基于多尺度地理加权回归的安徽省土壤pH预测

Prediction of Soil pH based on Multi-scale Geographically Weighted Regression in Anhui Province

基于安徽省140个采样点的土壤pH数据,综合考虑土壤、地形、气候、生物等因子对土壤pH的影响,利用MGWR与GWR模型对安徽省土壤pH空间分布进行预测。结果如下:①MGWR模型的AICc值比GWR减小49.72,其R_(adj)^(2)较GWR模型增加了0.08,模型的残差较GWR模型降低了10.84,拟合效果得到了很大提升;②MGWR的多带宽有效揭示了各环境因子的影响尺度,使得模型可靠性更高。

Based on the soil pH data from 140 sampling sites in Anhui Province,and the effects of soil,topography,climate and biology on soil pH considered comprehensively,this paper predicted the spatial distribution of soil pH in Anhui Province by using the MGWR and GWR models.The results are as follows:①Compared with GWR,AICc value of MGWR model decreased by 49.72,and the R_(adj)^(2) of MGWR model is 0.08 more than that of the GWR model,and the residual of the MGWR model is 10.84 lower than that of the GWR model,and the fitting effect is greatly improved.②The multi-bandwidth of MGWR effectively reveals the influence scale of various environmental factors,which makes the model more reliable.