Spatial autocorrelation analysis of soil pollution data in central Taiwan

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2011 International Conference on Computational Science and Its Applications, ICCSA 2011
Pages219-222
Number of pages4
DOIs
Publication statusPublished - 2011 Sep 5
Event11th International Conference on Computational Science and Its Applications, ICCSA 2011 - Santander, Spain
Duration: 2011 Jun 202011 Jun 23

Publication series

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

Other

Other11th International Conference on Computational Science and Its Applications, ICCSA 2011
CountrySpain
CitySantander
Period11-06-2011-06-23

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications

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