Journal of Geographical Sciences ›› 2019, Vol. 29 ›› Issue (10): 1610-1624.doi: 10.1007/s11442-019-1644-8

• Research Articles • Previous Articles     Next Articles

Exploring the database of a soil environmental survey using a geo-self-organizing map: A pilot study

LIAO Xiaoyong1, TAO Huan1,2,3, GONG Xuegang1,3, LI You1,3   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2018-07-05 Accepted:2018-10-31 Online:2019-10-25 Published:2019-12-09
  • About author:Liao Xiaoyong (1977-), PhD and Professor, specialized in evaluation and remediation of soil pollution. E-mail: liaoxy@igsnrr.ac.cn
  • Supported by:
    Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA19040302);The Key Research Program of the Chinese Academy of Sciences(No.KFZD-SW-111)

Abstract:

A 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.

Key words: self-organizing map, geo-information, heavy metal, soil environmental quality, Hechi