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One of the latest updates on the soil cover of the mountain regions of Uzbekistan is contained in the “Atlas of the Soil Cover of the Republic of Uzbekistan”, published in 2010. It contains soil maps of the regions of the country at the scales of 1 : 350 000 to 1 : 2 500 000 and provides brief charateristics of the soils. The Atlas was compiled on the basis of traditional methods of soil mapping. As a result, its contour part is typical of maps of the mentioned scales and rather schematic. The aim of the research was to update the contour part of the soil maps of mountain territories of Uzbekistan, contained in this Atlas, by means of the analysis of Landsat 8 satellite data. The contour part of the map was updated for the territory with absolute terrain altitude exceeding 900 m. Updating of the map contours was based on the methods of interactive indirect interpretation, when the boundaries of the contours were specified in the GIS using as a substrate the color composites of satellite data obtained at the optimal time of survey. Map correction, mountainous area delineation, and area counting were performed using the GIS ILWIS v.3.3 software package. About 18% of all soil mapping units were divided into several subunits. For 37% of the soil mapping units the boundaries changed significantly (the area of the units changed – by more than 30% with an average change in the length of the boundary of 15–38%). For 45% of soil mapping units the boundaries had changed less significantly (the area of the units had changed by no more than 30% and the boundary length had changed by no more than 20%). No cases of merging of soil mapping units were recorded. As a result, the contour part of the corrected map, compared to the original one, became much more detailed with more indented boundaries. The updated map shows the natural soil cover, excluding the anthropogenically changed soils. But the approach used for updating the original soil map may be also applied to expand the information on anthropogenical load as well. Moreover, this information can be obtained by interpretation of the same satellite data that were used for the map updating.

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.

Satellite data have been used for a long time to assess various properties of arable soils. At the same time, there are certain difficulties associated with the fact that a number of agronomically important soil properties do not directly affect spectral reflectance of their surface, which complicates the remote assessment of such properties. In addition, to obtain reproducible models, it is necessary to take into account the state of the open soil surface during the survey. The aim of the study was to demonstrate a method for detecting agronomically important properties of arable soils based on Landsat 8-9 OLI satellite data and including information about the state of their open surface using the example of a test field in the Serebryano-Prudsky district of the Moscow region. Depending on the soil property, R2cv of the models developed based on Landsat 8-9 OLI satellite data varied from 0.57 to 0.91. The best models with R2cv>0.8 were obtained for organic matter and properties higly correlated with it such as the content of exchangeable calcium and magnesium cations, the content of total nitrogen, pH of water and salt extracts. The involvement of information on the state of the open surface of arable soils for most properties made it possible to obtain models of higher quality and predictive ability, regardless of the survey period. Based on the models obtained, maps of the spatial variation of agronomically important properties of arable soils were constructed as part of the demonstration of the method. The resulting models can be used for remote monitoring of the analyzed properties of arable soils of the test field. At the same time, for such properties as the content of exchangeable potassium and phosphorus compounds, it is necessary to search for the approaches that will take into account their high variability, as well as to perform a prior assessment of the informativity of the survey periods in which the open soil surface is not transformed.

At the end of the 20th century, a geoinformation database on soil degradation in Russia, relied on the soil map of Russia at a scale of 1 : 5 million, was developed under the leadership of V.S. Stolbovoy. As part of the development of this problem and in the course of obtaining new information on soil degradation, an attempt was made to refine and supplement this database, that relies on the soil map of the Russian Federation 1 : 2.5 million scale. Soil degradation resulted from the impact of various types of pollution was taken into account, including industrial emissions, leakage of oil products, excessive application of pesticides, the impact of vehicles and radiation pollution. Each soil polygon of the soil map exposed to the pollution was characterized by the degree and area of pollution in accordance with the developed scales. The results of the analysis were used to construct cartograms illustrating the spatial distribution of chemical and radiation degradation of the country soils. According to the data obtained, in the zone of pollution derived from industrial enterprises and oil pollution, 20% of the soil-geographic polygons of the map are characterized by a strong degree of pollution, and 30% and 50% – by weak and medium, respectively. Agricultural pollution due to excessive use of plant protection products in Russia does not exceed 10% of the area of polygons and is characterized by a low degree. About 10% of the soil polygons of the basic soil map are heavily contaminated with radioactive contamination, while 40% and 50% of the polygons are moderately and weakly contaminated, respectively. Pollution from vehicles is weak and generally has low level. At the same time, megacities and highways with heavy traffic are distinguished by relatively high level of pollution.

One of the most important applications of soil knowledge is in agricultural processes and crop production. Crop and forage yields strongly depend on soil conditions. Therefore, accurate soil information is an important component of informational support for agricultural production. A soil map is used as the basis for obtaining the soil data of a land plot. But the information on the soil map in many cases does not reflect the spatial variation of all agronomically important properties of soils, which leads to oversimplified and inaccurate analysis of soil information when making management decisions. A new methodology of applied soil mapping for agricultural purposes, based on a detailed analysis of the state of crops in a crop rotation with the use of multi-year satellite data archives, is proposed. The maps of soil inhomogeneity of individual fields, obtained on the basis of the proposed approaches, differ significantly from the traditionally developed soil maps and more accurately reflect the spatial heterogeneity of soil properties, predetermining their actual fertility.

By the example of arable horizon samples taken from three soil types (sod-podzolic, gray forest, and leached chernozem) the peculiarities of electromagnetic waves reflection from their different particle size fractions were studied. The extraction of fractions by dry sieving was carried out using Retsch AS 200 BASIC equipment. As a result, 14 fractions ranging in size from less than 20 microns to more than 5,000 microns were isolated. Spectral reflectance was determined for each fraction and for the soil sample before sieving in the electromagnetic wave range from 350 to 2,500 nm using a SR-6500 field spectroradiometer (Spectral Evolution, USA). Analysis of similarities and differences in the obtained spectral reflectance curves of individual fractions was carried out using their visual analysis, the method of similarity dendrogram construction, as well as regression analysis between light reflectance and fraction particle size. It was confirmed that at a more detailed level of analysis compared to the one carried out by other researchers earlier, the general patterns of light reflectance of the samples do not change. A higher reflection of waves by thinner fractions and a lower reflection by more coarse fractions are observed. At the same time, spectral reflection curves for individual fractions are out of the general pattern, the level of intensity of local extremes of the curves’ changes. This confirms the difference of the material composition, which forms the color of soils, of these fractions from others. The color of the mixed sample is a spectral mixture of colors of its separate fractions. Presumably, this is the main reason for such a phenomenon as change of spectral reflectivity of open surface of soils under the influence of atmospheric precipitation.

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.

One of the main stream of digitalization in agriculture is the introduction of Internet of Things technologies, which is expressed in the creation and use of specialized sensors that are placed in the fields. The placement of such sensors within agricultural plot should make it possible to characterize all the microvariability of soil fertility parameters in the field. That is, their number and spatial location should be optimal, on the one hand, in terms of costs of their acquisition and operation, and, on the other hand, in terms of accuracy of interpolation of data obtained with their help to the entire plot. It has been shown that the use of crop condition maps obtained on the basis of satellite data and the separation based on them of management zones can lead to significant errors in the interpolation of monitoring results, obtained in separate points, on the whole plot. An approach for optimization of sensor placement is proposed based on the use of soil fertility mapping, which is the result of refinement, updating and clarification of traditionally drawn soil maps on the basis of high spatial resolution remote sensing data. The possibilities of using the approach are demonstrated by the example of a test plot in Leningrad region of Russia.

Dust is a major component of atmospheric aerosols – 75% of the global aerosol load. Natural and anthropogenic sources are listed, as well as dust research methods. According to different estimates, the average mineral dust load in the atmosphere ranges from 20 to 33 Tg, and the annual dust emission is 1 200–5 900 Tg/year. Reports from the Intergovernmental Panel on Climate Change (IPCC) inform about the total direct radiative forcing of dust ranging from -0.56 to +0.1 W/m2, with little scientific understanding of the processes leading to this result. The particle size, including soil aerosol, is divided into fine (20 μm) dust. Fine dust cools the global climate due to dispersion of solar radiation, while coarse dust (greater than 5 μm) warms the climate by absorbing solar and thermal radiation. However, the coarse dust (above 20 μm) remains poorly investigated, with very little data on its content and emission. Recent studies suggest that coarse dust (17 Tg), missed by the global models, contributes on average 0.15 W/m2 (0.10 to 0.24 W/m2) to atmospheric heating and also affects the global distribution of clouds and precipitation. In addition, soil dust is characterised by a complex and diverse particle shape and structure, heterogeneous mineralogical and chemical composition; due to its dispersion ability and large surface area dust reacts with other types of aerosols, resulting in the formation of different films on the particle surface or internal mixing. All this significantly changes the optical properties of mineral dust and complicates the development of models for its investigation.

Methodological approaches to the formation of a unified national system for monitoring and accounting the balance of carbon and greenhouse gas emissions are considered. The purpose, typification, requirements for the spatial placement of “carbon” polygons, assessment of the carbon absorption capacity of forests and agricultural ecosystems in the Russian Federation, the standard methodology recommended by the international community for assessing carbon stocks in soils, which should be applied in the Russian Federation to ensure comparability of the results of greenhouse gas accounting between countries, determination of the carbon absorption capacity of natural ecosystems and soils are discussed. The potential of carbon uptake by agricultural soils is shown. The list of indicators for assessing soil carbon according to the IPCC methodology for Tiers 2 and 3 is given. Taking into account the analysis of international practice, as well as on the basis of theoretical and applied experience of national science, the priority measures have been developed, they are aimed at working out and implementation of the national strategy for the use of terrestrial ecosystems in order to regulate greenhouse gas emissions to mitigate climate change.

The necessity of a comprehensive description of greenhouse gas fluxes on different types of soils, the methodology for creating “carbon polygons” and “carbon farms” with the use of modern methods for assessing carbon fluxes in ecosystems, taking into account the specifics of the natural conditions of Russia and competitive advantages, are substantiated. Directions for developing national methods for calculating carbon fluxes are given, which should be subjected to verification by the interested parties of the Paris Agreement adopted by the Russian Federation. Such issues are considered as the role and potential of the Russian soil cover in the carbon balance of the planet, factors of reducing carbon stocks from the upper 1 meter depth layer of the soil, competitive edge in the EU and the Western world in the questions of natural and climatic changes, the use of remote sensing of the Earth from space in order to obtain regular, complete and reliable estimates of the absorption of greenhouse gases.

The analysis of the possibility of using the thermal infrared images for detecting soil fertility parameters of gray forest and alluvial arable soils was carried out by the example of a test filed in Tula region of Russia. Together with the sampling of 25 soil probes from the 0–10 cm layer, the open surface of the soil was photographed using a FLIR VUE 512 thermal imager, and the spectral reflectance of the soil was measured. According to the results of the correlation analysis, it was found that the closest correlations for thermal images are observed with the following parameters of soil fertility: the content of humus, nitrogen, exchangeable magnesium and potassium. The correlation coefficient between the humus content and the reflectance in the visible and near IR-regions, as well as with the average value of the reflectance in thermal band exceeds 0.81. In different diapasons of the visible spectrum, the spectral reflectance correlation with the content of exchangeable magnesium and potassium is lower than in the thermal band, where the correlation coefficient with the content of exchangeable magnesium is 0.81, and with the content of exchangeable potassium is 0.65. Power regression equations were constructed for detecting such soil fertility parameters as humus content (R2 = 0.74), exchangeable potassium content (R2 = 0.68), and exchangeable magnesium content (R2 = 0.72) by reflection in the thermal band of the spectrum. The regressions obtained with the thermal imager data and with the spectral reflectance data in the visible and near IR-bands are similar in quality for detecting humus and exchangeable potassium content, while for detecting exchangeable magnesium content they are a bit higher. The obtained results show that thermal infrared images are applicable for detecting the most significant parameters of soil fertility in the test field and can be used as a basis for their real-time remote sensing monitoring.

The article presents a scientific literature review in the field of modern methods of monitoring wind erosion of soils such as: visual indicators of erosion, erosion bridge, close-range photogrammetry, cesium-137 and remote sensing cover. The brief description of each method, advantages and disadvantages, conditions and limitations of their applicability are given. When choosing the method, it is necessary to take into account the monitoring conditions, the area of the territory under consideration and the scale of research, time frames, financial and labor resources. It has been established that the most relevant, economically justified and promising, especially on large territories, are the remote sensing methods, which allow monitoring on different scales, and not only estimating the erosion activity, but also predicting it, thus providing the parties concerned with the necessary information for making right, prompt and timely economic decisions, aimed both at combating wind erosion and elimination of its consequences, and for organizing preventive measures as well. To improve the effectiveness of these methods it is also necessary to create databases, expand and accumulate soil information that can help verify, refine, process and calibrate the satellite data obtained. In order to understand aeolian processes and dust particle transport mechanisms one should create integrated methods that include remote sensing data, meteorological data, on the basis of which the improved models and maps would be developed, and erosion processes would be predicted. The scientific literature is mostly devoted to the interpretation of wind erosion in arid and semi-arid zones. The possibility of satellite monitoring of soil erosion in arable fields remains poorly studied. There are also practically no research results available on the transport of chemicals with micro-particles due to wind erosion. Both in Russia and abroad the attempts are made in soil erosion modelling, but the quality of the models is very limited by the lack of field data required for their calibration and verification. Eroded soils in the country are still identified using ground-based methods. However, field studies can only be conducted in a very limited area, in a few key points, and as a matter of fact it is quite complicated to conduct field studies on actively used agricultural lands.

Modern Russian Pedology is a young science and emerged a little more than 100 years ago. The article is devoted to the analysis of modern scientific schools in the field of soil science, which are developing in Russia. The investigations are based on the analysis of candidate's dissertations (PhD theses equivalent in Russia) defended on a specialty “soil science” in Russia for the last ten years, as well as on information about the scientific advisors supervised these dissertations and their belonging to this or that scientific school. It has been found that the most actively developing schools are the ones of immediate disciples of V.V. Dokuchaev, A.V. Sovetov or A.N. Sabanin. The schools of S.S. Neustruev and I.V. Tyurin are singled out as separate “branches” in the development of Russian soil science. At present, the main training resource centres in pedology are the Faculty of Soil Science of Lomonosov Moscow State University, Russian State Agrarian University – Moscow Agricultural Academy named after K.A. Timiryazev, V.V. Dokuchaev Soil Science Institute, Bashkir Agricultural Institute, Voronezh and Kuban universities. Number of soil scientists with advanced degrees over the past 10 years has tended to decrease, which is associated with the low demand for the profession in modern conditions of the country.

Delineation of especially valuable agricultural lands (EVAL) is currently an important task, which will make it possible to preserve agricultural land for its direct use. There are currently no uniform approaches for delineation of EVAL, or they need to be upgraded. We have proposed a new approach based on GIS modeling and simulation of agricultural plant growth. It is proposed to delineate EVAL for each municipal district taking into account its existing specialization in agricultural production. The allocation of EVAL should be based on the assessment of potential productivity of soils and lands for cultivation of the main crops in the district. EVAL should also include pilot fields and areas used for scientific and educational purposes, regardless of potential soil productivity. The proposed approach has been successfully tested on the example of Yasnogorsk district of Tula region. It is shown that the EVAL map, based on the proposed approach, is more related to the actual land productivity and does not depend on the current land use within the area. It is possible to build an EVAL map for the whole country only by building such maps separately for all municipal districts of Russia.

The analysis of peculiarities of applied use of soil data has been carried out. It is shown that most of practical tasks require spatial information about soils and their properties. In this regard, a soil map is considered as a kind of interface between theoretical and applied soil science. The disadvantages and limitations of modern soil maps, which significantly reduce the possibility of their practical use, have been revealed. The analysis of possible ways of overcoming the revealed limitations has been carried out. It is established that increase of practical importance of soil science at present is impossible both without technological modernization of soil mapping and without semantic, methodological adjustments. The complete transition from traditional soil maps to pixel spatial soil databases is necessary and already possible. Information load and accuracy of soil maps can and should be increased due to transition from mapping of soil position in one or another classification to mapping of individual, agriculturally important soil properties. In order to solve practical agricultural problems it is important to complete the information of soil maps with information about modern processes occurring in soils, which can be obtained from spatial digital modeling.

One of the features of the transition from traditional soil cartography to digital technologies for compiling and using soil maps is a qualitative change in both the concept of “map” and the concept of “map scale”. A map in digital cartography is a spatially coordinated database that can consist of many layers of information and can be visualized at any scale. The scale of traditionally compiled paper soil maps is of great importance for understanding the semantic load of the map and the degree of its generalization. When using digital soil mapping, the concept of “scale” loses its meaning. This happens because the level of generalization of soil information in this case is not determined by the scale at which the map is visualized on the computer monitor or printed, but by what pixel size the map was created (in the case of raster maps) or which map served the basis for creating a vector layer of the soil map. For raster soil maps it is more logical to use the concept of “pixel size” instead of “scale”. For vector soil maps it is more important to indicate the scale of the original soil map (which was vectorized), rather than the scale of their visualization. The scale of visualization of the digital soil map is not important in the computer (digital) applied analysis of soil data. When creating raster soil maps, it is impossible to use source materials of different scales without bringing them to a unified level of generalization. All this must be taken into account when using digital soil mapping technology.

The analysis of the Landsat 5 satellite data helped to study the processes of soil changes which took place from 1991 to 2011 inclusively at the test site located in the south-west of the Belgorod Region. As a result, it was found that despite intensive agricultural land use the proportion of soils, the properties of which have changed over the past 20 years, within the total area studied is quite small. The changes of soil erosion status were recorded within the territory of no more than 1 % of the total area; the territories characterized by soil humus losses on subhorizontal surfaces cover no more than 2 % of considered area. The most intensive process among the others is humus accumulation in the soil, the increase in humus content is noted on 5.6 % of the analyzed area. The identified tendencies in soil changes may be due to both the specifics of agricultural land use and climate changes.

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.

The paper presents the results of the of the country's plowed area assessment on the basis of the Unified State Register of Soil Resources of Russia, a digital land cover map created on the basis of MODIS satellite data, and study of plowed land areas according to the data of the Internet service Google Earth. Information on the plowing of soils is tied to the soil-geographical units. The map shows the actually plowed soils and soils under the layland. Independent verification of the plowland soil digital map of Russia showed its high enough accuracy (an error of about 8–9%). The share of all plowed soils of the Unified State Register of Soil Resources in Russia has been determined. It is found that chernozem soils predominate on the arable land of Russia, from the northernmost subtypes to the most southern ones. Somewhat unexpected is the presence in this list of meadow chernozem solonetzic and solonchak soils. The map is intended for applied analysis and accounting of soil resources at the national level.

The long-term dynamics of agrochemical properties for leached chernozem under an orchard monoculture has been studied. The objects of monitoring are two testing areas in the south (“Krasnodar”) and in the center of the European part of Russia (“Michurinsk”) without applying of organo-mineral fertilizers and chemical melioration to the soil. A significant decrease of the main fertility indicators within the soils humus horizon has been revealed during the period of intensive growth and stabilization of apple trees yields for the testing area in the south of Russia: a reduction in the nitrogen mineral forms stores and nitrification ability, and in exchange potassium stores. As for the area in the center of the European part of Russia, a trend for the content of mobile forms of phos-phorus and potassium decreasing during the growth and stabilization of apple yields has been revealed. The regression models obtained as a result of the anal-ysis were linear and revealed probable significant trend of the decrease for the observed indicators over time. Quantitative changes in the parameters of the organic matter content in soils within the boundaries of the testing area made it possible to identify the processes of dehumification: in conditions of monocul-ture at the natural level of fertility. During the period from 1990 to 2014, the depletion of soil organic matter contained 7.5%. It is shown that the processes of soil organic matter depletion occur differently under different soil and climatic conditions. It is established that apple plantations, consuming the amount of available forms of mineral elements needed for the forming of sustainable yields, create prerequisites for the development of processes of chernozems chemical degradation. Absence of fertilizers and chemical reclamation on this background contribute to aggravation of this process.

The results of digital mapping of organic carbon content within the arable horizons of soils and the assessment of obtained models accuracy with the use of machine learning methods for the area of Central Russian Upland in Voronezh Oblast are presented. The digital mapping was based on 22 points of soil samplings, applied for the learning and verification of models, and also on several sets of predictor variables. We took also digital elevation model, its derivatives and also remote sensing data of different spatial resolution as predictor variables. Several methods were used to create the spatial variability models for the investigated property based on the decision trees methods: random forest, boosting regression trees and Bayessian regression trees. The assessment of the models obtained accuracy was conducted by a method of cross-validation. As the accuracy indices we used the determination coefficient, mean absolute error and the root mean square error. The modelling results showed that the use of predictor variables presented by digital elevation model, its derivatives and Landsat 8 data we were able to obtain more sustainable models. The determination coefficient varied from 0.6 to 0.7, RMSEcv, i.e., the prognosing error varied from 0.5791 to 0.6520. Whereas, the best model was obtained with the method of Bayessian regression trees; whereas the predictor variables presented by the digital elevation model, its derivatives and Sentinel 2 data determination coefficient varied from 0.47 to 0.55, and the prognosing error varied from 0.7031 to 0.7909. It was revealed that in the described models according to different data sets the most significant were the various predictor variables.

The issues of improving land relations, rational land use and adaptation to climate are considered as the basic directions of the development strategy of the agro-industrial complex, discussed and supported by the Presidium of the RAS (18.04.2017). It is emphasized that the main determinant of a successful solution of all problems in modern land use management in Russia are measures to protect the soil cover, an adequate assessment of its condition and a fundamental change in land relations that the Federal Land Service should resolve. The consequences of the inconsistent implementation of land reform in the post-Soviet period, the main negative outcome of which are the latifundism of large agroholdings and companies, are shown. The resource potential of the modern land fund of the country is estimated to be one third less than the pre-perestroika one. The main direction in the development of agroproduction is modernization, intensification, development of land reclamation and chemicalization, which will allow us to reach, at a minimum, the average world yield level (3.5 tons / ha). The risks associated with the proposed land expansion (plowing) of land withdrawn from circulation, including marginal and badlands, are discussed. Examples of micromorphological indication of soil degradation and uncertainty associated with the detection of the results of modern space images analysis are shown. The necessity of actualization of information on soil degradation and assessment of suitability (favorability) for active agricultural production is substantiated.

The temporal dynamics (1980-1989-1997-2002-2007-2012-2015) of the physical and chemical properties of the mountain chernozems, the most widely spread soils of the northern slope of Djinal ridge, were studied. The investigations were conducted on the lands of “Kabardino-Balkaria Research Institute of Agriculture”. We revealed that according to the state of these soils in a year 2015 the soils were affected by two types of degradation processes, which differ according to the development degree and the spatial cover of the territory. The whole territory is characterized by the processes of the strong dehumification, and the processes of medium degree of dehumification are manifested only within local areas. The consequences of the strong dehumification of the investigated soils are manifested in the significant (the coefficient is 0.70) decrease of their fertility level. The damage for the soils affected by the strong dehumification reaches 18% according to the assessment of the lands value. The most of the studied soils were also affected by the agro-exhausting in a weak or medium degree. The fertility level index for weakly diluted soils of the agricultural areas is considered to be equal to 0.90. The damage for the assessment of the land area for these soils contain 5%. The decrease of the fertility for weakly diluted soils is insignificant (the coefficient of the fertility level is 0.95), and the damage for the purposes of the land area assessment may be neglected. We calculated the total damage (30009 rubles per ha) due to the degradation processes which affected the value of the land area. We also calculated the cost of rehabilitation of these soils and their recovery to the level of the initial state.

The color is one of the main morphological properties of soils, as it integrally reflects their material composition. Most of the macro-, micro- and nano-morphological methods in pedology are based on the analysis of soil reflectance characteristics within the visible spectrum (i.e., soils color). The evolution of soil color study methods and the features of modern instruments are described in the report. The main directions in the development of this field of soil science as well as the achievements and problems to be addressed in the study of soil color are demonstrated by specific examples.

The data obtained by GRACE satellite allowed comprehensively analyzing the dynamics of total terrestrial water storage within the period from 2003 to 2012 at the territory of European Russia. Having compared the satellite data and the information on the dynamics of the groundwater level obtained in the course of field survey by using 12 evenly distributed bore holes at the studied territory (Central Federal and North-Caucasian Federal regions), it is worth emphasizing that there is a clearly expressed co-variation between the satellite images and the groundwater depth. The analysis of trend in total water content identified by satellite data showed that it is positive towards the north-western and negative in the south and south-eastern part of European Russia. The total content of terrestrial water storage reveals periodical changes in the range from 3 to 8-9 years. The prolonged periods are observed in central and north-western parts, being shortened towards the north and south-east of the studied territory. The obtained data serve as evidence of periodically changing the total terrestrial water storage but its minimum will be observed in the east of Northern Caucasus, in Vologda, Yaroslavl, Moscow and Kostroma regions in 2016, in central part and Krasnodar region in 2018-2019 and in Kirov and Perm’ regions in 2016-2017. The results of the given studies can find a use in long-term forecasting of crop yields, in soil mapping and cultivation of new fruit plantations.

As seen from a comprehensive review of literature sources, at the current stage of technological development and simplicity the pilotless aircrafts should be considered as a reliable tool for operative monitoring of soils and crops on fields and areas of small farms. The possibilities to use the imagery obtained by pilotless aircrafts are predetermined by a type of survey apparatus to a considerable extent. At present, the miniature survey apparatus permits to obtain images, the spectral resolution of which can be compatible with those obtained by satellites. Today, the images of pilotless aircrafts are used to give a visual assessment of any object to be surveyed. There are publications devoted to the computer analysis of images including those used for agricultural purposes. The experience is becoming common to use the imagery obtained by pilotless aircrafts and their computer analysis for constructing digital models of the field relief, monitoring over the soil erodibility and operative valuation of the agricultural crops state. Being compared with satellite imagery, the data of pilotless aircrafts have a number of advantages in aerial surveying. The major limits to use data obtained by pilotless aircrafts consist in insufficient miniaturization of the surveying apparatus and the fact that the monitoring cannot be organized to control over large areas.

A new approach to estimating the quality of arable lands was developed as based upon MODIS-derived satellite data. The essence of the approach consists in an expert analysis of NDVI curves created separately for different crop groups in the last 10–12 years as well as the inter-annual variability of the NDVI seasonal maximum, whose value was used as an indicator for the crop state and yield on different fields. The nature of NDVI curves allowed expertly classifying the groups, characterizing the winter, early spring and late spring crops. The approach to estimating the quality of arable lands was approved on the example of the Baksan region in Kabardino-Balkaria. All the arable lands have been comprehensively analyzed in the region, the mask of which was created by visual interpretation of field boundaries using LANDSAT satellite data. The temporary NDVI profiles were obtained by the satellite service VEGA. Based upon the given method all the fields in the region were classified according to the quality of arable lands. The obtained data may be used in cadastre surveys for objective estimate of lands and optimal arrangement of the main agricultural crops in this Republic, being applicable in the other regions of the Russian Federation.

The state of the exposed surface of arable soils strongly varies in time and depends on properties of the upper soil horizon, meteorological conditions, and specific character of its usage. A change of the arable soil surface has a significant effect on their image on remote sensing data. For the maximum extraction of information about the spatial heterogeneities of soil properties satellite survey must be carried out before the first treatment of the surface of arable soils in spring.

Possibilities to use the archive images obtained by Landsat TM5 in different years have been comprehensively analyzed with the aim at recognizing the soils with different salinity degree. Special approaches were proposed to study the dynamics of saline soils by using the satellite imagery. Based upon a computer analysis of the information transmitted by Landsat in 1987-1988 and 2009-2010 as well as the data of field soil survey, it seemed reasonable to identify changes in the area of such soils in Shauldersk irrigated massive (the South-Kazakhstan region, Republic of Kazakhstan). It was concluded that the share of saline soils revealed an increase at the studied territory within the period from 1987 to 2010.

The variability of the brightness heterogeneities of the open chernozemic soil surface on LANDSAT images obtained in different seasons and different dates of survey were investigated. The brightness of the images (3 band) was unstable and considerably changes from one period of survey to another even within the one season of the year. Obtained results lead to the conclusion that during the automated recognition of soils on the satellite images the analysis of brightness of single image cannot serve as reliable basis for the digital soil mapping.

An analysis of the possibility of using Landsat satellite data for the recognition of the most widespread soils of Benin was made. It was found that it is impossible to detect all the soils depicted on the soil map based on Landsat satellite images for the research area. More accurately, the soils developed on identical soil-forming rocks are distinguished. The revealed features of the grouping of soils by image tone characteristics are most likely due to the specific properties of the soil surface, and also to the type of vegetation growing on them. The found specifics of soil detection can be used to adjust the soil map of Benin, as well as to organize satellite monitoring of soils of the Benin Republic.

Analysis of suitability of meteorological conditions in Mali for cotton cultivation was conducted. It has been determined that climatic conditions severely limit land usage for the cultivation of cotton in Mali. Climatic restrictions are not present only at 4% of the territory. Changing climatic conditions over the past 10 years are expressed only in a small shift of the start and end of the growing season of cotton to earlier dates and don’t affect the results of suitability analysis.