For better estimation of snow water equivalents for a dam basin in cold snowy regions, the relationship between snow depth distribution outside forests and topography was investigated using high-resolution digital elevation model (DEM) created from airborne laser scanning. A linear relationship between snow depth outside forests and overground-openness was clarified. A method to estimate snow depths and snow water equivalents outside forests was developed using this linear relationship. Using the method, snow water equivalents in the Chubetsu Dam basin were estimated and resulted in estimates with a higher level of accuracy than those based on existing methods
We developed an approach to estimate snow water equivalent (SWE) through interpolation of spatially ...
International audienceAbstract. The unprecedented precision of satellite laser altimetry data from t...
Predicting changes in forested seasonal snowpacks under altered climate scenarios is one of the most...
For better estimation of snow water equivalents for dam basins in cold snowy regions, snow depth dis...
To clarify the water balance of the melting snow period, we estimated the snow water equivalent from...
Snow is an important source of water. However, data is often lacking on the water content (snow wate...
Snowpack is an important source of freshwater in mountainous regions. Understanding the role of diff...
Regression tree models have been shown to provide the most accurate estimates of distributed snow wa...
International audienceAccurate knowledge of snow depth distributions in mountain catchments is criti...
The amount of water stored in snowpack is the single most important measurement for the management o...
In nonpolar, cold climate zones, snow accounts for 17% of the total terrestrial water storage. Estim...
An algorithm is constructed to use snow-depth estimates, derived from repeat airborne LiDAR (Light D...
Information on snow depth and its spatial distribution is important for numerous applications, inclu...
There is increasing need to characterize the distribution of snow in complex terrain using remote se...
The processes controlling snowpack mass balance are highly variable in time and space, requiring rem...
We developed an approach to estimate snow water equivalent (SWE) through interpolation of spatially ...
International audienceAbstract. The unprecedented precision of satellite laser altimetry data from t...
Predicting changes in forested seasonal snowpacks under altered climate scenarios is one of the most...
For better estimation of snow water equivalents for dam basins in cold snowy regions, snow depth dis...
To clarify the water balance of the melting snow period, we estimated the snow water equivalent from...
Snow is an important source of water. However, data is often lacking on the water content (snow wate...
Snowpack is an important source of freshwater in mountainous regions. Understanding the role of diff...
Regression tree models have been shown to provide the most accurate estimates of distributed snow wa...
International audienceAccurate knowledge of snow depth distributions in mountain catchments is criti...
The amount of water stored in snowpack is the single most important measurement for the management o...
In nonpolar, cold climate zones, snow accounts for 17% of the total terrestrial water storage. Estim...
An algorithm is constructed to use snow-depth estimates, derived from repeat airborne LiDAR (Light D...
Information on snow depth and its spatial distribution is important for numerous applications, inclu...
There is increasing need to characterize the distribution of snow in complex terrain using remote se...
The processes controlling snowpack mass balance are highly variable in time and space, requiring rem...
We developed an approach to estimate snow water equivalent (SWE) through interpolation of spatially ...
International audienceAbstract. The unprecedented precision of satellite laser altimetry data from t...
Predicting changes in forested seasonal snowpacks under altered climate scenarios is one of the most...