Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry
Satellite retrievals of snow depth and water equivalent (SWE) are critical for monitoring watershed scale processes around the world. However, the problem is especially challenging in mountainous regions where complex heterogeneities limit the utility of low resolution satellite sensors. The Geoscie...
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ftnasantrs:oai:casi.ntrs.nasa.gov:20120013477 2023-05-15T18:18:28+02:00 Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry Stoll, Jeremy Jasinski, Michael F. Unclassified, Unlimited, Publicly available June 05, 2012 application/pdf http://hdl.handle.net/2060/20120013477 unknown Document ID: 20120013477 http://hdl.handle.net/2060/20120013477 Copyright, Distribution as joint owner in the copyright CASI Geophysics GSFC.ABS.6483.2012 Eastern Snow Conference Meeting; 5-7 Jun. 2012; Claryville, NY; United States 2012 ftnasantrs 2019-07-21T00:47:48Z Satellite retrievals of snow depth and water equivalent (SWE) are critical for monitoring watershed scale processes around the world. However, the problem is especially challenging in mountainous regions where complex heterogeneities limit the utility of low resolution satellite sensors. The Geoscience Laser Altimeter Sensor (GLAS) aboard the Ice, Cloud, and land Elevation Satellite (ICESat) collected surface elevation data along near-repeat reference transects over land areas from 2003-2009. Although intended for monitoring ice caps and sea ice, the seven year global GLAS data base has provided unprecedented opportunity to test the capability of satellite lidar technology for estimating snow depth over land. GLAS single track and low repeat frequency does not provide data sufficient for operational estimates. However, its comparatively small footprint size of -65 m and its database of seasonal repeat observations during both snow and no-snow conditions have been sufficient to evaluate the potential of spacebased lidar altimetry for estimating snow depth. Recent analysis of ICESat elevations in the Uinta Mountains in NE Utah provide encouraging results for watershed scale estimates of snow depth. Research reported here focuses on the sensitivity of several versions of an ICESat snow depth algorithm to a range of landscape types defined by vegetation cover, slope and roughness. Results are compared to available SNOTEL data. Other/Unknown Material Sea ice NASA Technical Reports Server (NTRS) |
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NASA Technical Reports Server (NTRS) |
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Geophysics |
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Geophysics Stoll, Jeremy Jasinski, Michael F. Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry |
topic_facet |
Geophysics |
description |
Satellite retrievals of snow depth and water equivalent (SWE) are critical for monitoring watershed scale processes around the world. However, the problem is especially challenging in mountainous regions where complex heterogeneities limit the utility of low resolution satellite sensors. The Geoscience Laser Altimeter Sensor (GLAS) aboard the Ice, Cloud, and land Elevation Satellite (ICESat) collected surface elevation data along near-repeat reference transects over land areas from 2003-2009. Although intended for monitoring ice caps and sea ice, the seven year global GLAS data base has provided unprecedented opportunity to test the capability of satellite lidar technology for estimating snow depth over land. GLAS single track and low repeat frequency does not provide data sufficient for operational estimates. However, its comparatively small footprint size of -65 m and its database of seasonal repeat observations during both snow and no-snow conditions have been sufficient to evaluate the potential of spacebased lidar altimetry for estimating snow depth. Recent analysis of ICESat elevations in the Uinta Mountains in NE Utah provide encouraging results for watershed scale estimates of snow depth. Research reported here focuses on the sensitivity of several versions of an ICESat snow depth algorithm to a range of landscape types defined by vegetation cover, slope and roughness. Results are compared to available SNOTEL data. |
format |
Other/Unknown Material |
author |
Stoll, Jeremy Jasinski, Michael F. |
author_facet |
Stoll, Jeremy Jasinski, Michael F. |
author_sort |
Stoll, Jeremy |
title |
Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry |
title_short |
Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry |
title_full |
Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry |
title_fullStr |
Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry |
title_full_unstemmed |
Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry |
title_sort |
feasibility of estimating snow depth in complex terrain using satellite lidar altimetry |
publishDate |
2012 |
url |
http://hdl.handle.net/2060/20120013477 |
op_coverage |
Unclassified, Unlimited, Publicly available |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
CASI |
op_relation |
Document ID: 20120013477 http://hdl.handle.net/2060/20120013477 |
op_rights |
Copyright, Distribution as joint owner in the copyright |
_version_ |
1766195058928779264 |