Abstract
The area of the Smolenskoe Poozerye National Park is characterized by a complicated and poorly studied soil cover and considerable anthropogenic impact. Soil maps, scale of 1 : 25 000, were compiled for a plot of 8.8 km2 in the southwest of the National Park, using the methods of traditional and digital soil mapping (DSM). The results obtained were compared. Both maps show that the study area is dominated by gray-humus soils (Umbric Cambisol (Loamic) and Arenosols (Ochric)). This is related to the agricultural use and regeneration of abandoned plowed soils. Smaller areas are occupied by Al-Fe-humus and texture-differentiated soils (Podzols (Arenic) and Retisols (Loamic), respectively). In addition, isolated areas of psammozems (Arenosols) have been found and identified on the map compiled by the traditional approach. The general accuracy of the map compiled by the DSM was 55%. The identified leading factors were the following: position in the relief, the parent rock, and vegetation. The distribution of soddy-podzolic soils associated with loamy parent rocks and of mucky-peat soils (Histosols) formed in local depressions and on the floodplain of Baklanovskoe Lake was predicted by the DSM methods with an accuracy of 87 and 60%, respectively. The location of soddy podburs (Entic Rustic Podzols (Ochric)) was predicted with an accuracy of only 29%. Large-scale differentiation of the soil cover was better reflected by the traditional method of the soil cover mapping as compared to the digital approach.
REFERENCES
Ya. Ya. Alekseev, “Essay on the vegetation of the Smolensk province,” in Agriculture of the Smolensk Province (1924), pp. 107–119 [in Russian].
GIS-Atlas “Resources of Russia” (Vseross. Nauchno-Issled. Geol. Inst. im. A. P. Karpinskogo, Moscow, 2001) [in Russian].
V. V. Dokuchaev, Cartography of Russian Soils (Izd. Minist. Gos. Imushchestv, 1879) [in Russian].
V. V. Dokuchaev, Collection of Works (Akad. Nauk SSSR, Moscow–Leningrad, 1950), Vol. 4, Part 1 [in Russian].
Map of Forest Inventory (Smolenskoye Poozerye National Park of Smolensk Oblast, Smolensk, 2015).
Classification and Diagnostic System of Russian Soils (Oikumena, Moscow, 2004) [in Russian].
D. N. Kozlov and N. I. Lozbenev, Methods and Algorithms for Digital Soil Cartography - Models of Soil-Landscape Relationships for Categories of the Nominal Scale. https://landscapeedu.ru/files/edu/R_DSM_ sid_v0.99.pdf
D. N. Kozlov and N. P. Sorokina, “Tradition and innovation in large-scale soil mapping,” in: Digital Soil Cartography: Theoretical and Experimental Studies (Pochv. Inst. im. V. V. Dokuchaeva, Moscow, 2012), pp. 35–57.
Comprehensive Study of the State of Nature of the Smolensk Poozerie for the Purposes of Protection and Rational Use at the Time of the Organization of a National Natural Park in This Region, Ed. by N. D. Kruglov (Smolensk. Gos. Pedagog. Inst., Smolensk, 1995) [in Russian].
N. V. Koroleva, E. V. Tikhonova, D. V. Ershov, A. N. Saltykov, E. A. Gavrilyuk, and A. V. Pugachevskii, “Twenty-five years of reforestation on nonforest lands in Smolenskoe Poozerye national park according to Landsat imagery assessment,” Contemporary Problems of Ecology 11 (7), 719–728 (2018).https://doi.org/10.1134/S1995425518070077
G. L. Kosenkov and E. Yu. Kolbovskii, “Periodization and reconstruction of the history of development of the territory of the national park “Smolenskoye Poozerye” for the purposes of typology of the cultural landscape,” Yarosl. Pedagog. Vestn. 3 (4), 232–238 (2012).
A. S. Kochergin, Abstract of Candidate’s Dissertation in Geography (Moscow, 2002).
All-Union Instruction on Soil Surveys and Compilation of Large-Scale Soil Maps of Land Use (Kolos, Moscow, 1973) [in Russian].
Field Guide on Correlation of Russian Soils (Pochv. Inst. im. V. V. Dokuchaeva, Moscow, 2008) [in Russian].
S. P. Chistyakov, “Random forests: a review,” Tr. Karel. Nauchn. Tsentra, No. 1, 117–136 (2013).
O. V. Shopina, M. I. Gerasimova, I. M. Bavshin, V. R. Khokhryakov, and I. N. Semenkov, “Soil inventory and mapping in the “Smolenskoye Poozerye” national park,” Lesovedenie, No. 5, 478–493 (2022). https://doi.org/10.31857/S0024114822040088
O. V. Shopina, A. P. Geraskina, A. I. Kuznetsova, E. V. Tikhonova, A. V. Titovets, I. M. Bavshin, V. R. Khokhryakov, and I. N. Semenkov, “Stages of restoration of the components of postagrogenic pine forest ecosystems at the National Park “Smolensk Lakeland”,” Eurasian Soil Sci. 55 (1), 16–28 (2023).https://doi.org/10.1134/S1064229322601639
Y. Bouslihim, A. Rochdi, R. Aboutayeb, N. el Amrani-Paaza, A. Miftah, and L. Hssaini, “Soil aggregate stability mapping using remote sensing and GIS-based machine learning technique,” Front. Earth Sci. No. 9, 863 (2021). https://doi.org/10.3389/FEART.2021.748859/BIBTEX
L. Breiman, “Random forests,” Mach. Learn. 45 (1), 5–32 (2001).
Environmental Soil-Landscape Modelling: Geographic Information Technologies and Pedometrics, Ed. by S. Grunwald (CRC Press, Boca Raton, 2006).
D. V. Ershov, E. A. Gavrilyuk, N. V. Koroleva, E. I. Belova, E. V. Tikhonova, O. V. Shopina, A. V. Titovets, and G. N. Tikhonov, “Natural afforestation on abandoned agricultural lands during post-Soviet period: a comparative Landsat data analysis of bordering regions in Russia and Belarus,” Remote Sens. 14 (2), 322 (2022). https://doi.org/10.3390/rs14020322
T. Hengl, A Practical Guide to Geostatistical Mapping (Luxembourg, 2009).
Y. Ma, B. Minasny, B. P. Malone, and A. B. McBratney, “Pedology and digital soil mapping,” Eur. J. Soil Sci., No. 70, 216–235 (2019).
A. B. McBratney, M. L. Mendonca Santos, and B. Minasny, “On digital soil mapping,” Geoderma, No. 117 (1–2), 3–52 (2003). https://doi.org/10.1016/S0016-7061(03)00223-4
D. G. Rossiter, Assessing the Thematic Accuracy of Area–Class Soil Maps (Soil Science Division, ITC. Enschede, Holland, Waiting publication, 2001).
A. M. J. C. Wadoux and A. B. McBratney, “Hypotheses, machine learning and soil mapping,” Geoderma, No. 383, 114725 (2021). https://doi.org/10.1016/j.geoderma.2020.114725
S. Wang, M. Zhou, K. Adhikari, Q. Zhuang, Z. Bian, Y. Wang, and X. Jin, “Anthropogenic controls over soil organic carbon distribution from the cultivated lands in Northeast China,” Catena 210, 105897 (2022). https://doi.org/10.1016/J.CATENA.2021.105897
G. Zhang, L. I. U. Feng, and X. Song, “Recent progress and future prospect of digital soil mapping: a review,” J. Integr. Agric. 16 (12), 2871–2885 (2017).
ACKNOWLEDGMENTS
The authors are grateful to the administration of the Smolenskoe Poozerye National Park for the opportunity to carry out the research, to I.M. Bavshin and M.A. Smirnova for discussing the text of the manuscript and valuable advices for its improvement, to M.I. Gerasimova for the assistance in soil diagnostics, as well as to participants in the terrain survey: D.S. Zhogov, V.E. Karpachev, D.A. Kasimova, G.I. Kolos, D.V. Kotov, A.D. Naumov, A.A. Peunova, A.A. Piskunova, E.A. Sergeeva, N.S. Sobolev, E.S. Starchikova, I.E. Tamarovskii, and D.A. Terekhova. Materials provided by the Geoportal Center for Collective Use (Lomonosov Moscow State University) were used for the selection of research objects.
Funding
This work was supported by the Russian Science Foundation, project no. 21-74-20171 (interpretation of the results), by the Lomonosov Moscow State University (Research Project no. 1.4 Anthropogenic Geochemical Transformation of Landscape Components), and by the Interdisciplinary Scientific and Educational School The Future of the Planet and Global Environmental Changes (terrain survey and soil diagnostics).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
The authors declare that they have no conflicts of interest.
Additional information
Translated by I. Bel’chenko
Supplementary Information
Rights and permissions
About this article
Cite this article
Kulikova, A.I., Chechenkov, P.D., Osipova, M.S. et al. Comparative Analysis of the Results of Traditional and Digital Large-Scale Soil Mapping on the Example of a Key Site in the Smolenskoe Poozerye National Park. Eurasian Soil Sc. 56, 271–277 (2023). https://doi.org/10.1134/S1064229322602281
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S1064229322602281