A review of the article "Spatial Data Mining for Enhanced Soil Map Modeling".
Written in 2005; 900 words; 1 sources; $ 35.95
Paper Summary:
This paper discusses the methodology described in an article by Christopher J. Moran and Elisabeth N. Bui entitled "Spatial Data Mining for Enhanced Soil Map Modeling". This paper notes the terrain attributes the researchers saw as better-suited to landscape description as predictors of soil type, using a map sampling strategy and testing it on a region in eastern Australia.
From the Paper:
"Christopher J. Moran and Elisabeth N. Bui test a new methodology for improving the quality of the soil map models generated by rule induction. In their method, the researchers considered terrain attributes they saw as better-suited to landscape description as predictors of soil type, using a map sampling strategy. The authors use the Murray-Darling Basin (MBD) in eastern Australia as an example of an area not now covered by any detailed form of land-resource inventory, and the authors use their method of spatial modeling to develop soil-landscape models in areas that have been surveyed and then to extend these across the unmapped areas. While this is a logical approach, it raises the question of how certain the authors can be that the model for mapped areas can be extended across unmapped areas. "
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