Indices for estimating fractional snow cover in the western Tibetan Plateau

• Published in: Journal of glaciology Vol. 55; no. 192; pp. 737 - 745
• Main Authors: Shreve, Cheney M., Okin, Gregory S., Painter, Thomas H.
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 2009; International Glaciological Society
• Subjects: Earth, ocean, space; Exact sciences and technology; External geophysics; Snow. Ice. Glaciers; Far East; Asia; China; Qinghai-Xizang Plateau; China, People's Rep., Xizang, Tibetan Plateau; time variations; Linear regression; Moderate resolution imaging spectroradiometer; Space remote sensing; spectral analysis; Satellite observation; Landsat satellite; Polar orbiting satellite; Spatial distribution; Water equivalent; spatial variations; Snow cover; Computing method
• DOI: 10.3189/002214309789470996
• ISSN: 0022-1430

Snow cover in the Tibetan Plateau is highly variable in space and time and plays a key role in ecological processes of this cold-desert ecosystem. Resolution of passive microwave data is too low for regional-scale estimates of snow cover on the Tibetan Plateau, requiring an alternate data source. Optically derived snow indices allow for more accurate quantification of snow cover using higher-resolution datasets subject to the constraint of cloud cover. This paper introduces a new optical snow index and assesses four optically derived MODIS snow indices using Landsat-based validation scenes: MODIS Snow-Covered Area and Grain Size (MODSCAG), Relative Multiple Endmember Spectral Mixture Analysis (RMESMA), Relative Spectral Mixture Analysis (RSMA) and the normalized-difference snow index (NDSI). Pearson correlation coefficients were positively correlated with the validation datasets for all four optical snow indices, suggesting each provides a good measure of total snow extent. At the 95% confidence level, linear least-squares regression showed that MODSCAG and RMESMA had accuracy comparable to validation scenes. Fusion of optical snow indices with passive microwave products, which provide snow depth and snow water equivalent, has the potential to contribute to hydrologic and energy-balance modeling in the Tibetan Plateau.