Agricultural areas are declining in many areas of the world, often because socio-economic and political changes make agriculture less profitable. The transition from centralized to market-oriented economies in Eastern Europe and the former Soviet Union after 1989 represented major economic and political changes, yet the resulting rates and spatial pattern of post-socialist farmland abandonment remain largely unknown. Remote sensing offers unique opportunities to map farmland abandonment, but automated assessments are challenging because phenology and crop types often vary substantially. We developed a change detection method based on support vector machines (SVM) to map farmland abandonment in the border triangle of Poland, Slovakia, and Ukraine in the Carpathians from Landsat TM/ETM+ images from 1986, 1988, and 2000. Our SVM-based approach yielded an accurate change map (overall accuracy = 90.9%; kappa = 0.82), underpinning the potential of SVM to map complex land-use change processes such as farmland abandonment. Farmland abandonment was widespread in the study area (16.1% of the farmland used in socialist times), likely due to decreasing profitability of agriculture after 1989. We also found substantial differences in abandonment among the countries (13.9% in Poland, 20.7% in Slovakia, and 13.3% in Ukraine), and between previously collectivized farmland and farmland that remained private during socialism in Poland. These differences are likely due to differences in socialist land ownership patterns, post-socialist land reform strategies, and rural population density.