The recent development of precision farming technologies has necessitated the creation of the maps of sustainable intrafield heterogeneity of soil fertility on the basis of the analysis of remote sensing big data. To create such maps, thousands of remote sensing images for 35 years have been analyzed for each element of the earth surface to identify the areas of reduced fertility. The conducted analysis allows us to detect the areas of decreased fertility. In turn, such areas are indicative of the negative soil properties. Some of the negative properties are of the initial natural origin, and others appeared as a result of the development of degradation processes. It is possible to separate the zones of reduced fertility emerged due to the natural factors from those specified by the anthropogenic impacts on the basis of the analysis of morphometric parameters of surface topography coupled with technology of the spectral neighborhood of soil line. A combination of various methods of the analysis of big remote sensing data and landscape parameters has made it possible to create the maps of degraded lands with an accuracy sufficient for precision farming technologies. This study presents the results of identification of three natural and four anthropogenic factors of fertility decrease on arable land. The areas under the impact of particular degradation factors are identified with the help of remote sensing data. They have been verified by the ground soil survey. The results obtained are the direct consequence of the remote sensing big data analysis development. A soil cartographer, as well as a farmer, has now received a new method for detecting distribution patterns of degradation factors.

Changes in the land legislation of Russia led to the development of cadastral mapping. On agricultural land, the type of land use is taken into account. Land assessment is carried out on the basis of soil differences (soil units). This opens up new possibilities for large-scale soil mapping. It is required that soil maps contain the necessary information to fully realize the potential of soil cartography in solving practical problems of accounting and valuation of agricultural lands. Most of the soil maps for agricultural land contain errors of the first and second kind of information theory and have problems with soil taxonomy, that is: missing contours, excessive information and erroneous soil diagnostics. This significantly complicates the practical application of soil maps. On the basis of soil maps, it is not possible to establish the boundaries of territories where a change in land use occurs due to soil processes. There are also certain diagnostic and taxonomic difficulties in using soil maps for practical needs. The development of soil cartography in the form of a technology for retrospective monitoring of the soil and land cover can significantly improve soil mapping and facilitate the transfer of soil contours to cadastral maps.

Large-scale soil maps produced by research institutes for land management (GIPROZEM) are the main source of soil information on arable land in Russia. These maps date back to the 1960s–1990s. During the time that has passed since the last round of soil surveys, the development of precision farming has greatly increased the requirements for the accuracy of the maps. At present, archival soil maps require correction (verification, updating, detailing, and unification). It is suggested that the maps of stable intrafield heterogeneity (SIFH) of soil fertility based on the analysis of big remote sensing data can find application in modern agriculture. Such maps are created within the framework of the general concept of big data analysis, including big geodata and big agricultural data as its components. Comparative analysis of archival soil maps and the SIFH map for the territory of southern Russia attests to the great potential of SIFH maps for soil mapping. Missing soil polygons have been detected, the location of existing soil polygons has been refined, new soil units not marked on archival soil maps have been identified, and a plan for additional soil surveys within the framework of the data-driven geography concept has been worked out. The accuracy of the soil map has been improved to be applicable to state-of-the-art farming systems, including precision farming. A new source of information on the spatial heterogeneity of the soil cover and its fertility has appeared.

On soil maps and in land management documents, the excessively moistened areas of the earth surface are shown differently, and their areas on three different source maps (large-scale soil survey map, land cadaster map, and land management planning map) may differ by five times. According to current land legislation, soil maps should be used for cadastral valuation and cadastral division of arable land. It is supposed that the three sources of information on the land cover do not contradict one another. We analyzed the allocation of waterlogged lands on these source maps in order to find the reason for the existing discrepancies in the areas of waterlogged lands. Soil and land management materials from four rounds of the soil survey in 1937–1996 and remote sensing materials from 1968 to 2018 were analyzed. It was found that, until the third round of soil surveys, the concept of waterlogged area was the same for soil scientists, cadastral specialists, and land surveyors and meant the areas of limited use for arable farming because of the excessive atmospheric or ground moistening. Since the mid-1980s, soil scientists have ceased to consider waterlogging as a factor limiting land use, whereas land management specialists have not changed their approaches. In the cadastral division of land, the use of soil maps has become fragmentary; often, land plots are characterized as agreed with the owner. In 1958, the area of waterlogged soils on the soil map of Tambov oblast was 14%; all these lands had certain limitations of their use for arable farming. On the soil map of 1986, the area of waterlogged soils reached 65%, though only 6% of them were of limited use for arable farming. Independent retrospective monitoring methods applied by us to this territory indicated that limitations in the arable use of land related to the soil water regime are observed on about 16% of the territory of Tambov oblast. It is suggested that the allocation of waterlogged soils and lands should be unified on the basis on the technology of retrospective monitoring of soil and land covers.

A new quantitative approach to zoning of arid territories based on a new zoning climatic parameter (the sum of precipitation excesses over evaporation) and the soil-granulometric coefficient of moisture supply is proposed.

This study is an attempt to quantify parameters taken into account in separation of the dry steppe soil zone. A detailed analysis of the maps of zoning, vegetation, land use, and soils has made it possible to suggest quantitative criteria of the dry steppe soil zone in Russia and to gain a better correlation between the calculated boundaries of this zone and the maps of vegetation, land use, and soils. Except for the East European Plain, boundaries of the dry steppe zone with chestnut soils do not coincide on different maps of zoning. Climatic parametersthe sum of active temperatures, the humidity factor, and the continentality coefficientare the main factors specifying the spatial pattern of soil zones and facies on the maps of zoning. Soil characteristicstexture and water-physical propertiesplay a subdominant role. It is argued that data on the texture, water-physical properties, and solonetzic properties of soils should be taken into account in separation of the dry steppe zone as the factors controlling the depth of soil moistening and the reserves of productive moisture. Together with the accumulated sum of active temperatures, they specify the development of dry steppe vegetation and, hence, the boundaries of the dry steppe soil zone. A new indicatorthe sum of monthly excesses of precipitation over evapotranspirationshould be calculated with due correction for the soil texture, solonetzic properties, and the content of carbonates. In combination with the accumulated sum of active temperatures, this indicator makes it possible to perform a detailed zoning of the area of chestnut soils on a quantitative basis and to separate cryoarid areas (cold semideserts) and semideserts with chestnut soils. Soil zones and facies determined with the use of this indicator are in good agreement with geobotanical maps and maps of land use.

A new quantitative approach to the zoning of arid territories is proposed on the basis of a new climatic parameter for zoning (the sum of precipitation exceedances over evaporation) and a soil textural water recharge coefficient.

A classical soil line (SL) in the RED–NIR spectral space is specified by two coefficients “a” and “b.” In this form, it does not characterize soil types and subtypes. A multitemporal soil line (MSL) represents the major axis of the ellipse describing all possible pairs of RED–NIR values characterizing a bare soil surface for a given pixel of remote sensing images. The MSL in the RED–NIR spectral space is specified by several (N) coefficients. The resulting N-dimensional space of MSL coefficients makes it possible to give unique characteristics for each type and subtype of soils in the following zonal soil sequence: soddy-podzolic soils, light gray forest soils, gray forest soils, dark gray forest soils, podzolized chernozems, and leached chernozems. The analysis of variance allows us to state that the soils of this sequence significantly differ from one another in the characteristic sets of MSL coefficients. In other words, these coefficients characterize soil types and subtypes, and the MSL can be considered an empirical soil line (ESL) of the given type and subtype of soil. A classical SL is an integrity of ESLs of different soils within the given scene of remote sensing data.

A retrospective monitoring of changes in land use on cultivated salt-affected soils of Azov district in Rostov oblast for a period from 1968 to 2013 was performed within the framework of the creation of a problem- oriented system of retrospective monitoring of the soil cover and land uses. A higher dynamism of land uses on salt-affected soils in comparison with that on nonsaline soils was shown. A decisive role of the anthropogenic factor in the increasing soil salinization in the region was established. The areas of meadow ecosystems with participation of salt-affected soils considerably increased at the end of the 1960s–the beginning of the 1970s. It is argued that their development with a corresponding worsening of the salt status of regional soils was initiated by the wide-scale planting of shelterbelts in the 1940s and 1950s.

Soil as a separate natural body occupies certain area with its own set of spectral characteristics within the RED–NIR spectral space. This is an ellipse-shaped area, and its semi-major axis is the soil line for a satellite image. The spectral area for a bare soil surface is neighboring to the areas of black carbon, straw, vegetating plants, and missing RED–NIR values. A reliable separation of the bare soil surface within the spectral space is possible with the technology of spectral neighborhood of soil line. The accuracy of this method is 90%. The determination of the bare soil surface using vegetation indices, both relative (NDVI), and perpendicular (PVI), is incorrect; the accuracy of these methods does not exceed 65%, and for most of the survey seasons it may be lower than 50%. The flat part of the “tasseled cap” described as the soil line, is not a synonym for the area of the bare soil surface. The bare soil surface on the RED–NIR plots occupies significantly smaller areas than the area of soil line according to Kauth and Thomas.