Methods of verification of soils prediction maps: a case study from Chernivtsi region, Ukraine

Abstract

Knowing the spatial distribution of individual soil taxonomic units is a key factor in managing efficient land use not only for agriculture but also for forestry. The use of a comprehensive soil surveys held in past decades and based on fieldwork created the basis for the initial spatial representation of the soil fund structure. However, the spatial distribution of the soil cover was the result of fieldwork and the experience of the person who drew this map. Often this led to some errors in determining the types of soils and their boundaries. To date, there is a growing need for precise methods of land taxation, based on correct information on soil cover. In countries with a large area, such as Ukraine, field surveys still do not cover the whole territory, often the density of the allocation of soil pits was too low, which in some cases led to an incorrect demarcation of soil boundaries. Since such a problem is very urgent for Ukraine, the search and identification of probable problem soil maps by constructing their predicted versions, their comprehensive analysis and cross-validation is an important task. The conducted investigations revealed that morphometric parameters of the relief and their derivatives obtaining from the analyses of DEM are a reliable basis for the predictive modelling of the spatial distribution of soil cover with sufficiently high accuracy, and the methodology based on 11 types of prognostic algorithms would have a significant prospect in solving scientific and production problems. Very important in this process is the selection of predictors derived from the DEM, as well as the structure and distribution of the training dataset, based on which the model will be built later. Afterwards the results need to be validated, in our case, on the basis of the cross-validation of the models and by comparing the results with field survey. The article presents the results of 11 simulations, evaluates the quality of predictive algorithms and the models obtained. Therefore, several possible ways to check the cartographic and simulation results of the spatial distribution of soil taxonomic units were described, as well as their comparison with those actually existing in nature. The most reliable method of the 11 presented is a direct study of the soil in the field and comparing them with the soil map. It is recommended to use it in case of suspicion of poorly executed maps, although financially it is very expensive. More preferred is a set of modelling methods that is based on the data already collected. With reliable sources, they provide an opportunity to predict the soil in places where the survey was not conducted at all. Verification of the quality of the tested models was carried out on a fragment of the Ukrainian region within the boundaries of the Chernivtsi region, confined to the Prut-Dniester and Prut-Siret interfluves.

Methods of modeling and mapping of the soil bulk density: a case study from Chernivtsi region, Ukraine

“…This soil survey was almost completed. About 15-18 million hectares of 60 million hectares have never been assessed by systematic soil surveys in scale of 1:10,000; this includes not only the Carpathian and Crimean Mountains, but also forested, built-up, and some cropland areas (Achasov et al 2015, Cherlinka 2017a, 2017b, 2017c, Cherlinka et al 2019, 2020, and therefore there is no reliable soil map for these areas. Since 1991, surveys have been only fragmentary (Kanash 2013).…”

“…However, for soils used in agriculture, especially of the top layer, genetic features are significantly reduced by constant anthropogenic influence. The indicators of the soil texture, content of organic matter, exchangeable cations, that is, some of the indicators of the soil absorbing complex (Cherlinka 2019, Nazarenko et al 1998, 2000 come first. But this kind of research requires a sufficiently voluminous sample of data to reliably establish relationships of density with other soil indicators and to build appropriate cartographic models.…”

Untitled

“…Soils need a comprehensive assessment of their condition for forecasting and timely prevention of degradation processes, protection, and rational use of land ( Balyuk et al, 2017;Graham, 2021;Hunchak, 2022;). Cherlinka V. et al (2019) indicate that in the current conditions, there is a growing need for updated land taxation methods based on accurate information about the ground cover. Ukraine has a large area of land, so field examinations often do not cover the entire territory, which can lead to errors in determining soil varieties and their properties.…”