I. Yu. Savin

Near infrared spectroscopy techniques for soil contamination assessment in the Nile Delta

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.

National approaches to evaluation of the degree of soil degradation

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 updating of medium-scale soil maps

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.

Match method and its application for the development of a large-scale soil map

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.

Carbon Balance in Forest Ecosystems of Southern Part of Moscow Region under a Rising Aridity of Climate

This study estimates carbon balance in a mixed mature forest on sod-podzolic sandy-loamy soil (Albeluvisols sandy, the Prioksko-Terrasny Nature Reserve) and in a secondary deciduous forest at the Experimental Field Station of the Institute of Physicochemical and Biological Problems of Soil Sciences, Russian Academy of Sciences (gray forest loamy soil, Luvisols loamy). CO2 emissions from soils have been continuously measured every week since 1998. Net primary production was estimated in 2000–2014 by remote sensing using the normalized difference vegetation index. Long-term weather monitoring has revealed a distinctive trend toward increasing aridity of climate in the southern part of Moscow region in the observation period (1998–2014). Based on long-term ground-based and satellite monitoring data, this study shows that in the growing season, mixed and deciduous forests of the southern part of Moscow region are the sink of carbon with a mean flux of 41–112 g C m–2, depending on the contribution of root respiration. Taking into account the CO2 emissions from soils during the cold season, the forests are very likely to function as sources of atmospheric carbon at an amount of 30–100 g C m–2 yr–1, sometimes reaching very significant values of C flux (170–300 g C m–2 yr–1). In mature forest ecosystems, a significant influence on the quantitative estimate of the C balance is hampered by the CO2 emission activity from coarse woody debris, which can reach up to 14% of the total losses of C during the decomposition of soil organic matter in the mixed forest, which turns it into a persistent source of CO2 to the atmosphere. It is shown that the sink function of the forest ecosystems was more pronounced in dry years, whereas the excessive wetness diminishes their sink potential, turning the forests into sources of carbon dioxide.

Automated updating of medium-scale soil maps

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.

GPR Diagnostics of Chernozem Humus Horizon Thickness

This work aimed to search for indicators of the thickness of the humus horizon of chernozem soils based on the data of ground-penetrating radar (GPR) surveying. The investigation was carried out on a test site located in Russia’s Tula oblast. The area is dominated by arable podzolized chernozems, including ones eroded to a varying extent. In parallel with GPR profiling in the field, soil was drilled to determine the lower boundary of the humus horizon. Based on the conjugate analysis of GPR profiling data and the field determination of the thickness of the humus horizon, a new indicator was proposed: the coefficient of asymmetry of the modal value of the peak of the spectral density of the first-period reflected GPR pulse obtained at a frequency of 100 MHz. The proposed indicator demonstrates a good statistical relationship with the thickness of the humus horizon of chernozem soils. For the test region, a regression model of this relationship was constructed with a determination coefficient of approximately 0.82. To calculate the thickness of the humus horizon (A+AB), it is suggested to use the lower boundary of the second period of the spectral density of the reflected signal, which correlates well with the actual data. The developed approach can be used to map the thickness of the humus horizon in the chernozem soils of the research region. Theoretically, this approach can be extended to soils of other regions.

Mapping of Rill Erosion of Arable Soils Based on Unmanned Aerial Vehicles Survey

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.

POSSIBILITIES OF DETECTING OF SOILS OF BENIN BASED ON LANDSAT SATELLITE IMAGES

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.

The resource potential of Russian lands for crop farming

Geoinformational analysis shows that the fraction of lands that are optimal for farming of the main crops in Russia is about 10% of the available land at best (for summer wheat, buckwheat). For the majority of other crop cultures, this value is a few percent at most. The available resources are used very incompletely. The index of completeness of land resource potential use is no more than 10% for the majority of crops. Only in the case of soy are the available resources almost completely involved, whereas available land resources of winter wheat, grain maize, and sunflowers are used at 20–30%.