Soil-Archaeological Study of the Votikeevo Medieval Archeological Site in the Northern Forest-Steppe Zone of the Southern Cis-Ural Region

Suleymanov, Ruslan; Ovsyannikov, V. V.; Kolonskih, A. G.; Abakumov, Evgeny; Kungurtsev, A. Ya.; Suleymanov, Azamat

doi:10.1134/s1064229320030084

Cited by 7 publications

(2 citation statements)

References 36 publications

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“…The original soil is preserved mainly in the sanitary protection zone around the enterprises of the petrochemical complex and in the central and southern parts-in city parks and green areas. These soils are classified as Umbric Luvisols and Albeluvisols, but they are also characterized by anthropogenic transformation [32,33].…”

Section: Study Areamentioning

confidence: 99%

Mercury Prediction in Urban Soils by Remote Sensing and Relief Data Using Machine Learning Techniques

Suleymanov

Kulagin

et al. 2023

Remote Sensing

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This article aims to explore the use of machine learning (ML) methods for mapping the distribution of mercury (Hg) content in topsoil, using the city of Ufa (Russia) and adjacent areas as an example. For this purpose, a soil dataset of 250 points sampled from a 0–20 cm depth on different land uses, including residential, industrial and undisturbed (forests and parks), was used. Random Forest (RF), Extreme Gradient Boosting (XGboost), Cubist and k-Nearest Neighbor (kNN) ML techniques were employed to model and map the Hg concentrations. We used remote sensing data (RSD) and topographic attributes as explanatory variables. ML models were calibrated and validated using the leave-one-out cross-validation approach. The Hg content varied from 0.005 to 0.58 mg/kg and was characterized by very high variability. According to the MAE and RMSE metrics, the RF method resulted in the most accurate spatial prediction for the Hg content (0.029 and 0.065 mg/kg, respectively), while the XGBoost approach showed the lowest prediction efficiency (0.032 and 0.073 mg/kg, respectively). The results showed that the slope map, spectral index MSI and Sentinel-2A band B11 were the key variables in explaining the variability of Hg content. We found that higher uncertainty values of soil Hg were found in croplands, urban residential and industrial areas, which supports the view that spatial modelling of HM in urban landscapes is challenging. The present study provides insights into the potential of digital soil mapping techniques in combination with RSD and terrain variables for identifying areas at risk of Hg contamination in urban areas, which can inform land-use planning and management strategies to protect human health and the environment.

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Section: Study Areamentioning

confidence: 99%

Mercury Prediction in Urban Soils by Remote Sensing and Relief Data Using Machine Learning Techniques

Suleymanov

Kulagin

et al. 2023

Remote Sensing

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“…Archaeologists investigated hundreds of region monuments of different Holocene chronosequence [6]. But only part of them was examined by the methods of natural sciences [7][8][9][10][11][12][13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Complex Study of Settlements Dating from Paleolithic to Medieval Ages of Southern Urals on Border of Europe and Asia

Prikhodko,

Savelev,

Kotov

et al. 2024

Preprint

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Soil, geochemical, microbiological and archaeological studies were conducted at eight settlements dating from the Paleolithic to Late Medieval and New Times near the Southern Trans-Urals mountains, Russia. The forest-steppe landscapes, rivers and abundance of mineral resources have attracted people to region since ancient times. Properties of cultural layer (CLs): close to neutral pH, well structured, absence of salinity, enrichment with exchangeable calcium and anthropogenic phosphorus (0.2–0.4%). The majority of CLs start from 3–25 cm and last up to 40–60 cm and contain 6–10% organic carbon (Corg), in a layer of 0–20 cm because modern processes are developing here, at Ishkulovo site (around 14th century) Corg decreases to 1.3%, because CL is below 80 cm and in the absence of fresh organic material it is mineralized. The content of microbial biomass of the 0–10 cm layer is 520–680 μg С/g of soil, microbes cause the emission of 0.2–1.0 μg C–CO2/g soil per h. The proximity of the studied sites to deposits of copper, chromium, zinc, manganese and Magnitogorsk Metallurgical and Uchaly processing plants creates geochemical anomalies of soils. Pollutants are also released into the CLs from bronze products, ore, ceramic fragments and raw materials from their manufacture. It leads to the concentration of pollutants of the 1st (arsenic, lead, zinc) and 2nd (cobalt, copper, nickel, chromium) hazard classes in the studied CLs, often in quantities higher than the clarke and less often – more than the allowable content for human health.

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Empirical relationship for the estimate of pyroclastic soil thickness using slope steepness

Forte

Massaro

Falco

et al. 2023

CATENA

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Soil-Archaeological Study of the Votikeevo Medieval Archeological Site in the Northern Forest-Steppe Zone of the Southern Cis-Ural Region

Cited by 7 publications

References 36 publications

Mercury Prediction in Urban Soils by Remote Sensing and Relief Data Using Machine Learning Techniques

Mercury Prediction in Urban Soils by Remote Sensing and Relief Data Using Machine Learning Techniques

Complex Study of Settlements Dating from Paleolithic to Medieval Ages of Southern Urals on Border of Europe and Asia

Empirical relationship for the estimate of pyroclastic soil thickness using slope steepness

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