Abstract:329 soil samples were collected from the citrus growing areas in Honghuatao Town,Yidu City,Hubei Province.Based on the principle of spatial stratified heterogeneity,the top five major impact factors having the greatest correlation with soil organic matter (SOM) were selected with the GeoDetector software.Using the interpolation results of ordinary Kriging as control,the global model multiple linear regression (MLR),partial least squares regression (PLSR) and local model geographical weighted regression (GWR) were established by the soil organic matter and its main environmental factors.After analyzing the structure of the model residuals,GWRMLR and GWRPLSR were constructed as the extensions of GWR model.The results showed that the mean square error (MSE),root mean square error (RMSE),relative analysis error (RPD) and the correlation coefficient (r) between measured and predicted values of GWRPLSR were 9.834,3.136,1.468,0.743,respectively.The GWRPLSR model had the highest prediction accuracy,followed by GWRMLR.In summary,except for the spatial correlation between SOM and its major impact factors,analyzing model residuals can further eliminate the predicted instability.Therefore,taking the model residual terms into consideration is more suitable to predict the regional SOM spatial distribution and digital soil mapping.
