title: Integrating classification and regression tree (CART) with GIS for assessment of heavy metals pollution.
abstract: The classification and regression tree (CART) model integrated with geographical information systems and the assessment of heavy-metals pollution system was developed to assess the heavy metals pollution in Fuyang, Zhejiang, China. The integration of the decision tree model with ArcGIS Engine 9 using a COM implementation in Microsoft Visual Basic 6.0 provided an approach for assessing the spatial distribution of soil Zn content with high predictive accuracy. The Zn concentration classes estimated by CART assigned the right classes with an accuracy of near 90%. This is a great improvement compared to the ordinary Kriging method for the spatial autocorrelation of the study area severely destroyed by human activities. Also, it can be used to investigate the inter-relationships between the heavy metals pollution and environmental and anthropogenic variables. Moreover, the research presents model predictions over space for further applications and investigations.
authors.affiliation: Institute of Remote Sensing and Information System Application, Zhejiang University, Hangzhou, 310029, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Cheng
authors.forename: Xiuying
authors.initials: X
authors.lastname: Zhang
authors.forename: Ke
authors.initials: K
authors.lastname: Wang
authors.forename: Xuelong
authors.initials: X
authors.lastname: Dai
mesh_terms: D002681:China; D004784:Environmental Monitoring / Q000379:methods*; D004787:Environmental Pollution / Q000032:analysis*; D040362:Geographic Information Systems; D019216:Metals, Heavy / Q000032:analysis*; D008962:Models, Theoretical
chemical_list: D019216:Metals, Heavy