Abandonment and recultivation of agricultural lands in Slovakia: Patterns and determinants from the past to the future - Robert Pazúr; Juraj Lieskovský; Matthias Bürgi; Daniel Müller; Tibor Lieskovský; Zhen Zhang; Alexander V. Prischchepov (Land, 2020)
Central and Eastern Europe has experienced fundamental land use changes since the collapse of socialism around 1990. We analyzeanalyzed the patterns and determinants of agricultural land abandonment and recultivation in Slovakia during the transition from a state-controlled economy to an open-market economy (1986 to 2000) and the subsequent accession to the European Union (2000 to 2010). We quantified agricultural land-use change based on available maps derived from 30-m multi-seasonal Landsat imagery and analyzeanalyzed the socioeconomic and biophysical determinants of the observed agricultural land-use changes using boosted regression trees. We used a scenario-based approach to assess future agricultural land abandonment and recultivation until 2060. The maps of agricultural land use analysis reveal that cropland abandonment was the dominant land use process on 11% of agricultural land from 1986 to 2000, and on 6% of the agricultural land from 2000 to 2010. Recultivation occurred on approximately 2% of agricultural land in both periods. Although most abandoned land was located in the plains, the rate of abandonment was twice as high in the mountainous landscapes. The likelihood of abandonment increased with increased distance from the national capital (Bratislava), decreased with an increase of annual mean temperatures and was higher in proximity to forest edges and on steeper slopes. Recultivation was largely determined by the opposite effects. The scenario for 2060 suggests that future agricultural land abandonment and recultivation may largely be determined by climate and terrain conditions and, to a lesser extent, by proximity to economic centers. Our study underscores the value of synergetic use of satellite data and land-use modeling to provide the input for land planning, and to anticipate the potential effects of changing environmental and policy conditions.
Keywords: 630; land cover; land use; land use intensity; remote sensing; machine learning; Landsat; land change drivers; Eastern Europe; socialism; scenario; climate