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Relationships between soil pH and base saturation – conclusions for Polish and international soil classifications

habitats in the Stołowe Mountains. Sylwan 158(9): 684–694. Gruba P., Mulder J., 2015. Tree species affect cation exchange capacity (CEC) and cation binding properties of organic matter in acid forest soils. Science of the Total Environment 511: 655–662. IUSS Working Group WRB, 2015. World Reference Base for Soil Resources 2014, Update 2015. International soil classification system for naming soil and creating legends for soil maps. Food and Agriculture Organization of the United \ Nations, Rome: 186 pp. Jaremko D., Kalembasa D., 2014. A comparison of

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Selected issues relating to classification of mountain organic soils in Poland according to the Polish Soil Classification (2011)

., Gajewski P., Kaczmarek Z., 2016c. The effect of long-term forestry drainage on the current state of peatland soils: A case study from the Central Sudetes, SW Poland. Mires and Peat 18(21): 1–11. IUSS Working Group WRB, 2006. World Reference Base for Soil Resources, A framework for international classification, correlation and communication. World Soil Resources Report No. 103. FAO, Rome: 143 pp. IUSS Working Group WRB, 2015. World Reference Base for Soil Resources 2014, update 2015 International soil classification system for naming soils and creating legends

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Clay-illuvial soils in the Polish and international soil classifications

Poland). Soil Science Annual 65: 18–24. Glinka K.D., 1915. Pochvovedenie. Wydawnictwo A.F. Dewrena, Piotrogród: 708 pp. IUSS Working Group WRB, 2006. World Reference Base for Soil Resources. World Soil Resources Reports 103. FAO, Rome: 162 pp. IUSS Working Group WRB, 2014. World Reference Base for Soil Resources – an international system for soil classification. World Soil Resources Reports 106. FAO, Rome: 181 pp. Jaworska H., Dąbkowska-Naskręt H., 1999. Gleby płowe wytworzone z utworów pyłowych Pojezierza Chełmińsko-Dobrzyńskiego i Wysoczyzny

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The Soil Classification course in Russian universities: an important ingredient of education

References AUBERT G., DUCHAUFOUR Ph., 1967, Classification des sols. Commission de Pédologie et Cartographie des sols. BEZUGLOVA O.S, 2009, Soil classification. Rostov-on-Don Southern Federal University (in Russian). CLASSIFICATION AND DIAGNOSTICS OF SOILS OF THE USSR. 1977, Moscow, Kolos Publ. (in Russian). English translation of 1987. DOBROVOLSKIY G.V., TROFIMOV S. Ya., 1996, Systematics and classification of soils (History and present-day status) (in Russian). FAO and ITPS, 2015, Status of the World’s Soil Resources (SWSR) – Main

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Polish Soil Classification, 6th edition – principles, classification scheme and correlations

References Arnold R.W., 2002. Soil classification principles. [In:] Soil Classification 2001 (Micheli E., Nachtergaele F.O., Jones R.J.A., Montanarella L., Editors). ESBR Report No 7, EUR 20398 EN, Luxembourg: 3–8. Bednarek R., 1991. Wiek, geneza i stanowisko systematyczne gleb rdzawych w świetle badań paleopedologicznych w okolicach Osia (Bory Tucholskie). Wyd. UMK, Toruń: 422 ss. Brevik E.C., Calzolari C., Miller B.A., Pereira P., Kabala C., Baumgarten A., Jordán A., 2016. Soil mapping, classification, and pedologic modeling: History and

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An attempt of integrating the systematic of urban soils into the new Russian soil classification system

References Achkasov A.I., Basharkevich I.L., Varava K.V., Samayev S.B., 2006. Snow cover pollution by icing-reducing reagents (in Russian). Prospect. & control geol. environ. 9.10: 132.137. Aparin B.F., Sukhacheva E.YU., 2012. Principles of urban soils classification (with the example of S. Petersburg). (in Russian) [In:] Proceedings of the All-Russian Conference .Geochemistry of Landscapes and Geography of Soils., dedicated to the 100th birthday of M.A. Glazovskaya. Moscow Lomonosov Univ., Moscow 4.6.04.2012 (Kasimov

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Experience of the teaching of soil classification systems to students at different stages of education (Faculty of Soil Science, LMSU, Russia)

, problems and proposals. Eurasian Soil Science, 5: 599–609, doi: 10.1134/S1064229313050037. GUIDELINES FOR SOIL DESCRIPTION (5th Edition), 2006, Food and Agriculture Organization of the United Nations. Rome. Russian version: Rukovodstvo po opisaniyu pochv. Rim: Prodovolstvennaya i selskohoziaystvennaya organizatsyia obedinennyh natsyi (FAO), 2012. IUSS WORKING GROUP WRB, 2015, World Reference Base for Soil Resources 2014, update 2015. International soil classification system for naming soils and creating legends for soil maps, World Soil Resources Reports No

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Correction of inaccuracies to article of Stanisław Brożek, „Does Polish soil classification, V edition, refer to all soils in our country“ published in the Soil Science Annual, vol. 63 no. 3/2012: 49–56

Warszawa. Systematyka gleb Polski, 2011, wyd. 5. Roczniki Gleboznawcze - Soil Science Annual, L 62, nr 3 (Marcinek J., Komisarek J. red. nauk.) (Marcinek J., Komisarek J., Bednarek R., Mocek A. Skiba S., Wiatrowska K.). Wieś Jutra Warszawa. Soil Survey Staff, Soil Conservation Service, 1960. Soil Classi- fication, a comprehensive system - 7 th approximation”, USDA Soil Survey Stall', 1999. SoilTaxonomy,2“ ,a edition. A Basic Sys- tem of Soil Classification for Making and Interpreting Soil Surveys

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Proposal of the correlation between cartographic units on the agricultural soil map and types and subtypes of Polish Soil Classification (6th edition, 2019)

., Charzyński P., Chodorowski J., Drewnik M., Glina B., Greinert A., Hulisz P., Jankowski M., Jonczak J., Łabaz B., Łachacz A., Marzec M., Mendyk Ł., Musiał P., Musielok Ł., Smreczak B., Sowiński P., Świtoniak M., Uzarowicz Ł., Waroszewski J., 2019. Polish Soil Classification, 6th edition – principles, classification scheme and correlations. Soil Science Annual 70(2): 71–97. Kabała C., Musztyfaga E., 2015. Gleby płowe w systematyce gleb Polski i w klasyfikacjach międzynarodowych. Soil Science Annual 66(4): 204–213. Kabała C., Płonka T., Przekora A. 2015. Vertic

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Adaptive modelling of spatial diversification of soil classification units

Abstract

The article presents the results of attempts to use adaptive algorithms for classification tasks different soils units. The area of study was the Upper Silesian Industrial Region, which physiographic and soils parameters in the form of digitized was used in the calculation. The study used algorithms, self-organizing map (SOM) of Kohonen, and classifiers: deep neural network, and two types of decision trees: Distributed Random Forest and Gradient Boosting Machine. Especially distributed algorithm Random Forest (algorithm DRF) showed a very high degree of generalization capabilities in modeling complex diversity of soil. The obtained results indicate, that the digitization of topographic and thematic maps give you a fairly good basis for creating useful models of soil classification. However, the results also showed that it cannot be concluded that the best algorithm presented in this research can be regarded as a general principle of system design inference.

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