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Journal of Applied Remote Sensing • Open Access

Spatiotemporal changes of snow cover over the Tibetan plateau based on cloud-removed moderate resolution imaging spectroradiometer fractional snow cover product from 2001 to 2011
Author(s): Zhiguang Tang; Jian Wang; Hongyi Li; Lili Yan

Paper Abstract

Snow cover changes over the Tibetan plateau (TP) are examined using moderate resolution imaging spectroradiometer (MODIS) daily fractional snow cover (FSC) data from 2001 to 2011 as well as in situ temperature data. First, the accuracy of the MODIS FSC data under clear sky conditions is evaluated by comparing with Landsat 30-m observations. Then we describe a cloud-gap-filled (CGF) method using cubic spline interpolation algorithm to fill in data gaps caused by clouds. Finally, the spatial and temporal changes of snow cover are analyzed on the basis of the MODIS-derived snow-covered area and snow-covered days (SCD) data. Results show that the mean absolute error of MODIS FSC data under clear sky condition is about 0.098 over the TP. The CGF method is efficient in cloud reduction (overall mean absolute error of the retrieved FSC data is 0.092). There is a very high inter-annual and intra-seasonal variability of snow cover in the 11 years. The higher snow cover corresponds well with the huge mountains. The accumulation and melt periods of snow cover vary in different elevation zones. About 34.14% (5.56% with a significant decline) and 24.75% (3.9% with a significant increase) of the study area presents declining and increasing trend in SCD, respectively. The inter-annual fluctuation of snow cover can be explained by the high negative correlations observed between the snow cover and the in situ temperature, especially in some elevations of February, April, May, August, and September.

Paper Details

Date Published: 4 March 2013
PDF: 15 pages
J. Appl. Remote Sens. 7(1) 073582 doi: 10.1117/1.JRS.7.073582
Published in: Journal of Applied Remote Sensing Volume 7, Issue 1
Show Author Affiliations
Zhiguang Tang, 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)
Lili Yan, Cold and Arid Regions Environmental and Engineering Research Institute (China)


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