基于大尺度低密度样点的东北土壤全氮空间插值方法比较

基于全国第二次土壤普查东北地区土壤数据,以ArcGIS和GS⁺软件为支撑,对比分析了反距离加权法(IDW)、径向基函数(RBF)、普通克里金(OK)和回归克里金(RK)4种地统计空间插值方法在7个不同样本容量下土壤全氮含量(STNC)的空间插值效果。结果表明,由普查数据得到的东北地区STNC在0.08~21.48 g/kg之间,数据变异性较大;STNC空间结构表现出中强度空间自相关性,空间自相关范围大于同区域的小尺度采样研究;样本容量<171时,STNC空间变异性发生变化,空间结构特征和精度检验水平难以确信。4种空间插值方法对STNC空间趋势表达均呈现从东北向西南方向递减规律,空间趋势预测效果为:RK >OK >RBF >IDW。RK方法通过线性回归分析添加了阳离子交换容量(CEC)、年均温(MAT)、土层厚度(d)和pH值等辅助信息,比IDW,RBF和OK方法的插值精度分别提高了19.40%,18.50%和16.15%;在不同样本容量下RK方法的插值精度较为稳定且对无样点区STNC的空间趋势预测也体现出了更多细节信息,因此对于大尺度低密度采样的土壤属性空间插值可重点考虑RK方法。

Comparison of Spatial Interpolation Methods for Soil Total Nitrogen Content at Large Scale Using Low Density Soil Survey Data in Northeast China

Based on the relatively low density sampling data from China's second national soil survey in northeast China, we compared the erformance of four spatial interpolation methods, inverse distance weighting(IDW), radial basis function(RBF), ordinary Kriging(OK) and regression Kriging(RK), under seven sample sizes in generating digital map of soil total nitrogen content at large scale based on the software ArcGIS and GS⁺. Results showed that soil total nitrogen content was in the range of 0.08~21.48 g/kg with great variability. The Nugget effect showed a medium strong spatial autocorrelation of soil total nitrogen content in the region, and the range of spatial autocorrelation was greater than research on smaller scale in the same region; Spatial variability of soil total nitrogen content changed when sample size was less than 171, in this case, spatial structure and accuracy test of interpolation were unbelievable. All of the four compared methods predicted the spatial pattern of soil total nitrogen content well with decreasing from northeast to southwest. The accuracy of interpolation changed in the order of RK >OK >RBF >IDW. With incorporated auxiliary variables of soil cation exchange capacity, soil depth, soil pH value and annual mean air temperature, the RK improved accuracy by 19.40%, 18.50% and 16.15% than IDW, RBF and OK, respectively. It also exhibited more details on soil total nitrogen content variation at the areas with sparse sample points. It suggested that the RK is a potential spatial interpolation method to improve the soil mapping accuracy at large area with low density sample sites.