Institute of Remote Sensing and Information System Application, Zhejiang University, Hangzhou, 310029, China.
Environ Monit Assess. 2009 Nov;158(1-4):419-31. doi: 10.1007/s10661-008-0594-x. Epub 2008 Nov 13.
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.
利用决策树模型与 ArcGIS Engine 9 的集成，并结合 Microsoft Visual Basic 6.0 中的 COM 实现，开发了一个整合地理信息系统和重金属污染评估系统的分类回归树（CART）模型，以评估中国浙江富阳的重金属污染情况。该模型提供了一种方法，可以评估土壤 Zn 含量的空间分布，并具有较高的预测精度。CART 估算的 Zn 浓度类别具有近 90%的准确率，这与受人类活动严重破坏的研究区域的空间自相关的普通克里金方法相比，有了很大的改进。此外，它还可以用于研究重金属污染与环境和人为变量之间的相互关系。此外，该研究还对空间模型预测进行了进一步的应用和调查。
