Spatial analysis of heavy metals in surface soils based on GeoStatistics

Yingjun Sun; Ning Ding; Fei Cai; Fei Meng

doi:10.1117/12.813018

3 November 2008 Spatial analysis of heavy metals in surface soils based on GeoStatistics

Yingjun Sun, Ning Ding, Fei Cai, Fei Meng

Proceedings Volume 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments; 714514 (2008) https://doi.org/10.1117/12.813018
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

The pollution of surface soils caused by heavy metals has been a focus problem discussed. Instead of the acquisition of the "best" estimation of unsampled points, the author paid much attention to the assessment of the spatial uncertainty about unsampled values. The simulation method of Geostatistics, aimed at the same statistics (histogram, Variogram), can generate a set of equally-probable realizations which is particularly useful for assessing the uncertainty in the spatial distribution of attribute values. The case study was from an Urban - Rural transition zone of Shanghai, China. Six kinds of heavy metals (Cu, Pb, Cd, Cr, Hg and As) in agricultural surface soils were analyzed in the paper. Based on the study of spatial variation of different kind of heavy metal, the author got the different realization of the 6 kinds of heavy metals respectively based on the sequential simulation methods. At last, the author drew the conclusion that Cu, Cd and Cr were the dominant elements that influenced soil quality in the study area. At the end of the paper, the author gave the uncertainty map of the six heave metals respectively.

Citation Download Citation

Yingjun Sun, Ning Ding, Fei Cai, and Fei Meng "Spatial analysis of heavy metals in surface soils based on GeoStatistics", Proc. SPIE 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments, 714514 (3 November 2008); https://doi.org/10.1117/12.813018

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