Interpretation and Integration of Pedological Data in Land Evaluation Systems

1 Szent István University, Faculty of Horticultural Science, Department of Soil Science and Water Management, H-1118 Budapest, Hungary
2 Hungarian Academy of Sciences, Geographical Institute, Research Centre for Astronomy and Earth Sciences, H-1112 Budapest, Hungary


JUHOS, K. and B. MADARÁSZ, 2016. Interpretation and integration of pedological data in land evaluation systems. Bulg. J. Agric. Sci., 22: 209–215

Highly standardized land evaluation systems and applicable methods are necessary for an ecologically and economically sustainable land use, as the most important requirement. In general, available pedological data and their interpretation define the applicability of different land evaluation systems. Our study focuses on (1) the summary of already applied pedological land information; (2) the main methods of data interpretation and integration in the land evaluation systems; (3) the up to date quantitative land evaluation procedures, with the involvement of mathematical-statistical tools in the studies. Soil classification systems and other complex pedological qualifiers are the basis of qualitative and/or the semi-quantitative land evaluation systems. Selection, interpretation and integration of the simple soil properties and indicators are not easy to use, because those simple parameters should be evaluated in a highly multifactorial environmental context. Development of quantitatively flexible indices and mathematical and statistical methods, that are able to explore pedological and environmental factors in land productivity, beside the most accepted economic ones, seems to be highly necessary nowadays.

Key words: land capability, land suitability, soil quality index, multiple criteria decision making
Abbreviations: AHP – analytical hierarchy process; IQI – Integrated Quality Index; MCDM – multiple criteria decision making; MDS – minimum data set; NQI – Nemoro Quality Index; PCA – principal component analysis; PLS – partial squares regression; TDS – total data set; USDA-LCC – US Department of Agriculture Land Capability Classification

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