Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, Slovakia
The paper introduces a method of digital mapping of spatial distribution of soil typological units. It implements fuzzy k-means to classify the soil profile data (study area from the Považský Inovec Mountains, Slovakia) and regression-kriging with the selected digital terrain and remote sensing data...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Czech Academy of Agricultural Sciences
2007-12-01
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| Series: | Soil and Water Research |
| Subjects: | |
| Online Access: | https://swr.agriculturejournals.cz/artkey/swr-200704-0002_mapping-soils-using-the-fuzzy-approach-and-regression-kriging-case-study-from-the-povazsky-inovec-mountains-sl.php |
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| author | Juraj Balkovič Gabriela Čemanová Jozef Kollár Miroslav Kromka Katarína Harnová |
| author_facet | Juraj Balkovič Gabriela Čemanová Jozef Kollár Miroslav Kromka Katarína Harnová |
| author_sort | Juraj Balkovič |
| collection | DOAJ |
| description | The paper introduces a method of digital mapping of spatial distribution of soil typological units. It implements fuzzy k-means to classify the soil profile data (study area from the Považský Inovec Mountains, Slovakia) and regression-kriging with the selected digital terrain and remote sensing data to draw membership maps of soil typological units. Totally three soil typological units were identified: Haplic Cambisols (Skeletic, Dystric), Albic Stagnic Luvisols, and Haplic Stagnosols (Albic, Dystric). We analysed the membership values to these units with respect to terrain and remote sensing data. The membership values appeared as spatially smoothly dependant on the terrain gradients (linearly or exponentially) whereas the residua showed spatial autocorrelation. Based on regression and kriging analyses, the regression-kriging model was successfully deployed to draw raster membership maps. These maps yield coefficients of determination between R2 = 56% (Albic Stagnic Luvisols) to R2= 79% (Haplic Cambisols (Skeletic, Dystric)) when evaluated by cross validation. The grid-based continuous soil map represents an alternative to the classical polygon soil maps and can offer a wide range of interpretations for landscape studies. |
| first_indexed | 2024-04-10T08:04:58Z |
| format | Article |
| id | doaj.art-2f5d5689217e4ff3a104f497ead4eb27 |
| institution | Directory Open Access Journal |
| issn | 1801-5395 1805-9384 |
| language | English |
| last_indexed | 2024-04-10T08:04:58Z |
| publishDate | 2007-12-01 |
| publisher | Czech Academy of Agricultural Sciences |
| record_format | Article |
| series | Soil and Water Research |
| spelling | doaj.art-2f5d5689217e4ff3a104f497ead4eb272023-02-23T03:48:05ZengCzech Academy of Agricultural SciencesSoil and Water Research1801-53951805-93842007-12-012412313410.17221/2112-SWRswr-200704-0002Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, SlovakiaJuraj Balkovič0Gabriela Čemanová1Jozef Kollár2Miroslav Kromka3Katarína Harnová4Department of Soil Science, Faculty of Natural Science, Comenius University in Bratislava, Bratislava, Slovak RepublicDepartment of Soil Science, Faculty of Natural Science, Comenius University in Bratislava, Bratislava, Slovak RepublicInstitute of Landscape Ecology, Slovak Academy of Sciences, Bratislava, Slovak RepublicDepartment of Soil Science, Faculty of Natural Science, Comenius University in Bratislava, Bratislava, Slovak RepublicDepartment of Soil Science, Faculty of Natural Science, Comenius University in Bratislava, Bratislava, Slovak RepublicThe paper introduces a method of digital mapping of spatial distribution of soil typological units. It implements fuzzy k-means to classify the soil profile data (study area from the Považský Inovec Mountains, Slovakia) and regression-kriging with the selected digital terrain and remote sensing data to draw membership maps of soil typological units. Totally three soil typological units were identified: Haplic Cambisols (Skeletic, Dystric), Albic Stagnic Luvisols, and Haplic Stagnosols (Albic, Dystric). We analysed the membership values to these units with respect to terrain and remote sensing data. The membership values appeared as spatially smoothly dependant on the terrain gradients (linearly or exponentially) whereas the residua showed spatial autocorrelation. Based on regression and kriging analyses, the regression-kriging model was successfully deployed to draw raster membership maps. These maps yield coefficients of determination between R2 = 56% (Albic Stagnic Luvisols) to R2= 79% (Haplic Cambisols (Skeletic, Dystric)) when evaluated by cross validation. The grid-based continuous soil map represents an alternative to the classical polygon soil maps and can offer a wide range of interpretations for landscape studies.https://swr.agriculturejournals.cz/artkey/swr-200704-0002_mapping-soils-using-the-fuzzy-approach-and-regression-kriging-case-study-from-the-povazsky-inovec-mountains-sl.phpfuzzy k-meansregression-krigingdigital landscape datagrid interpretationspatial distributionsoil classification |
| spellingShingle | Juraj Balkovič Gabriela Čemanová Jozef Kollár Miroslav Kromka Katarína Harnová Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, Slovakia Soil and Water Research fuzzy k-means regression-kriging digital landscape data grid interpretation spatial distribution soil classification |
| title | Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, Slovakia |
| title_full | Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, Slovakia |
| title_fullStr | Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, Slovakia |
| title_full_unstemmed | Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, Slovakia |
| title_short | Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, Slovakia |
| title_sort | mapping soils using the fuzzy approach and regression kriging case study from the povazsky inovec mountains slovakia |
| topic | fuzzy k-means regression-kriging digital landscape data grid interpretation spatial distribution soil classification |
| url | https://swr.agriculturejournals.cz/artkey/swr-200704-0002_mapping-soils-using-the-fuzzy-approach-and-regression-kriging-case-study-from-the-povazsky-inovec-mountains-sl.php |
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