Igor Savin
Doctor of Agricultural Sciences

Remote sensing technologies are an indispensable tool to study our planet.


Graduated from Lomonosov Moscow State University. 

1984 - 1986

Engineer-weather forecaster of the Ministry of Defence (Soviet Union).

1986 - 1987

Engineer of forest protection of Shatura logging enterprise, Moscow region. 


Candidate thesis on “Decryption of soil cover of forest-steppe of the Central Black Earth region of medium-scale space images” was presented. Academic degree - Candidate of Geographical Sciences was awarded.

1990 - 2002

Head of the laboratory of V.V. Dokuchaev Soil Science Institute.

1993 – present

Professor of Agroengineering Department of Agrarian and Technological Institute RUDN (formerly - Department of Soil science, agriculture and land cadastre of the Agrarian Faculty RUDN).

2002 - 2009

Researcher, Institute for the Protection and Security of the Citizen (IPSC), Ispra, Italy.


Doctoral thesis on “Analysis of soil resources based on GIS technologies” was presented. Academic degree - Doctor of Agricultural Sciences was awarded.

2009 - 2011

Head of the sector of Space Research Institute of the Russian Academy of Sciences.

2011 - present

Deputy Director on scientific work of V.V. Dokuchaev Soil Science Institute. 

2016 - present

Corresponding member of scientific division on Agricultural Sciences (section of agriculture, melioration, water and forestry) RAS.


Conducts lectures for RUDN students of “Land management, cadastres” direction:

  • Geoinformatics,
  • Remote sensing,
  • Land monitoring.

The author of the following study guides:

  1. Digital soil mapping (Savin I. Yu.; Dokukin P. A. M.: RUDN, 2017, 156 p.)
    The study guide provides detailed instructions for processing field data to create digital soil maps using open source software (R, SAGA, QGIS, ILWIS, SoLIM). The purpose of the book is to make methods and approaches of digital soil cartography available to a wide range of specialists both theoretical and practical orientation - soil scientists, ecologists, geographers, agronomists. The first chapter provides a brief description of the programs used and a brief introduction to their interface. The second chapter describes procedures for initial data preparation: planning of sampling, harmonization of the relevant data on depths, morphometric analysis of digital elevation models, and finding and downloading satellite images from the resource earthexplorer.usgs.gov. The third chapter provides exercises - step-by-step instructions for creating digital maps based on field data of soil testing. The fourth chapter contains exercises to create maps of soil classes and properties based on satellite data. It is intended for use in courses on mapping and monitoring of soils and lands in the preparation of specialists in the directions “Agronomy”, “Land Management and Cadastres”, “Soil Science”, “Agrophysics”, “Landscape design”.
  2. Aerospace methods in forestry and agriculture (computer workshop) (Savin I. Yu., M., RUDN, 112 p., 2015)
    The study guide provides basic information about the techniques of computer interpretation and analysis of space images. The essence of the analysis methods and step-by-step instructions for practical tasks are described. Questions for self-examination are given. Tasks are based on the use of GIS application package ILWIS V. 3.3. For students studying in the directions “Agronomy” and “Land Management and Cadastres”.


  • Foundations of new methods of mapping (inventory) of soils in different scales, based on the use of modern computer GIS technologies and data of remote sensing of the Earth surface were developed.
  • Assessment of land suitability for cultivation of major crops at different levels of aggregation (all countries to the individual regions and farms) was conducted.
  • Developed Methodical basis of satellite monitoring of the soil cover to create a geographic information system (GIS) “Monitoring of black soil erosion” and GIS “Monitoring of soil moisture to predict barley yield” were developed.
  • Multivariate geographic information system to assess the resource potential of soils and lands of Russia was created.
  • Study in the development of satellite methods of monitoring crops and forecasting crop yields form the basis of the “System of remote monitoring of agricultural lands” of the Ministry of Agriculture of the Russian Federation, as well as the basis for a system of monitoring of crops of the European Commission.

Scientific interests

  • Remote mapping.
  • Monitoring of soils and lands.
  • Soil-genetic zoning.
  • Modern soil information system.
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.
The ‘4 per mille Soils for Food Security and Climate’ was launched at the COP21 with an aspiration to increase global soil organic matter stocks by 4 per 1000 (or 0.4 %) per year as a compensation for the global emissions of greenhouse gases by anthropogenic sources. This paper surveyed the soil organic carbon (SOC) stock estimates and sequestration potentials from 20 regions in the world (New Zealand, Chile, South Africa, Australia, Tanzania, Indonesia, Kenya, Nigeria, India, China Taiwan, South Korea, China Mainland, United States of America, France, Canada, Belgium, England & Wales, Ireland, Scotland, and Russia). We asked whether the 4 per mille initiative is feasible for the region. The outcomes highlight region specific efforts and scopes for soil carbon sequestration. Reported soil C sequestration rates globally show that under best management practices, 4 per mille or even higher sequestration rates can be accomplished. High C sequestration rates (up to 10 per mille) can be achieved for soils with low initial SOC stock (topsoil less than 30 t C ha− 1), and at the first twenty years after implementation of best management practices. In addition, areas which have reached equilibrium will not be able to further increase their sequestration. We found that most studies on SOC sequestration only consider topsoil (up to 0.3 m depth), as it is considered to be most affected by management techniques. The 4 per mille number was based on a blanket calculation of the whole global soil profile C stock, however the potential to increase SOC is mostly on managed agricultural lands. If we consider 4 per mille in the top 1m of global agricultural soils, SOC sequestration is between 2-3 Gt C year− 1, which effectively offset 20–35% of global anthropogenic greenhouse gas emissions. As a strategy for climate change mitigation, soil carbon sequestration buys time over the next ten to twenty years while other effective sequestration and low carbon technologies become viable. The challenge for cropping farmers is to find disruptive technologies that will further improve soil condition and deliver increased soil carbon. Progress in 4 per mille requires collaboration and communication between scientists, farmers, policy makers, and marketeers.
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%.
Legacy soil data have been produced over 70 years in nearly all countries of the world. Unfortunately, data, information and knowledge are still currently fragmented and at risk of getting lost if they remain in a paper format. To process this legacy data into consistent, spatially explicit and continuous global soil information, data are being rescued and compiled into databases. Thousands of soil survey reports and maps have been scanned and made available online. The soil profile data reported by these data sources have been captured and compiled into databases. The total number of soil profiles rescued in the selected countries is about 800,000. Currently, data for 117, 000 profiles are compiled and harmonized according to GlobalSoilMap specifications in a world level database (WoSIS). The results presented at the country level are likely to be an underestimate. The majority of soil data is still not rescued and this effort should be pursued. The data have been used to produce soil property maps. We discuss the pro and cons of top-down and bottom-up approaches to produce such maps and we stress their complementarity. We give examples of success stories. The first global soil property maps using rescued data were produced by a top-down approach and were released at a limited resolution of 1 km in 2014, followed by an update at a resolution of 250 m in 2017. By the end of 2020, we aim to deliver the first worldwide product that fully meets the GlobalSoilMap specifications.
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 (R 2 = 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.
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.
The optical properties of soils are the basis for mapping them from satellite data. The optical surface properties are affected by both soil and nonsoil factors; according to analysis of variance, the contribution of the latter to the variability of the optical properties is a factor of 2 greater. Moreover, their effect on the spectral reflectivity is more specific. Among the nonsoil factors that are analyzed, the mapping time is most closely associated with the optical properties. The models obtained in the course of regression analysis are characterized by good approximation quality and explain more than 61% of the variability of the given factor. The accuracy of the given models for the parameters developed to evaluate the optical properties is greater than 75%.
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.
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 soil cover of the Arctic zone of Russia is ∼330 million hectares. Permafrost restricts the thickness of the active layer but does not prevent the formation of significant diversity of soils and soil complexes, including Al–Fe humic and peat soils, gleysols, and others. The available data on soil resources are sufficient for organization and participation of Russia in scientific–practical international programs. At the same time, specific soil related targets and project tasks may require additional study of soils of the Arctic region.