Research on spatial interpolation of soil organic carbon on reclaimed land at Pingshuo opencast coal mine

It has important theoretical and practical value to monitor and evaluate reclaimed farmland by optimizing spatial interpolation to obtain the organic carbon content of reconstructed soil in mining area. To find out which is the best method for predicting the spatial distribution and variation of soil organic carbon in reclamation mining area,this study applied and compared multiple linear regression,inverse distance weighting method,ordinary kriging method and regression kriging in Pingshuo mining area. Prediction results were validated by Pearson’s correlation coefficient,RMS error,Root mean Square Error and Accuracy. Results showed that:① The spatial variation coefficient of soil organic carbon is high in reclaimed dumps of opencast coal mine,reaching up to 145. 408%,which belongs to high level;② In terms of accuracy,the regression kriging is the best method,its Pearson’ s Correlation coefficient reaches 0. 984; RMS error,Root mean Square Error and Accuracy are -0. 012,0. 211,0. 991 respectively. Multiple linear regression takes the second place;the effects of inverse distance weighting method and ordinary kriging method are the worst. ③ According to the expressed details,regression kriging is more meticulous,which can also depict the beating and uncertainty tendency of the data;Inverse distance weighting method and ordinary kriging method have obvious smoothing effects,meaning the spatial variation is continuous. Regression kriging has obvious advantages to predict the content of organic carbon in the reclaimed dumps at opencast coal mine.