Using Geostatistics, DEM and Remote Sensing to Clarify Soil Cover Maps of Ukraine

Cherlinka, Vasyl

doi:10.1007/978-3-319-45417-7_7

Cited by 6 publications

(7 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Одержані ще в 1957-1961 рр. результати застаріли, в них чимало недоречностей, а корекція цих даних не проводилася понад 25 років [5,6]. Ситуація в інших державах Європи різна, але аналогічні проблеми зустрічаються нерідко.…”

Section: ключові слова: морфометричні параметри цмр ґрунтова картаunclassified

“…Основним джерелом предикторів у такій симуляції є цифрова модель рельєфу (DEM), аналіз якої дозволяє виділити цілий ряд геоморфологічних та пов'язаних з ними параметрів. Оскільки модельовані змінні (різновиди ґрунтів) відносяться не до числового, а категоріального типу даних, а отримані з ЦМР показники, як правило, числові, то використання лише просунутих математичних методів дозволяє встановити неочевидні на перший погляд залежності між усіма цими параметрами [6,11,[17][18][19][20].…”

Section: ключові слова: морфометричні параметри цмр ґрунтова картаunclassified

“…Адміністративно цей ареал відноситься до території міста Чернівці (рис. 1), а при його виборі було вирішено деякі суто українські проблеми, детально описані в ряді праць [6,25,26]. Головними з них були проблеми з доступом до топографічних та ґрунтових даних та їх актуальністю, системою координат тощо.…”

Section: ключові слова: морфометричні параметри цмр ґрунтова картаunclassified

See 2 more Smart Citations

Verification methods for predicative soil maps

Cherlinka¹,

Dmytruk²

2018

Naukovij vìsnik Nacìonalʹnogo unìversitetu bìoresursìv ì prirod

View full text Add to dashboard Cite

Section: ключові слова: морфометричні параметри цмр ґрунтова картаunclassified

See 1 more Smart Citation

Verification methods for predicative soil maps

Cherlinka¹,

Dmytruk²

2018

Naukovij vìsnik Nacìonalʹnogo unìversitetu bìoresursìv ì prirod

View full text Add to dashboard Cite

“…The areas of settlements, forests, mountainous regions in most cases remained off the attention of researchers. The results obtained in 1957-1961 are outdated, there are many inappropriate results, and the correction of these data was not carried out over 25 years (Cherlinka 2017a). The situation in other European countries is different, but similar problems often occur.…”

Section: Introductionmentioning

confidence: 99%

“…The challenge in using DEMs is in defining relationship between quantitative measures of terrain topography and categorical variables defining as the soil types. Therefore, advanced mathematical methods are needed to establish the relationship between all these parameters which existence can be non-obvious at the first glance (Giasson et al 2008, Kempen et al 2009, Debella-Gilo and Etzelmüller 2009, Hengl 2009, Cherlinka 2017a, Malone et al 2016.…”

Section: Introductionmentioning

confidence: 99%

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

Cherlinka¹,

Dmytruk²,

Barabas³

2019

Geographia Cassoviensis

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Cartographic technique for determining areas of soil contamination by heavy metals

Dmytruk

Cherlinka

2022

International Journal of Environmental Studies

View full text Add to dashboard Cite

Using Geostatistics, DEM and Remote Sensing to Clarify Soil Cover Maps of Ukraine

Cited by 6 publications

References 11 publications

Verification methods for predicative soil maps

Verification methods for predicative soil maps

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

Cartographic technique for determining areas of soil contamination by heavy metals

Contact Info

Product

Resources

About