Using ArcGIS software for stochastic simulation of soil properties

DOI: 10.35595/2414-9179-2020-1-26-516-532

View or download the article (Rus)

About the Authors

Nikolay V. Klebanovich

Byelorussian State University, Faculty of Geography and Geoinformatics,
Leningradskaja str., 14, 220004, Minsk, Belarus;
E-mail: N_Klebanovich@inbox.ru

Arkady L. Kindeev

Byelorussian State University, Faculty of Geography and Geoinformatics,
Leningradskaja str., 14, 220004, Minsk, Belarus;
E-mail: akindeev@tut.by

Abstract

Gaussian geostatistical modeling by the Geostatistical Analyst tools of ArcGIS ArcMap using, stochastic modeling and a comprehensive spatial assessment of the variability of a number of soil properties in a key area were performed.

According to the parameters of the third (asymmetry) and fourth (excess) orders, the normality of the distribution of acidity indicators, the content of mobile phosphorus compounds, moisture and specific surface of soils is proved. According to the sharpness of the distribution of data, the need for their conversion by indicators of phosphorus content and specific surface area is revealed. According to the quartile-quartile type charts, points are identified that are knocked out of the general sample for exclusion during further analysis. The analysis showed the presence of global trends in acidity and phosphorus content, described by polynomials of the 2nd and 1st orders, which indicates the presence of a determinate component in the general heterogeneity of properties, which was removed when selecting a mathematical model (semivariogram) and will be automatically taken into account when constructing the final cartograms.

A large proportion of the total heterogeneity falls on the random spatially correlated mesocomponent, which is described by variography methods. When using the developed models in precision farming technologies, it is possible to take into account up to 85 % of the heterogeneity in humidity and up to 100 % in the phosphorus content. The existence of significant differences between the use of classical geostatistics and Gauss modeling, which allows smoothing and eliminating statistical heterogeneity, is proved.

It is shown that standard deviation cartograms can be representative tools for developing monitoring networks and determining the need for an additional sampling point. Based on the parameters of the absolute values of the indicator, the location of the initial reference points, the lag value and standard deviation, a total monitoring network of 100 points was obtained.

Keywords

GIS, geostatistics, variation, stochastic modeling

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For citation: Klebanovich N.V., Kindeev A.L. Using ArcGIS software for stochastic simulation of soil properties. InterCarto. InterGIS. GI support of sustainable development of territories: Proceedings of the International conference. Moscow: Moscow University Press, 2020. V. 26. Part 1. P. 516–532. DOI: 10.35595/2414-9179-2020-1-26-516-532 (in Russian)