The doctoral thesis describes methodologies and appropriate adaptations of existing solutions to model land suitability in two ways for the valley and basin areas of the South-Siberian Altai Mountains within a geo-information system (GIS) environment. Starting-point approaches are: 1) the Agricultural Soil Suitability Model „Almagra” and Land Capability Model “Cervatana”/MicroLEIS System (De la Rosa et. al 1992, 1998) developed for Mediterranean regions and a method specifically compiled by Burlakova L. M. (1988) for the Altai based on the weighted means of a factor set. 2) For comparison purposes, second, third and fourth versions of the same model are developed using three different types of Fuzzy Logic approaches. They are used to present how Gauss membership functions of particular classes can be computed as different classes and how variables taking values in ranges can be handled in a mathematical way. Furthermore, the paper presents ideas on how remote sensing might interact with the geo-information system (GIS) where - like in the present case – the required input geo-data are not fully sufficient to (i) feed the models formalising soil and climatic conditions, and (ii) to characterise the patterns of land management within the study area. Three agricultural crops (summer wheat, sunflowers and potatoes) are relevant to the Altai Region at a regional level and are, therefore considered. A rating is classified using five suitability classes according to the FAO classification (1976). For the case study the Uimon Basin was chosen. Social and economic factors are so far excluded but can be added within a further phase of development.