The expediency of joint application of methods of multi-criteria decision analysis of (MCDA) and geoinformation systems (GIS) in order to assess the suitability of lands for cultivation of agricultural crops is substantiated. The implementation of this approach will make it possible to partially automate the process of assessing land. The studies were carried out on the territory of ZAO Mirny, Kochenevsky District, Novosibirsk Region (54°56′24″ N, 82°06′12″ E), located in the forest-steppe zone. Taking into account the peculiarities of the territory under consideration, the following criteria were selected for assessing suitability of lands: drainage condition, soils granulometric composition, contrast of soil cover, working areas elevation pattern, humus layer thickness, ploughness, terrain slope angle, exposure of slopes, erosion degree. The sources of spatial information were land management maps, soil and topographic maps, digital elevation model (DEM), SRTM, ultra-high resolution satellite images. The collection and processing of spatial information was carried out in QuantumGIS (QGIS), which has an open modular architecture. ELECTRE TRI and the hierarchy analysis method were selected for the analytical assessment of information within MCDA. For both methods, there are procedures that are integrated with QGIS. With the help of QGIS GIS tools, the land use of a particular agricultural enterprise was divided into working areas, their boundaries and areas were determined. A method for obtaining an attribute database is described for each criterion. An overview of the ELECTRE TRI methods and the hierarchy analysis method is given, and their launch procedures in QGIS are described. The criteria weights were obtained using the hierarchy analysis method (Easy АНР procedure in QuantumGIS), and the main result – the land suitability map (according to the FAO classification) – was obtained using the ELECTRE TRI method (ELECTRE TRI procedure for QuantumGIS). Since the result of the ELECTRE TRI procedure are two decision maps: according to the pessimistic and optimistic scenarios, additional studies were carried out, on the basis of which it was possible to establish that the map obtained according to the optimistic scenario has a greater consistency with the natural conditions of the agricultural enterprise.

In order to solve the problem of the land agroecological estimation (natural resources potential) automation and artificial information system development, it is necessary to make the domain knowledge (DK) conceptualization, or conceptual modelling. The unified modelling language (UML) was chosen as a descriptive system. Three abstract objects (class, attribute and relationship) were selected to describe 33 concepts for land plot basic natural characteristics and 13 significant nature process aspects regulating changes of those characteristics. For 6 DK concepts abstract object “class” was chosen, for 27 DK concepts – “attribute”, for 13 nature process aspects – “relationship”. Class “land plot” is a central one interacting with the other 5 classes: “relief”, “agrometeorological resource”, “soil”, “erosion”, “vegetation”. All classes and attributes interdependencies are described by relationship classification of 3 types. The first type is dependency relationship showing on UML diagrams a directed connection between two classes towards the main class, which means that changing the main class properties implies changing the dependant class properties; the second type is association relationship, which is any relationship showing connection characterized by almost any verb of the Russian language; the third type is composition relationship showing connection between composite and its part and is always directed to the composite, where deletion of the composite class implies deletion of all parts. Optimization of the DK conceptual model described by means of UML diagram is a permanent process, thus new classes and concepts can be added to the model throughout the time.