A Com-Gis Based Decision Tree Model Inagricultural Application

Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 293)


The problem of agricultural soil pollution by heavy metals has been receiving an increasing attention in the last few decades. Geostatistics module in ArcGIS, could not however efficiently simulate the spatial distribution of heavy metals with satisfied accuracy when the spatial autocorrelation of the study area severely destroyed by human activities. In this study, the classificationand regression tree (CART) has been integrated into ArcGIS using ArcObjects and Visual Basic for Application (VBA) to predict the spatial distribution of soil heavy metals contents in the area severely polluted. This is a great improvement comparing with ordinary Kriging method in ArcGIS. The integrated approach allows for relatively easy, fast, and cost-effective estimation of spatially distributed soil heavy metals pollution.


Geographic Information System Multivariate Adaptive Regression Spline Soil Heavy Metal Component Object Model Soil Heavy Metal Content 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Institution of Remote Sensing & Information System ApplicationZhejiang UniversityHangzhouChina

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