Spatial autocorrelation analysis of soil pollution data in central Taiwan

Hone-Jay Chu, Yu Pin Lin, Tsun Kuo Chang

研究成果: Conference contribution

4 引文 斯高帕斯(Scopus)

摘要

Soil pollutant concentrations such as heavy metal Cr, Cu, Ni, and Zn were collected at 1082 sampling sites in Changhua county of Taiwan. This study applies a spatial autocorrelation analysis for identifying multiple soil pollution hotspots based on original and re-sampling data in the study area. Results show that the multiple hotspots for four heavy metals and are strongly related to the locations of industrial plants and irrigation systems in the study area. Soil pollution hotspots are clearly defined based on the LISA (local indicators of spatial association) cluster maps. The cluster maps show a clear spatial autocorrelation of soil pollutants in cLHS samples, especially for Cr. Furthermore, the maps explore the spatial patterns of hazards and capture the hotspot areas without exhaustive sampling in the study area.

原文English
主出版物標題Proceedings - 2011 International Conference on Computational Science and Its Applications, ICCSA 2011
頁面219-222
頁數4
DOIs
出版狀態Published - 2011 九月 5
事件11th International Conference on Computational Science and Its Applications, ICCSA 2011 - Santander, Spain
持續時間: 2011 六月 202011 六月 23

出版系列

名字Proceedings - 2011 International Conference on Computational Science and Its Applications, ICCSA 2011

Other

Other11th International Conference on Computational Science and Its Applications, ICCSA 2011
國家Spain
城市Santander
期間11-06-2011-06-23

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications

指紋 深入研究「Spatial autocorrelation analysis of soil pollution data in central Taiwan」主題。共同形成了獨特的指紋。

引用此