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Journal of Applied Remote Sensing

Extraction and assessment of snowline altitude over the Tibetan plateau using MODIS fractional snow cover data (2001 to 2013)
Author(s): Zhiguang Tang; Jian Wang; Hongyi Li; Ji Liang; Chaokui Li; Xin Wang
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Paper Abstract

Snowline altitude (SLA) is the most sensitive indicator for monitoring climatic behavior among all the cryosphere elements. In this study, the snowline and SLA over the Tibetan plateau (TP) during 2001 to 2013 are extracted using the cloud-removed MODIS daily fractional snow cover (FSC) products combined with digital elevation model (DEM), and the spatiotemporal changes of SLA and their response to the changing temperature are examined. The proposed MODIS-based SLA-extracting methodology includes cloud removal from MODIS FSC data, the determination of the snowline and SLA, and the establishment of the snowline altitude field (SLAF). Results show that the SLA in the interior of the TP is obviously higher than the peripheral mountainous area due to the complex terrain. There is no obvious trend of SLA change during the examined period although a strong seasonal and interannual variability of SLA is discovered. The interannual fluctuation of SLA in the snowmelt period can be explained by the high-positive correlations between the SLA and temperature. The MODIS-based SLA-extracting method described has a good application potential in SLA monitoring for other regions.

Paper Details

Date Published: 3 June 2014
PDF: 13 pages
J. Appl. Remote Sens. 8(1) 084689 doi: 10.1117/1.JRS.8.084689
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Zhiguang Tang, Hunan Univ. of Science and Technology (China)
Cold and Arid Regions Environmental and Engineering Research Institute (China)
Jian Wang, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Hongyi Li, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Ji Liang, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Chaokui Li, Hunan Univ. of Science and Technology (China)
Xin Wang, Hunan Univ. of Science and Technology (China)


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