The research papers assessing the content of soil organic carbon with the help of Vis-NIR spectroscopy approaches are systematically analyzed and subject to meta-analysis. This meta-analysis included 134 studies published in 1986–2022 with a total sample of 709 values of quantitative metrics. The papers have been searched for in databases of scientific periodicals (RSCI, Science Direct, Scopus, and Google Scholar) by the key word combination “Vis-NIR spectroscopy AND soil organic carbon”. The meta-analysis using the nonparametric one-sided Kruskal–Wallis variance analysis in conjunction with nonparametric pairwise method shows the presence of a statistically significant difference between the median values of the accepted quantitative metrics of the predictive power of the models, namely, coefficient of determination ( R 2 cv/val ), root mean square error (RMSE), and the ratio of performance to deviation (RPD). The best performance of the preprocessing method for spectral curves is demonstrated and the estimates of soil organic carbon content obtained by laboratory and field spectroscopies are compared.

Atmospheric dust affects both human health and climate change. Therefore, the study of atmospheric dust is one of the important tasks of many scientific fields. The aim of our research was to indirectly assess the relation of atmospheric dust over arable lands of two test sites in Tver and Tula regions of Russia with soils. Dust was analyzed on aspirator filters after pumping specified volumes of air at the level of 20–30 cm above the arable surface. Its spectral reflectance was used as a criterion of soil origin of dust, which was compared with the reflectance of the size fraction (50–200 nm) of soils isolated by dry sieving of a sample of arable soil horizon. The spectral reflectance of dust was calculated based on approaches of linear separation of spectral mixture, taking into account the projective coverage of dust particles on filters, which was determined by analyzing microscope photographs of the filters in GIS. As a result, it was found that the recovered dust spectra on the filters correlate well with the spectra of the same size soil fraction separated by dry sieving, which indirectly confirms the predominance of specifically soil dust on the filters. Spearman correlation coefficient is within the range of 0.84–0.90, Kendall's Tau correlation coefficient varies within 0.70–0.79 (at significance level p < 0.05). Under the conditions of insignificant atmospheric dust load and when collecting a sufficient amount of dust for direct analysis is time and labour consuming, the approach used may serve as an alternative for indirect confirmation of the soil origin of dust in the near ground layer of the atmosphere. In the future, this approach can be used as a basis for monitoring of arable soils deflation.

The problem of pedo- and biodiversity of mire ecosystems under the long-term multiple anthropogenic impact was studied in one of the most intensively technogenically transformed areas of Shaturskaya Meshchera, adjacent to power station Shaturskaya in the north and stretching along the route Kerva – Dolgusha – Severnaya Griva. For more than a hundred years, mires in the Shatura area have been under the influence of drainage, peat extraction, fires, attempts to create agricultural land, secondary watering and pollution, resulting from the power station, transport, and settlements wastewaters. Currently, the bio- and soil diversity of secondary ecosystems has increased significantly compared to undisturbed mires. Instead of bog, in some cases there appeared secondary meadow, grass-shrub communities, small-leaved forests, and dry sparse areas. The remaining bogs experience stable eutrophication, which leads to the formation of mesotrophic and eutrophic phytocenoses and, accordingly, peat mesotrophic and oligotrophic secondary eutrophic soils. In addition, the proportion of eutrophic mires is slightly increased by the peat formation in shallow lakes, which at the initial stage of peat extraction were used for storing wood waste. The phenomenon of secondary oligotrophization of the disturbed bogs of Meshchera, noted in the literature, is not observed in the area under consideration due to a significant anthropogenic load. To preserve the local flora of oligotrophic bogs, marginal areas of flooded quarries and cofferdams with undeveloped peat deposits are of great importance. The increase in pedodiversity was facilitated by the agricultural development of drained peatlands for the cultivation of perennial grasses, which resulted in the formation of torfozems and agrotorfyano-gleyzems.

The study focuses on the possibilities of using photographs obtained using crowdsourcing technologies for the operational inventory of arable soils. The object of the study is the spectral reflectance of the open surface of arable soils of the test plots, measured using a HandHeld-2 spectroradiometer operating in the range of 325–1 075 nm, and their image in photographs taken with conventional cameras. Test sites are located in the Tula, Moscow and Tver regions. The soils of the test plots are sod-podzolic, gray forest, and leached chernozems. Based on the analysis of photographs of the surface and information obtained using a spectroradiometer, a set of spectral parameters in the RGB, YMC and HSI color systems, as well as their ratios (45 parameters), was calculated. These parameters were used to separate the analyzed soil types using classification trees. The accuracy of classification based on the results of validation varies from 63–100%. At the same time, the parameters of the HSI and YMC color systems turned out to be more informative than the parameters of the RGB color system. The established classification rules can later be used to determine the classification position of soils from images collected using crowdsourcing technologies.

On the example of the test field located in the Tula region (Russia), the possibility of using remote sensing data for mapping the fertility of arable soils is considered. Analysis of ground-based spectrometry data showed that the correlation between the spectral reflectance of the surface of arable soils and fertility indicators increases with an increase in wavelength. The maximum value of the correlation coefficient for mobile phosphorus was 0.84, for humus content – -0.83, for mobile potassium – -0.7, for pH – -0.86, for exchangeable calcium – -0.88, for exchangeable magnesium – 0.67. When analysing the Sentinel-2 satellite data, the correlation coefficients turned out to be higher than in the case of ground-based spectrometry data. Band 5 of Sentinel-2 was found to be the most informative for the detection of most of the analysed parameters of soil fertility. Depending on the property, the R2cv of the models varied from 0.47 to 0.93. The best models were obtained for pH, humus, mobile phosphorus, and exchangeable calcium. Based on regression models, maps of fertility indicators of arable soils for the test field were produced. The obtained models can be used to organize operational monitoring of the main parameters of soil fertility in the field.

During the model experiment we exposed samples from surface layer of leached chernozem, grey forest and soddy-podzolic soils to study the impact of raindrop action on their surface. According to our results, surface of leached chernozem and grey forest soil transformed similarly forming the crust separated by the cracks. The crust consisted of light (washed silt fraction) and dark (compacted fine material) areas. As for the soddy-podzilic soil, we observed surface accumulation of sand and washed mineral grains. Surface image classification showed that cracks generally tended to increase in area during the surface drying. However, leached chernozem cracked quicker and heavier compared to grey forest soil. In addition, the proportion between light and dark areas of the crust for these two types of soil changed differently as well. In conditions of different transformation cycles divided by heavy rainfalls, the changes of cracks position and the increase of light crust area was observed, while dark area moved to the cracks. Such spatial rearrangement resulted in the increase of average reflectance in RGB channels. The inequality between reflectance in different channels increased as well. During the experiment significant surface lightening occurred. It mainly affected the light area of crust and led to significant rise in reflectance in red channel.