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Remote Sensing Technology and Application  2007, Vol. 22 Issue (1): 39-44    DOI: 10.11873/j.issn.1004-0323.2007.1.39
    
Comparison of Spatial Interpolation Methods of Snow Depth in the West of China
TANG Guo-dong, KE Chang-qing
(Department of Urban and Resources Sciences,Nanjing University,Nanjing210093,China)
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Abstract  

The spatial interpolation methods of Inverse Distance Weighted (IDW), Spline and Kriging are utilized for comparison study on spatial interpolation of annual average snow depth from 113 observatories in the west of China (79.05°~103.57°E,27.17°~48.05°N). The principles of these three methods are different from each other. IDW determines cell values using a linear-weighted combination set of sample points. Spline estimates values using a mathematical function that minimizes overall surface curvature. And ordinary Kriging is a powerful statistical interpolation method which assumes that the distance or direction between sample points reflects a spatial correlation that can be used to explain variation in the surface. Compared with the unsatisfactory interpolation results of IDW and Spline, the result of ordinary Kriging is more close to the real snow depth distribution and can represents the spatial structure of snow depth distribution better. The main reasons which affect the precision are the small number of observatories and their asymmetric spatial distribution. However, the accuracy of spatial interpolation can be improved through reasonable design of sampling, combining deterministic and stochastic methods, and considering the influencing factors of snow distribution such as the terrain and climate.

Key words:  Kriging      IDW      Spline      Snow depth      The west of China     
Received:  10 May 2006      Published:  14 October 2011
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Cite this article: 

TANG Guo-dong, KE Chang-qing. Comparison of Spatial Interpolation Methods of Snow Depth in the West of China. Remote Sensing Technology and Application, 2007, 22(1): 39-44.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2007.1.39     OR     http://www.rsta.ac.cn/EN/Y2007/V22/I1/39


[1] Wu T W, Qian Z A, The Relation Between the Tibetan Winter Snow and the Asian Summer Monsoon and Rainfall: An Observational Investigation
[J]. Journal of Climate 16, 2003,2038-2051.

[2] 陈烈庭.青藏高原异常雪盖和ENSO在1998年长江流域洪涝中的作用
[J].大气科学,2001,25(2):184-192.

[3] 曹梅盛,李培基.中国西部积雪微波遥感监测
[J].山地研究,1994,12(4):230-234.

[4] 车涛,李新,高峰.青藏高原积雪深度和雪水当量的被动微波遥感反演
[J].冰川冻土,2004,26(3):363-368.

[5] 冯锦明,赵天保,张英娟.基于台站降水资料对不同空间内插方法的比较
[J].气候与环境研究,2004,9(2):261-277.

[6] 李新,程国栋,卢玲.青藏高原气温分布的空间插值方法比较
[J].高原气候,2003,22(6):565-573.

[7] 冯学智,柏延臣,史正涛,等.北疆地区积雪深度的克里格内插估计
[J].冰川冻土,2000,12:358-361.

[8] 柯长青,李培基.青藏高原积雪分布与变化特征
[J].地理学报,1998,53(3):209-215.

[9] 韦志刚,黄荣辉,陈文,等.青藏高原地面站积雪的空间分布和年代际变化特征
[J].大气科学,2002,26(4):496-508.

[10] Collins F C. A Comparison of Spatial Interpolation Techniques in Temperature Estimation
[S/OL].http://www.ncgia.ucsb. edu/conf/SANTA-FE-CD-ROM/sf-papers/collinsfred/collins.html, 1999.

[11] 李新,程国栋,卢玲.空间内插方法的比较
[J].地球科学进展,2000,15(3):260-265.

[12] 侯景儒,尹镇南,李维明,等.实用地质统计学
[M].北京:地质出版社,1998.

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