%0 Journal Article
%T On Comparison of Spatial Interpolation Methods of Daily Rainfall Data: A Case Study of Shenzhen<br>日降水量的空间插值方法与应用对比分析——以深圳市为例
%A SONG Liqiong
%A TIAN Yuan
%A WU Lun
%A ZHANG Hui
%A <br>宋丽琼
%A 田原
%A 邬伦
%A 张晖
%J 地球信息科学
%D 2008
%I 
%X Discrete or continuous rainfall data are required to run many GIS models for environment and planning.The paper attempts to make a general comparison on different spatial interpolation methods.It carried out a study on four spatial interpolation methods: Inverse Distance Weighing(IDW),Local Polynomial,Ordinary Kriging and co-Kriging with respect to elevation.Daily rainfall data obtained from 36 rainfall stations during 27 inconsecutive days in the rainy season of 2006 in Shenzhen was employed in this study.Cross validation of the results shows that the four methods could to some extent reflect the rainfall situation of the region,yet the four interpolated surfaces are more smoothing than the practical circumstance.Particularly,IDW is the most smoothing one of the four.Besides,all the criteria(Mean Error,Mean Absolute Error,Root Mean Square Error and Percentage Error)that brought up in our study to measure accuracy of the four methods demonstrated that Ordinary Kriging and co-Kriging methods are superior to Local Polynomial and IDW.Inclusion of elevation in the co-Kriging method does not lead to improvement of result compared with Ordinary Kriging method.Furthermore,the interpolation data was grouped according to elevation and average daily rainfall and the same criteria above was bought to the statistics of those groups.Comparison on the criteria reveals that,the interpolated result on rain gauge stations with high elevation tend to larger than the observed data,and those rain gauge stations with low elevation are on the contrary.The interpolation error increases sharply while the average daily rainfall is bigger than 50mm.
%K daily rainfall
%K spatial interpolation
%K inverse distance weighing
%K local polynomial
%K ordinary kriging
%K co-kriging<br>日降水量
%K 空间插值
%K 距离权重倒数法
%K 局部多项式法
%K 普通克里金法
%K 协克里金法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=DA72A78627FE64EAA572951EA05D274A&jid=366CD77E372F1875C812440223DE7AFB&aid=40273B12E126D721BF051ABE23DEB0EE&yid=67289AFF6305E306&vid=F3090AE9B60B7ED1&iid=94C357A881DFC066&journal_id=1560-8999&journal_name=地球信息科学&referenced_num=3&reference_num=27