Tóth T., S. Kabos, L. Pásztor and L. Kuti. 2002. Statistical prediction of the 
presence of salt-affected soils by using digitalized hydrogeological maps. Arid 
Land Research and Management 16:55-68

Since spatial databases created from maps in Geographical Information Systems 
(GIS) do not typically meet the requirements of multivariate tests such as 
multiple linear regression analyses, we used novel, more robust statistical 
techniques for predicting the occurrence of certain categories of a soil map. 
Based on published maps of salt-affected soils (SASs), (hydro)geological 
conditions (all at the scale of 1:500,000) and regionalization, we showed that 
the spatial occurrence of SASs in the Great Hungarian Plain can be predicted 
with an overall precision of 91; 96% for the SASs and 99% for the non-SASs. When 
we separated the non-SASs into potential SAS and non-SAS categories, the overall 
precision was 91%, and 87% for the SASs, 92% for the potential SASs and 94% for 
the non-SASs. The technique of classi(r) cation trees proved to be better than 
the classical Multiple L inear Regression, since it does not have limitations 
regarding the distribution of the data set created from the maps and because it
exibly provided a possibility for incorporating nominal variables through the
previous use of homogeneity analysis by means of alternating least squares
(HOMAL S). Inside the multidimensional space, the (r) rst and most important
(regarding spatial extent) splits for the separation of non-salt-affected cases
from salt-affected ones were realized in the plane of two variables derived with
HOMAL S from the map of ``Textural classes of near-surface geological
formations'' and the map of ``Dominant ion type of groundwater combined with the
map of Taxonomical division of the regions of Hungary. The plane of these
variables was split into (r) ve main bands. The clay band has 70% of SASs and
the mixed silty layer was divided to a bicarbonatic one with 12% SAS, and a
sulfatic one with 65% SAS cover. The remaining sandy band has few SAS, but the
dominance of sulfate in the groundwater indicates a higher cover of SASs and
these soils constituted the two last bands. Other variables entering the
classi(r) cation were the groundwater level above sea level and the depth to
groundwater.