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The research was aimed at the analysis of relationship between the soil surface spectral reflectance and the moisture content in soil samples as the basis for moisture detection based on remote sensing data. By the example of nine samples from the arable horizons of podzolized chernozem, gray forest and soddy-podzolic soils analyzed in laboratory, the relationship was assessed between the spectral reflectance of soil surface in the visible spectral band detected with the HandHeld-2 spectroradiometer and the moisture content in samples. It was found that changes in the soil moisture content induce synchronous changes in the integral reflection in the visible spectral band only in a rather narrow interval of moisture, being specific for different soils. Variation in soil moisture content beyond these intervals does not change the spectral reflectance of soil surface. The results obtained prove that most of the satellite survey data in the optical range register the dry state of open soil surface, though the arable horizon proper may be rather moist. These regularities should be taken into account when developing satellite techniques for prompt monitoring of soil moisture by the remote sensing data obtained within the optical range of electromagnetic waves.

The aim of the research was to analyze the relationship of color indicators of soil layers with the parameters obtained by ground-penetrating radar (GPR) profiling. Such parameters were the data of the spectral Fourier transform of the amplitude of the reflected pulse in the subsurface horizons of the soils of the Kamennaya Steppe area. GPR profiling was carried out by a Loza-V geophysical device. The diffraction points of reflected pulse amplitude corresponding to local soil horizons and groundwater surface were determined. The variability in the thickness of horizons and layers was calculated through the modules of amplitude maxima taking into account the conductivity of the horizon (dielectric permittivity and the rate of signal passage in a given medium). The procedure of verification of differentiation of sounding points was based on their comparison with real soil profiles and patterns. Statistical processing included the calculation of mean values, standard deviations, and frequencies of signal amplitude distribution; the use of the principal component method; and cluster analysis. Two polynomial models of connection of changes in parameters of the spectral Fourier transform of electromagnetic pulses in subsurface medium of chernozems with attributive parameters of formation of spectral pure colors of dominant wavelength (λi) were constructed. The indicative parameters included the conditional coefficient of pure color (Kλi), which corresponds to the addition functions in the tri-color colorimetric system MKO XYZ 1931, and its saturation, which is completely determined by the properties of the reflection coefficient (R) in the spectral range of λ 580–720 nm (red band). The calculated parameters of soil chromaticity obtained on the basis of these models were the prerogative for constructing the RGB model of soil layers and its visualization in graphic editors.

The main trends in the development of soil mapping methods are discussed, and the major problems are identified. By the present time, the transition from the paper-based soil maps to digital soil-geographical databases has already been completed. The digital mapping of soils and their properties is now accepted as the main method at all the levels of generalization. The approaches of digital soil mapping, as well as of the traditional one, are based on the ideas of V.V. Dokuchaev about the dependence of soils on soil-forming factors. However, in digital soil mapping, new achievements of mathematical statistics and mathematical modeling are being widely applied. This provides for a greater objectivity and reproducibility of the digital soil maps in comparison with the traditional soil maps. At the same time, all unsolved problems of soil cartography related to the lack of field observation data, scale, soil taxonomy, spatial microheterogeneity, and mapping of individual soil properties are preserved. Partially, these problems can be solved by using remote sensing data. When the soil geographical information is used to assess the quality of soil resources, the interpretation of remote sensing data for mapping purposes seems to be more preferable in comparison with the methods of digital soil mapping.

Possibilities of using data obtained from unmanned aerial vehicles for detection and mapping of rill erosion on arable lands are analyzed. Identification and mapping of rill erosion was performed on a key plot with a predominance of arable gray forest soils (Greyzemic Phaeozems) under winter wheat in Tula oblast. This plot was surveyed from different heights and in different periods to determine the reliability of identification of rill erosion on the basis of automated procedures in a GIS. It was found that, despite changes in the pattern of rills during the warm season, only one survey during this season is sufficient for adequate assessment of the area of eroded soils. According to our data, the most reliable identification of rill erosion is based on the aerial survey from the height of 50 m above the soil surface. When the height of the flight is more than 200 m, erosional rills virtually escape identification. The efficiency of identification depends on the type of crops, their status, and time of the survey. The surveys of bare soil surface in periods with maximum possible interval from the previous rain or snowmelt season are most efficient. The results of our study can be used in the systems of remote sensing monitoring of erosional processes on arable fields. Application of multiand hyperspectral cameras can improve the efficiency of monitoring.

An approach towards an automated updating of medium-scale soil maps via imitation of traditional mapping technologies is suggested. It is based on formulation of the rules of mapping in the form of classification trees for separating different soil cover patterns and on creation of the maps of soil-forming factors with the use of satellite data. Algorithms for mapping alluvial soils (Fluvisols), eroded (abraded), and anthropogenically transformed soils are presented. This approach was tested for the southern (Trans-Oka) part of Moscow oblast. The model for an automated soil mapping was realized using ILWIS software. The polygons of alluvial soils were mapped with a higher accuracy via the automated separation of floodplains according to the digital terrain model. The total area of alluvial soils shown on the medium-scale soil map decreased from 373 to 340 km2. Calculations of slope angles according to digital terrain models allowed us to localize soil cover patterns with participation of eroded soils with a higher accuracy; their area decreased insignificantly: from 791 to 781 km2. Anthropogenically transformed soils of building areas were mapped for the territory of Moscow oblast on the basis of satellite data for the first time. Their areas were delineated taking into account land use types and comprised 551 km2, i.e., 15.4% of the total area (3570 km2) of the Trans-Oka part of Moscow oblast.

Heavy metals concentration is considered one of the factors directly affecting soil and crop quality and, thus, human health. The objective of the current work was to critically examine the suitability of Vis- NIR (350–2500 nm) measurements for calibration procedures and methods to predict contaminated soil. 25 different sites were selected adjacent to drain Bahr El-Baqar east of Nile Delta. Spectroradiometer ASD was used to measure the spectral reflectance profile of each soil site. The concentrations of three heavy metals (Cr, Mn and Cu) were determined in the studied samples. Stepwise multiple linear regression (SMLR) was used to construct calibration models subjected to the independent validation. The obtained regression models were of good quality (R2 = 0.82, 0.75, and 0.65 for Cr, Mn, and Cu, respectively). Thus, Visible and Nearinfrared (Vis-NIR) reflection spectroscopy is cost- and time-effective procedure that can be used as an alternative to the traditional methods of determination of heavy metals in soils.

A geoinformation database for assessing soil resource potential for horticulture in Krasnodar region and Adygea has been developed. The results of geoinformation analysis indicate that only 55–60% of soils in these regions are suitable for growing horticultural crops without limitations; about 35–40% of the total soil area is unsuitable for horticultural purposes. For plum trees, the area of unsuitable soils is somewhat lower than for other horticultural crops. Geographically, the areas of soils suitable and unsuitable for horticulture are close to one another. The thickness of the loose earthy soil material, the gravel content, the degree of salinization, the soil texture, and the degree of soil hydromorphism are the major soil properties imposing considerable limitations for the development of fruit-growing industry in the studied regions. The highest portions of soils suitable for horticulture are found in Eiskii, Kushchevskii, Krylovskii, Shcherbinovskii, and Novokubanskii districts of Krasnodar region. The development of horticulture in Tuapsinskii, Slavyanskii, and Primorsko-Akhtarskii districts is limited because of the unsuitability of soils for this purpose. About 8% of the existing orchards are found on soils recognized as unsuitable for horticulture, and only about 20% of the existing orchards are found on soils suitable for fruit growing without limitations. About 70% of the existing fruit orchards are located on degraded soils or on soils with certain limitations for horticulture. The profitability of fruit orchards on such soils is lower than that of the orchards planted on soils without limitations for horticulture. This information is necessary for the adequate economic evaluation of the degree of soil degradation.

The principles of typological soil-genetic zoning based on the substantive-genetic classification of Russian soils (2004) and realized for the State Soil Map of Russia on a scale of 1 : 1 M are considered. Three categories of characteristics are applied to the system of zoning units: taxonomic, process-based, and landscape- indicative characteristics. The relationship between them changes in dependence on the taxonomic level of the zoning unit; at the lower level, the spatial (landscape-indicative) criterion plays the major role. This criterion is also important in the delimitation of soil groups (soil communities) serving as the central taxonomic unit of the zoning. At this level, all the three groups of characteristics are equally important. The definitions of the taxonomic units of the soil-genetic zoning are given, and their characteristic features are described. An algorithm of the zoning procedure is illustrated by the example of the maps developed for the Privolzhskii federal okrug. It is suggested that the soil-genetic zoning can be used as one of the ways to update the State Soil Map.

Approaches to evaluation of the degree of soil degradation and the related normative documents applied by specialists from state institutes for land management of the former Soviet Union in the course of largeand medium-scale soil surveys in the 1960s–1990s are analyzed. It is shown that the types and rates of soil degradation were specified without proper consideration for the taxonomic position of particular soils. Reference (nondegraded) soils were not clearly defined, which made it difficult to judge the degree of soil degradation by means of a comparative analysis of degraded and nondegraded soils. Such reference soils are suggested for several types of soil degradation (dehumification, compaction, depletion of nutrients, etc.). Additional diagnostic criteria of the degree of soil degradation caused by wind and water erosion, waterlogging, swamping, and other adverse processes are specified. The study of qualitative and quantitative changes in the soil properties during the post-Soviet period is important for the development of land monitoring system and for the analysis of economic aspects of land degradation. To ensure reliability of data on changes in the soil properties and soil cover patterns, possible errors related to incorrect comparison of the data obtained by traditional and modern approaches should be taken into account.

On the basis of legislative norms concerning land and nature management in Russia and scientific concepts of soil and land, new definitions of these basic concepts are suggested. Soils and lands are considered as separate components of the environment, each performing their own ecological functions. The definitions for land degradation and soil degradation are given. It is argued that the indicators of the ecological functions of soils and lands can be used for the qualitative and quantitative assessment of soil and land resources, ecological norming, and control of their ecological state, including degradation processes.

Possibilities of using satellite data for the evaluation of soil degradation processes on arable lands in Saratov region were analyzed. A regression model describing the relationships between the humus content in the upper layer of arable soils and their spectral reflectance was developed and applied to assess dehumification in the studied region on the basis of Landsat TM5 images. It was found that the humus content on 36.3% of test fields decreased by 1–2% in the period from 1988 to 2011. On the slopes with slightly eroded soils, the humus content decreased by 1.4–1.6% (in some cases, up to 2.5%); on the slopes with moderately eroded soils, by 1.8–2.0% (up to 2.8%). During the considered period, the area of slightly eroded soils increased by almost two times, and the area of moderately eroded soils increased by nearly three times. The most pronounced reduction in the humus content took place in the soils developed from sands, loamy sands, and sandy loams. An increase in the humus content was identified on the lower parts of the slopes (13.44% of test area), where the accumulation of the high-humus soil material eroded from the upper parts of the slopes could take place.

An approach for the updating of medium-scale soil maps is discussed. It is based on the use of modern remote sensing and geoinformation technologies. The boundaries of soil polygons shown on the old soil maps and their soil contents are corrected using geoinformation analysis of modern topographic data and automated interpretation of vegetation conditions as reflected on satellite imagery. The developed methods are illustrated by the particular examples.

A method for interpolating field soil data to obtain the maps of soil taxa is suggested. It is based on representation of categorical data in the form of Voronoi map with barriers limiting the areas with particular combinations of indicative soil-landscape relationships. The predictive capacity of the proposed model depends on the level of the taxon and exceeds 80% for soil types and subtypes in the study area. At different levels of detail of the indicative soil-landscape relationships, the accuracies of prediction are different. The proposed method significantly reduces the time of soil mapping and opens new possibilities for investigating the soil-landscape relationships.