@inbook {50267,
	title = {Remote Sensing of the Snowpack},
	booktitle = {Principles of Snow Hydrology},
	year = {2008},
	month = {July 2008},
	pages = {118-145},
	publisher = {Cambridge University Press},
	organization = {Cambridge University Press},
	chapter = {5},
	address = {Cambridge, NY},
	abstract = {<p>Because of vast differences in the physical properties of snow and other natural surfaces, the occurrence of snow in a drainage basin can cause significant changes in energy and water budgets. As an example, the relatively high albedo of snow reflects a much higher percentage of incoming solar, shortwave radiation than snow-free surfaces (80\% or more for relatively new snow as opposed to roughly 15\% or less for snow-free vegetation). This can be important because snow may cover up to 53\% of the land surface in the northern hemisphere and up to 44\% of the world\&rsquo;s land areas at any one time. The visible portion (0.4 to 0.7 \&micro;m) of the electromagnetic spectrum can be used to map the percentages of a basin covered by snow because of the differences in reflectance of snow and snow-free areas. The thermal infrared portion of the spectrum (8-14 \&micro;m) can detect snowpack surface temperature variability in space and time which can be directly linked to the presence of water in the snowpack and perhaps to snowmelt. Although, in widely disparate portions of the spectrum the gamma radiation (3 divided by 10 to the sixth power to 3 divided by 10 to the fifth power \&micro;m) and the microwave radiation (1 mm 1 m) bands can be used in similar ways to detect the snowpack water equivalent using the attenuation of the relevant radiation by the snowpack itself. A combination of two different remote sensors can at certain times increase information available about the snowpack. With recent technological advances in data processing and transmission, data and derived snow and ice products from many current sensors are available to the hydrologic community in near real time (e.g., within 6 to 24 hours of satellite overpass).</p>
},
	keywords = {drainage basin, energy, remote sensing, snow, snowmelt, snowpack, water},
	url = {http://www.cambridge.org/us/academic/subjects/earth-and-environmental-science/hydrology-hydrogeology-and-water-resources/principles-snow-hydrology},
	author = {A. Rango and D. DeWalle}
}
