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Using remote sensing information to estimate snow hazard and extreme snow load in China

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Abstract

The consideration of snow hazard and snow load is important for lightweight structures in cold regions. The assessment of spatial variation of the extreme snow hazard and ground snow load is complicated because the measurements of annual maximum snow depth or snow water equivalent are not always available or the spatial distribution of measuring stations is not sufficiently dense. An alternative is to use the available snow depth data derived from remote sensing for such an assessment. Several observations are made by carrying out such an assessment for the Mainland China using the derived data from 1979 to 2010. These include that there is no temporal trend in the annual maximum snow depth; the coefficient of variation of the annual maximum snow depth obtained by using the derived data is greater than that obtained by using the measurement data; and the results of the assessment by using the derived data may be useful to understand the spatial trends of the snow hazard and ground snow load. However, there are differences between the estimated snow hazard and ground snow load by using the derived snow depth from remote sensing and those estimated based on ground snow depth measurements.

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Acknowledgements

Financial support received from the National Natural Science Foundation of China (Grant No. 51478147) and from the National Science and Engineering Research Council of Canada is much appreciated. The authors are grateful to Heilongjiang Bureau of Meteorology for providing part of the observed snow depth data used in this study.

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Authors and Affiliations

  1. Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, Harbin, 150090, China

    H. M. Mo & F. Fan

  2. Key Lab of Smart Prevention and Mitigation of Civil Engineering Disaster of the Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin, 150090, China

    H. M. Mo & F. Fan

  3. School of Civil Engineering, Harbin Institute of Technology, Harbin, 150090, China

    H. M. Mo & F. Fan

  4. Department of Civil and Environmental Engineering, University of Western Ontario, London, N6A 5B9, Canada

    H. P. Hong

Authors
  1. H. M. Mo
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  2. H. P. Hong
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  3. F. Fan
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Correspondence to F. Fan.

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Mo, H.M., Hong, H.P. & Fan, F. Using remote sensing information to estimate snow hazard and extreme snow load in China. Nat Hazards 89, 1–17 (2017). https://doi.org/10.1007/s11069-017-2939-7

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  • DOI: https://doi.org/10.1007/s11069-017-2939-7

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