The purpose of the study was to identify the main stages and space images processing methods in agrolandscape study and to structure them into a generalized technological scheme, as well as to analyze and generalize the decoding features of main indices of irrigated soil cover on space photos. The studies were carried out by taking into account the scientific and practical developments of Russian and foreign scientists in the field of agrolandscape research using remote sensing data and were based on experimental and theoretical methods. The main technological blocks are singled out: organizational and managerial, initial data, pre-thematic processing, thematic decoding and creation of GIS. It is noted that at present the methods for applying space survey to assess the dynamic properties of soil cover (salinity, erosion, dehumification, etc.) both at the qualitative and quantitative levels are being developed. To create regression models for determining the humus content, the channels of the average infrared and visible spectrum portions are often used. As a result of the analysis of various data it was revealed that it is possible to determine the soil moisture content with 2–4 % gradations (with a relative error of about 12 %) by the space images. The studies where the granulometric texture is determined along other indicators most often with the humus content prevail. The complexity of the soil-and-vegetation cover which causes a spotted image on space images is typical for the alkalized agrolandscape plots. Forms of gully erosion (deep ruts, ravines) are depicted only in the highest resolution (1–2 m) images in the form of narrow, clearly outlined contours of the jagged form. The current state of space research methods for agrolandscapes is characterized by the development of digital analysis means, integration with GIS technologies, information field formation of open data sources.
Key words: irrigated agrolandscape, space survey, processing methods, spectral properties of soils, automated decoding.
