TY - JOUR
T1 - Extending the utility of modis daily snow-cover products through snow-cover prediction of cloud-obscured areas in Idaho's big lost river basin (USA)
AU - Hruska, Ryan C.
AU - Lee, Randy
N1 - Funding Information:
ABSTRACT. Increasing demand for water resources in the Western United States has given rise to many conflicts and has increased the need for more accurate and timely water management decisions. Snow-Covered Area (SCA) is an important hydrologic variable for both volumetric and daily stream flow forecasting. Satellite data provide the ideal way to map snow cover in mountain regions; however, the utility of these datasets have been limited due to the large number of scenes that are contaminated with cloud cover. To improve the utility of these datasets for the snowmelt season, in particular the Moderate Resolution Imaging Spectroradiometer (MODIS) Daily Snow-Cover Product dataset, a new procedure was developed to predict snow-cover in cloud-obscured areas using a snow-occurrence map technique. Results show that this method effectively increases the usefulness of Ryan C. Hruska, Research Scientist, Idaho National Laboratory, PO Box 1625, Idaho Falls, ID 83415–2213. (E-mail: [email protected].) Randy Lee, Research Scientist, Idaho National Laboratory, PO Box 1625, Idaho Falls, ID 83415–2213. (E-mail: [email protected].) Acknowledgement: Work supported by NASA, under DOE Idaho Operations Office Contract DE-AC07–05ID14517. The authors wish to thank the Pacific Northwest Regional Collaboratory (PNWRC) and NASA for funding this research, and Ron Abromavich of the USDA-NRCS Idaho Snow Survey for providing valuable guidance on how these products are, and will be used. We would also like to thank the National Snow and Ice Data Center for helping establish the automated MODIS subscription. This article is not subject to U.S. copyright law.
PY - 2007
Y1 - 2007
N2 - Increasing demand for water resources in the Western United States has given rise to many conflicts and has increased the need for more accurate and timely water management decisions. Snow-Covered Area (SCA) is an important hydrologic variable for both volumetric and daily stream flow forecasting. Satellite data provide the ideal way to map snow cover in mountain regions; however, the utility of these datasets have been limited due to the large number of scenes that are contaminated with cloud cover. To improve the utility of these datasets for the snowmelt season, in particular the Moderate Resolution Imaging Spectroradiometer (MODIS) Daily Snow-Cover Product dataset, a new procedure was developed to predict snow-cover in cloud-obscured areas using a snow-occurrence map technique. Results show that this method effectively increases the usefulness of the MODIS Snow-Cover product in mapping the daily evolution of snow cover extent in the Big Lost River Basin located in southeastern Idaho.
AB - Increasing demand for water resources in the Western United States has given rise to many conflicts and has increased the need for more accurate and timely water management decisions. Snow-Covered Area (SCA) is an important hydrologic variable for both volumetric and daily stream flow forecasting. Satellite data provide the ideal way to map snow cover in mountain regions; however, the utility of these datasets have been limited due to the large number of scenes that are contaminated with cloud cover. To improve the utility of these datasets for the snowmelt season, in particular the Moderate Resolution Imaging Spectroradiometer (MODIS) Daily Snow-Cover Product dataset, a new procedure was developed to predict snow-cover in cloud-obscured areas using a snow-occurrence map technique. Results show that this method effectively increases the usefulness of the MODIS Snow-Cover product in mapping the daily evolution of snow cover extent in the Big Lost River Basin located in southeastern Idaho.
KW - Cloud-Obscured
KW - Mapping
KW - Satellite Data
KW - Snow-Cover
KW - Stream Flow
KW - Water Resources
UR - https://www.scopus.com/pages/publications/70249125088
U2 - 10.1080/15420350802142702
DO - 10.1080/15420350802142702
M3 - Article
AN - SCOPUS:70249125088
SN - 1542-0353
VL - 4
SP - 356
EP - 366
JO - Journal of Map and Geography Libraries
JF - Journal of Map and Geography Libraries
IS - 2
ER -