A Predictive Model for Cropland Transformation at the Regional Level: A Case Study of the Belgorod Oblast, European Russia

The problem of choosing the type of land use is now more relevant than ever. Against the backdrop of the growth of urbanized territories, the challenge is to preserve cropland, maintain the quality of soil resources, and find a balance between competing land uses. Forecasting and modeling changes in the area of cropland is a sought-after area of research against the backdrop of a growing shortage of fertile land and a threat to food security. In this study, on the example of one of the agriculturally most developed administrative regions of Russia (Belgorod Oblast), an approach to statistical modeling of agricultural land areas over the past 30 years is shown. Two approaches were used: statistical modeling of the dynamics of the total area of the study region’s cropland depending on the balance of other types of land and spatial interaction modeling of cropland in a key area. For the study region, administrative districts with positive and negative cropland dynamics were identified; the main types of land were revealed, due to which cropland is withdrawn, and a regression balance model was developed. It was revealed that the implementation of the planned regional programs to expand the development and conservation of meadow lands will reduce cropland by 3.07% or 83.2 thousand ha. On the example of one of the administrative districts with high rates of urbanization, the probability of cropland transformation into other types of land was estimated and a predictive spatial model of land use was developed. According to the forecast, about 6.2 thousand ha of cropland will turn into residential development land, and 2/3 of their area will be concentrated within 6 km from the borders of the regional capital city (Belgorod). The presented approach to forecasting the area of cropland and the threats of its reduction due to the need to replace other types of land is relevant for all agricultural regions and countries with developing urbanization processes.