Digital soil mapping of county level in southwest Sichuan mountainous areas
[Objective]The selection of environmental variables and the selection of spatial reasoning methods for soil types were studied to provide references for improving the accuracy of digital soil mapping in counties.[Method]Taking Yanyuan county in Sichuan province as the research area,we selected climate factors,terrain data,and remote sensing images as auxiliary factors for inference mapping.Field sampling point data and environmental covariate factors were used to obtain the basic data of soil environment knowledge.The decision tree classifica-tion method was subsequently used for importance ranking,feature selection,and combination optimization of environmental features.Soil classification mapping accuracy of several soil classification methods,including decision tree classification,support vector machine,random forest,and SoLIM model,was compared.Based on the theory of soil environment relationship,the article explored ways to improve the accura-cy of digital soil mapping in mountainous counties with three-dimensional climate characteristics.[Result](ⅰ)Climate and topographic char-acteristics played an important role in soil classification in the study area.The screening accuracy of soil classification was 83.22％by using a single climate factor as the environmental variable of soil classification.The screening accuracy was increased to 85.78％and 89.43％by adding topographic and biological characteristics in turn.(ⅱ)Compared with other models,the random forest model achieved better mapping results.Using sampling point data as validation data,the overall accuracy of the soil classification was 77.10％,with Kappa coefficient of 0.72.(ⅲ)The influence of climatic factors and topographic factors on regional climatic hydrothermal conditions mainly determined the spa-tial heterogeneity of soil types in the study area.Environmental factors,such as average annual temperature,annual accumulated temperature,annual precipitation,relative humidity,elevation and topographic wetness were closely related to the spatial distribution of major soil types.[Conclusion]In the mountain counties with three-dimensional climate characteristics,the use of climate,topographic and remote sensing data for digital soil classification mapping based on random forest method has good results.
Digital soil mappingClimate factorsTerrain factorsSoil environment relationshipComplex mountainous areas
万方数据
维普
