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Measuring Spatial Distribution Characteristics of Heavy Metal Contaminations in a Network-Constrained Environment: A Case Study in River Network of Daye, China

Author

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  • Zhensheng Wang

    (Shenzhen Key Laboratory of Spatial Smart Sensing and Services, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China
    Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, China
    College of Information Engineering, Shenzhen University, Shenzhen 518060, China
    Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 518034, China)

  • Ke Nie

    (Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 518034, China)

Abstract

Measuring the spatial distribution of heavy metal contaminants is the basis of pollution evaluation and risk control. Considering the cost of soil sampling and analysis, spatial interpolation methods have been widely applied to estimate the heavy metal concentrations at unsampled locations. However, traditional spatial interpolation methods assume the sample sites can be located stochastically on a plane and the spatial association between sample locations is analyzed using Euclidean distances, which may lead to biased conclusions in some circumstances. This study aims to analyze the spatial distribution characteristics of copper and lead contamination in river sediments of Daye using network spatial analysis methods. The results demonstrate that network inverse distance weighted interpolation methods are more accurate than planar interpolation methods. Furthermore, the method named local indicators of network-constrained clusters based on local Moran’ I statistic (ILINCS) is applied to explore the local spatial patterns of copper and lead pollution in river sediments, which is helpful for identifying the contaminated areas and assessing heavy metal pollution of Daye.

Suggested Citation

  • Zhensheng Wang & Ke Nie, 2017. "Measuring Spatial Distribution Characteristics of Heavy Metal Contaminations in a Network-Constrained Environment: A Case Study in River Network of Daye, China," Sustainability, MDPI, vol. 9(6), pages 1-11, June.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:6:p:986-:d:100795
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    References listed on IDEAS

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    2. Xuedong Li & Yunhui Liu & Yajuan Chen & Pengyao Li & Zhenrong Yu, 2019. "Village Regrouping in the Eastern Plains of China: A Perspective on Home-Field Distance," Sustainability, MDPI, vol. 11(6), pages 1-17, March.

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