Journal of Arid Land

, Volume 7, Issue 3, pp 285–295 | Cite as

Uncertainties of snow cover extraction caused by the nature of topography and underlying surface

  • Jun ZhaoEmail author
  • YinFang Shi
  • YongSheng Huang
  • JieWen Fu


Manas River, the largest inland river to the north of the Tianshan Mountains, provides important water resources for human production and living. The seasonal snow cover and snowmelt play essential roles in the regulation of spring runoff in the Manas River Basin (MRB). Snow cover is one of the most significant input parameters for obtaining accurate simulations and predictions of spring runoff. Therefore, it is especially important to extract snow-covered area correctly in the MRB. In this study, we qualitatively and quantitatively analyzed the uncertainties of snow cover extraction caused by the terrain factors and land cover types using TM and DEM data, along with the Per (the ratio of the difference between snow-covered area extracted by the Normalized Difference Snow Index (NDSI) method and visual interpretation method to the actual snow-covered area) and roughness. The results indicated that the difference of snow-covered area extracted by the two methods was primarily reflected in the snow boundary and shadowy areas. The value of Per varied significantly in different elevation zones. That is, the value generally presented a normal distribution with the increase of elevation. The peak value of Per occurred in the elevation zone of 3,700–4,200 m. Aspects caused the uncertainties of snow cover extraction with the order of sunny slope>semi-shady and semi-sunny slope>shady slope, due to the differences in solar radiation received by each aspect. Regarding the influences of various land cover types on snow cover extraction in the study area, bare rock was more influential on snow cover extraction than grassland. Moreover, shrub had the weakest impact on snow cover extraction.


Landsat TM Normalized Difference Snow Index (NDSI) snow cover uncertainty Manas River Basin 


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Copyright information

© Xinjiang Institute of Ecology and Geography, the Chinese Academy of Sciences and Springer - Verlag GmbH 2015

Authors and Affiliations

  • Jun Zhao
    • 1
    Email author
  • YinFang Shi
    • 1
  • YongSheng Huang
    • 1
  • JieWen Fu
    • 1
  1. 1.College of Geography and Environment ScienceNorthwest Normal UniversityLanzhouChina

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