Digital cartography of soil classes with fuzzy logic in mountain areas

Ángel R. Valera, María C. Pineda, Jesús A. Viloria

Article ID: 1674
Vol 5, Issue 2, 2022

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In order to strengthen the study of soil-landscape relationships in mountain areas, a digital soil mapping approach based on fuzzy set theory was applied. Initially, soil properties were estimated with the regression kriging (RK) method, combining soil data and auxiliary information derived from a digital elevation model (DEM) and satellite images. Subsequently, the grouping of soil properties in raster format was performed with the fuzzy c-means (FCM) algorithm, whose final product resulted in a fuzzy soil class variation model at a semi-detailed scale. The validation of the model showed an overall reliability of 88% and a Kappa index of 84%, which shows the usefulness of fuzzy clustering in the evaluation of soil-landscape relationships and in the correlation with soil taxonomic categories.


Fuzzy Logic; FCM Algorithm; Regression Kriging; Digital Soil Mapping; Soil Classes

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