Digital mapping of soil erosion using ordinal regression

Cartography

UDC:

528.946:631.459.22

DOI:

10.22389/0016-7126-2021-967-1-23-33

1 Buryak Z.A.

2 Ukrainsky P.A.

3 Lukin S.V.

4 Terekhin E.A.

Year:

2021

№:

967

Pages:

23-33

Belgorod State University

1,

2,

3,

4,

Abstract:

The authors describe a methodology of automated making soil erosion class maps using ordinal logistic regression, where relief characteristics are predictors. For mapping, a probabilistic approach is used, in which it is proposed to evaluate the possibility of belonging to several arbitrary erosion classes for each point in space: unwashed, slightly washed and medium washed soils. The model was developed for ordinary chernozem soils of arable lands. Ground data on the degree of soil erosion were obtained from the materials of the latest round of a continuous soil erosion survey, 491 points. Basing on the spatial analysis of a high-resolution digital elevation model, geomorphometric characteristics were obtained: slope, aspect, and index of the topographic position. From here, three raster probability models for three categories of erosion were generated. The resulting erosion map is a classified raster, where each cell corresponds to the degree of blurring that had a maximum probability at a given point. For the studied area, it was possible to achieve high modeling accuracy and the correspondence of the obtained erosion map to the logic of the course of erosion-accumulative processes on the slopes.

Keywords:

digital soil mapping, GIS, ordinal regression, relief, soil erosion

The reported study was funded by RFBR according to the research project № 18-35-20018.

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Citation:

Buryak Z.A.,

Ukrainsky P.A.,

Lukin S.V.,

Terekhin E.A.,

(2021) Digital mapping of soil erosion using ordinal regression. Geodesy and cartography = Geodezia i Kartografia, 82(1), pp. 23-33. (In Russian). DOI: 10.22389/0016-7126-2021-967-1-23-33