Аннотация:Land use change models are tools for allocating different types of land use depending on a variety of factors in certain periods of time. They visualise results of statistical analysis and show the cumulative impact of different driving forces on land use change. Our study is based on applying CLUE model for analysing three key areas in the northern part of Ryazan region, namely the Meshchera Lowlands. Original land use data had been obtained from General Land Survey maps (XVIII c.), Atlas Mende maps (XIX c.), Corona satellite imagery (XX c.) and modern satellite images (XXI c.). Two kinds of factors influencing land use distribution were analysed: local biophysical (various relief, hydrology, soil parameters) and socio-economic (population density, distance to roads, rivers, etc). Results of logistic regression analysis were used for running the model. In most of existing models population density is the main driver of land use transformation, so one of our goals was to manipulate model parameters and examine the role population density plays in land use dynamics and spatial distribution across the key areas of research. Our results suggest that the relationship is very complex and often hugely dependent on other factors. Comparison of generated and existing land use patterns shows that population density does not determine the extent and spatial distribution of agricultural transformation on this scale. In XVIII-XIX centuries, despite significant population growth, in the absence of technologies agricultural expansion was limited by biophysical factors; later, it was outmatched by nationwide socio-political changes. Another result is a time series of land use maps interpolating between periods with known land use patterns.
The study was supported by RSF, project № 16-17-10045.
