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Proceedings Paper

Snow mapping for water resource management using MODIS satellite data in northern Xinjiang, China
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Paper Abstract

Snow is the most important freshwater resource in northern Xinjiang, which is a typical inland arid ecosystem in western China. Snow mapping can provide useful information for water resource management in this arid ecosystem. An applicable approach for snow mapping in Northern Xinjiang Basin using MODIS data was proposed in this paper. The approach of linear spectral mixture analysis (LSMA) was used to calculate snow cover fractions within a pixel, which was used to establish a regression function with NDSI at a 250-meter grid resolution. Field campaigns were conducted to examine whether NDSI can be used to extend the utility of the snow mapping approach to obtain sub-pixel estimates of snow cover. In addition, snow depths at 80 sampling sites were collected in the study region. The correlation between image reflectivity and snow depth as well as the comparison between measured snow spectra and image spectra were analyzed. An algorithm was developed on the basis of the correlation for snow depth mapping in the region. Validation for another dataset with 50 sampling sites showed an RMSE of 1.63, indicating that the algorithm was able to provide an estimation of snow depth at an accuracy of 1.63cm. The results indicated that snow cover area can reach 81% and average snow depth was 13.8 cm in north Xinjiang in January 2005. Generally speaking, the snow cover and depth had a trend of gradually decreasing from north to south and from the surroundings to the center. Temporally, the cover reached a maximum in early January, and the depth reached a maximum was ten days later. Snow duration was so different in different regions with the Aletai region having the longest and the Bole having the shortest. In the period of snow melting, snow depth decreased earlier, afterward snow cover dwindled. Our study showed that the spatial and temporal variation of snow cover was very critical for water resource management in the arid inland region and MODIS satellite data provide an alternative for snow mapping through dedicated development of mapping algorithms suitable for local application.

Paper Details

Date Published: 2 October 2008
PDF: 10 pages
Proc. SPIE 7104, Remote Sensing for Agriculture, Ecosystems, and Hydrology X, 710414 (2 October 2008); doi: 10.1117/12.800203
Show Author Affiliations
Huan Pei, Nanjing Univ. (China)
Zhihao Qin, Nanjing Univ. (China)
Institute of Agro-Resources and Regional Planning (China)
Shifeng Fang, Xinjiang Univ. (China)
Zhihui Liu, Xinjiang Univ. (China)

Published in SPIE Proceedings Vol. 7104:
Remote Sensing for Agriculture, Ecosystems, and Hydrology X
Christopher M. U. Neale; Manfred Owe; Guido D'Urso, Editor(s)

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