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.
Bou Kheir
Rania
R
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
Greve
Mogens H
MH
Abdallah
Chadi
C
Dalgaard
Tommy
T
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