Long-term (>40-year) SWE data records have been generated for the globe through satellite passive microwave sensors, but the retrieval spatial resolution and accuracy has generally not met the requirements for regional climate, numerical weather prediction, and hydrological research. The retrieval uncertainties mainly come from four sources, including mixed pixel effects, terrain effects, large diversity in snow physical properties, and low microwave sensitivity to shallow snow.  
Landscape Freeze/Thaw States--Most of the available global FT products represent aggregate landscape FT conditions that do not distinguish land components of the FT signal within a satellite footprint at several-10s km. Accurate estimates of FT metrics (e.g., spring thaw timing, frost days) pertaining to soil, snow, and vegetation components isolated from the integrated microwave FT signals with improved spatial resolution are required for better understanding of land and atmosphere interactions, including carbon, water, and energy exchanges. It is also needed to understand the scaling effects for heterogeneous terrain to bridge multi-resolution satellite observations [38].  
Water Bodies--It is challenging to detect water within mixed pixels or under overlying vegetation for both optical-IR and microwave sensors. In addition, near real-time and fine-scale mapping of regional SW dynamics are urgently needed for monitoring flood hazards and arctic wetting and drying trends.  
Vegetation--The short growing season and generally low vegetation productivity of Arctic-boreal regions can create challenges in terms of detecting changes in vegetation growth through use of remote sensing time series data. Other challenges in Arctic-boreal regions include saturated satellite signals over high-biomass vegetation, high occurrence of shallow water bodies, the presence of snow and ice cover, and spatially heterogenous snowmelt resulting in pixels mixed with snow and vegetation. Additionally, long-term and fine-scale delineation (1-200 m) of vegetation (e.g., shrub) patch distributions is lacking, but greatly needed in high-latitude ecosystem studies [288].