MANAGING RURAL LAND USE MODELS IN THE CONTEXT OF URBAN AGGLOMERATION

DOI 10.32651/267-135

Issue № 7, 2026, article № 17, pages 135-144

Section: Social problems of rural territories

Language: Russian

Original language title: УПРАВЛЕНИЕ МОДЕЛЯМИ ЗЕМЛЕПОЛЬЗОВАНИЯ СЕЛЬСКИХ ТЕРРИТОРИЙ В УСЛОВИЯХ ВЛИЯНИЯ ГОРОДСКОЙ АГЛОМЕРАЦИИ

Keywords: RURAL AREAS, LAND USE, SUSTAINABLE DEVELOPMENT, PENZA AGGLOMERATION, MANAGEMENT MODEL, GROWTH POINT, CLUSTER, TERRITORIAL PLANNING, SOCIO-ECOLOGICAL-ECONOMIC SYSTEM

Abstract: Based on an analysis of the socio-economic situation of rural councils within the Penza agglomeration, disproportions in their development, population density, and territory area are identified. Spatial-statistical models (regression models for identifying determinants of land use change) and scenario modeling were used for forecasting purposes. Four typical management scenarios are considered: basic (current trends without additional measures); active agglomeration (stimulation of housing and commercial construction, weak protection of agricultural land); conservation (strict zoning, measures to preserve agricultural land and ecosystems); sustainable mixed development (targeted investments in agricultural infrastructure, green belts, and multifunctional rural areas). A forecasted settlement pattern of the agglomeration is proposed based on the identified "growth points." The results of the study are of practical importance for regional authorities in the development of strategic and territorial planning documents aimed at improving the quality of life for the rural population and the efficiency of the agricultural sector. Based on the analysis, functional types of rural areas within the Penza agglomeration have been identified. The proposed integrated land use management model, based on a systemic and socio-ecological-economic approach, allows for the integration of analysis, planning, regulation, control, and feedback processes, adapting them to the specific needs of individual municipalities. The inclusion of a feedback loop makes the model adaptable to changing conditions.

Authors: Vinnichek Liubov Borisovna, Akimova Mariia Sergeevna, Karabanova Natalia IUrevna