Li You; Liao Xiaoyong; Tao Huan; Gong Xuegang
Source Publicationjournalofgeographicalsciences
AbstractA model integrating geo-information and self-organizing map (SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals (As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows: (1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd. (2) As and Pb had a similar topological distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements. (3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers, factories, and ore zones. (4) The variations of contamination index (CI) followed the trend of construction land (1.353) > forestland (1.267) > cropland (1.175) > grassland (1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.
Document Type期刊论文
First Author Affilication中国科学院地理科学与资源研究所
Recommended Citation
GB/T 7714
Li You,Liao Xiaoyong,Tao Huan,et al. exploringthedatabaseofasoilenvironmentalsurveyusingageoselforganizingmapapilotstudy[J]. journalofgeographicalsciences,2019,29(10):1610.
APA Li You,Liao Xiaoyong,Tao Huan,&Gong Xuegang.(2019).exploringthedatabaseofasoilenvironmentalsurveyusingageoselforganizingmapapilotstudy.journalofgeographicalsciences,29(10),1610.
MLA Li You,et al."exploringthedatabaseofasoilenvironmentalsurveyusingageoselforganizingmapapilotstudy".journalofgeographicalsciences 29.10(2019):1610.
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