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2022 Vol. 46, No. 5
Article Contents

LIU Kai, DAI Hui-Min, LIU Guo-Dong, SONG Yun-Hong, LIANG Shuai, YANG Ze. 2022. Geochemical classification of the soil in a typical black soil area using the principal component analysis combined with K-means clustering algorithm. Geophysical and Geochemical Exploration, 46(5): 1132-1140. doi: 10.11720/wtyht.2022.0043
Citation: LIU Kai, DAI Hui-Min, LIU Guo-Dong, SONG Yun-Hong, LIANG Shuai, YANG Ze. 2022. Geochemical classification of the soil in a typical black soil area using the principal component analysis combined with K-means clustering algorithm. Geophysical and Geochemical Exploration, 46(5): 1132-1140. doi: 10.11720/wtyht.2022.0043

Geochemical classification of the soil in a typical black soil area using the principal component analysis combined with K-means clustering algorithm

  • The geochemical classification of soils is significant for agricultural and ecological regionalization. Based on the data on major elements in soil obtained from the multi-purpose regional geochemical survey, this study conducted the geochemical classification for a typical black soil area in northeast China using the principal component analysis combined with the K-means clustering algorithm (also referred to as the principal component clustering method). The results are as follows. The soil parent materials are the main factor controlling the characteristics of major elements in the soil. It is the most appropriate to divide the soil samples from the typical black soil area into five categories using the principal component clustering method. Various samples had significantly different major element contents (P<0.05). The geochemical classification results corresponded to the Quaternary geological units to a certain degree and can better reflect the actual distribution of soil parent materials. Moreover, the high SiO2 content in the black soil area in the southern Songhua River indicates desertification, to which much attention should be paid in the protection of the black soil.
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