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空间回归分析在土壤属性预测制图中的应用
引用本文:刘晓冰,程道全,刘鹏飞,宋 轩,陈 杰.空间回归分析在土壤属性预测制图中的应用[J].土壤,2013,45(3):533-539.
作者姓名:刘晓冰  程道全  刘鹏飞  宋 轩  陈 杰
作者单位:1. 郑州大学水利与环境学院,郑州,450001
2. 河南省土壤肥料站,郑州,450002
基金项目:国家自然科学基金项目(40971128)资助
摘    要:以河南省孟津县为研究区,选取坡度、高程、地面曲率和复合地形指数(CTI)作为表层土壤缓效钾含量空间预测的环境协变量,系统探讨了空间回归分析技术在土壤属性预测制图中的应用.结果表明:土壤缓效钾的空间自相关距离阈值约为10 000 m,与坡度、高程和地面曲率存在显著相关性;尽管空间回归模型的预测精度和普通回归模型相近,但前者可以更加准确地表征土壤缓效钾的空间分布格局及空间分异细节特征.

关 键 词:土壤属性  土壤缓效钾  环境协变量  空间回归模型  土壤预测制图

Study on Predicated Mapping of Soil Property Based on Spatial Regression Analysis
LIU Xiao-bing,CHENG Dao-quan,LIU Peng-fei,SONG Xuan,CHEN Jie.Study on Predicated Mapping of Soil Property Based on Spatial Regression Analysis[J].Soils,2013,45(3):533-539.
Authors:LIU Xiao-bing  CHENG Dao-quan  LIU Peng-fei  SONG Xuan  CHEN Jie
Institution:School of Environment and Water Conservancy, Zhengzhou University
Abstract:In this paper Mengjin County of Henan Province we selected as the study area, slowly available K contained in topsoil was spatially predicated by the method of spatial regression analysis with the terrain characteristics, included slope, elevation, curvature and CTI. The results indicated that the slowly available K had a distance threshold of spatial autocorrelation around 10 000 m and a significant correlation between slope, elevation, curvature and soil available K. Although output precision of the spatial regression model was quite similar to that of the classic regression ones, the spatial regression model displayed an evident advantage to reveal further the spatial distribution pattern and variation characteristics of soil property.
Keywords:Soil property  Slowly available potassium  Environmental covariate  Spatial regression model  Predictive soil mapping
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