文献类型：期刊文章

作　　者：王彬武[1] 周卫军[1] 马苏[2] 刘少坤[1] 于良艺[1] 郑超[1] 王金国[1]

机构地区：[1]湖南农业大学资源环境学院,湖南长沙410128 [2]湖南师范大学GIS研究中心,湖南长沙410081

出　　处：《Agricultural Science & Technology》

基　　金：Supported by National Natural Science Foundation of China(41071204);Hunan Provincial Innovation Foundation for Postgraduate(CX2011B310)~~

年　　份：2012

卷　　号：13

期　　号：4

起止页码：838-842

语　　种：中文

收录情况：CAB、CAS、CSA、CSA-PROQEUST、PROQUEST、普通刊

摘　　要：[Objective] The objective of this project was to evaluate and compare spa- tial estimation accuracy by ordinary kriging and regression kriging with MODIS data, predicting SOM contents using limited available data in Shimen County, Hunan Province, China. [Method] Terrain parameters （derived from DEM） and Normalized differential vegetation index （NDVI）, Land surface temperature （LST） （derived from MODIS data） were used as auxiliary data to predict the SOM spatial distribution. The mean error （ME） and mean square error （RMSE） were adopted to validate the SOM prediction accuracy. The descriptive statistics and data transformation were conducted by using computer technology. [Result] Regression kriging with terrain and remotely sensed data was superior to ordinary kriging in the case of limited available samples; even the linear relationship between environmental variables and SOM content was moderate. The accuracy assessment showed that the regression kriging method combining with environmental factors obtained a lower mean predication error and root mean square prediction error. The relative improvement was 6.03% compared with ordinary kriging. [Conclusion] Remotely sensed data such as MODIS im- age have the potential as useful auxiliary variables for improving the precision and reliability of SOM prediction in the hilly regions.

关 键 词：Regression-kriging  MODIS Soil organic matter  Spatial prediction  

分 类 号：S153.62]