J4 ›› 2011, Vol. 49 ›› Issue (05): 964-.

• 环境科学 • 上一篇    

3种空间插值方法在道路尘中Pb监测数据统计处理中的应用比较

田雷, 董德明, 魏强, 房春生   

  1. 吉林大学 环境与资源学院, 长春 130012
  • 收稿日期:2010-12-10 出版日期:2011-09-26 发布日期:2011-09-27
  • 通讯作者: 房春生 E-mail:fangcs@jlu.edu.cn

Comparison of Three Spatial Interpolation Methods for |Statistical Processing of Lead Monitoring Data in Road Dust

TIAN Lei, DONG Deming, WEI Qiang, FANG Chunsheng   

  1. College of Environment and Resources, Jilin University, Changchun 130012, China
  • Received:2010-12-10 Online:2011-09-26 Published:2011-09-27
  • Contact: FANG Chunsheng E-mail:fangcs@jlu.edu.cn

摘要:

以福建省龙岩市道路扬尘监测分析中的Pb元素质量浓度为例, 选取地统计学中具有代表性的反距离权重法、 径向基函数法、 普通克里格法3种空间插值方法, 进行污染物浓度的空间插值, 通过对插值结果进行交叉验证和评价, 对这3种插值方法进行对比研究. 道路扬尘样本共56个, 其中44个样本用于空间插值, 其余12个样本用于结果验证. 结果表明, 普通克里格法的平均预测误差为-0.129 6, 均方根预测误差为24.19, 与其他两种方法相比, 在检验标准上有明显优势, 故普通克里格法对于描述污染物质量浓度的空间分布趋势效果最佳, 而其他两种方法对Pb元素的空间分布插值精度较差.

关键词: 空间插值; 环境监测数据; 统计处理

Abstract:

Taking the concentrations of lead in the monitoring and analysis data of the road dust in Longyan city as an example, we made spatial interpolation study for pollutant concentration using three types of representative interpolation methods in geostatistics, inverse distance weighted (IDW), radial basis function (RBF) and ordinary Kriging (OK). By validating and appraising the resu
lt, we compared the three interpolation methods. Among the total 56 samples, 44 road dust samples were used for interpolation, and the rest 12 samples were used for validation. Compared with those of other interpolation methods, the ME of OK is -0.129 6, the RMSE of OK is 24.19. OK is apparently better than IDW and RBF for describing the error parameters. The results of comparison indicate that OK shows the best result in characterizing spatial distribution trend of pollutant concentration; IDW and RBF interpolate methods show less accuracy for the spatial distribution of lead elements.

Key words: spatial interpolation, environment monitoring data, statistical processing

中图分类号: 

  • X820.3