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Agricultural regionalization is perhaps one of the most complex kinds of revealing patterns in spatial differentiation of human activities. Formation of agricultural regions depend on numerous driving forces, combining natural conditions, human resources, cultural traditions and level of economic development. Thus, the present day dynamics of agricultural regions can be revealed through understanding of different kinds of processes, transforming the land use and land cover patterns, rural population and agricultural economy. Geographers have developed sophisticated tools for analysis of each of these groups of processes separately, but usually focus only on one of them, which often disable relevant results. Our paper provides an innovative approach to analysis of modern agricultural regions dynamics, based on a comparative study of remote sensing and statistical data. We focus on territories, where significant changes in agricultural development – positive or negative – recently happened, such as the interior parts of Brazil, where changes in land use and land cover during 2001—2012 were analyzed. Land cover changes were identified through processing of the Global Land Cover Facility data, and land use changes were revealed through processing of national agricultural and forestry statistics. Overlapping of both kinds of data served as a base for a complex typology of land use and land cover changes on a regional level. More ‘stable’ and more ‘dynamic’ regions were determined. This method seems productive not only for map of the agricultural regions dynamics, but also for determine its driving forces, and can be applied for other parts of the world.