Spatial soil zinc content distribution from terrain parameters: a GIS-based decision-tree model in Lebanon.
Heavy metal contamination has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, our study proposes a regression-tree model to predict the concentration level of zinc in the soils of northern Lebanon (as a case study of Mediterranean landscapes) under a GIS environment. The developed tree-model explained 88% of variance in zinc concentration using pH (100% in relative importance), surroundings of waste areas (90%), proximity to roads (80%), nearness to cities (50%), distance to drainage line (25%), lithology (24%), land cover/use (14%), slope gradient (10%), conductivity (7%), soil type (7%), organic matter (5%), and soil depth (5%). The overall accuracy of the quantitative zinc map produced (at 1:50.000 scale) was estimated to be 78%. The proposed tree model is relatively simple and may also be applied to other areas.
Lebanese University, Faculty of Letters and Human Sciences, Department of Geography, GIS Research Laboratory, P.O. Box 90-1065, Fanar, Lebanon. rania.boukheir@agrsci.dk
Rania
R
Bou Kheir
Mogens H
MH
Greve
Chadi
C
Abdallah
Tommy
T
Dalgaard
D000465:Algorithms; D003663:Decision Trees; D040362:Geographic Information Systems; D005843:Geography; D007861:Lebanon; D008962:Models, Theoretical; D012989:Soil Pollutants / Q000032:analysis*; D015032:Zinc / Q000032:analysis*
D012989:Soil Pollutants; D015032:Zinc