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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractSocio-economic and institutional changes may accelerate land-use and land-cover change. Our goal was to explore the determinants of agricultural land abandonment within one agro-climatic and economic region of post-Soviet European Russia during the first decade of transition from a state-command to market-driven economy (between 1990 and 2000). We integrated maps of abandoned agricultural land derived from 30 m resolution Landsat TM/ETM+ images, environmental and socioeconomic variables and estimated logistic regressions. Results showed that post-Soviet agricultural land abandonment was significantly associated with lower average grain yields in the late 1980s, higher distance from the populated places, areas with low population densities, for isolated agricultural areas within the forest matrix and near the forest edges. Hierarchical partitioning showed that average grain yields in the late 1980s contributed the most in explaining the variability of agricultural land abandonment, followed by location characteristics of the land. While the spatial patterns correspond to the classic micro-economic theories of von Thünen and Ricardo, it was largely the macro-scale driving forces that fostered agricultural abandonment. In the light of continuum depopulation process in the studied region of European Russia, we expect continuing agricultural abandonment after the year 2000.

HighlightsGlobal patterns of land use intensity are poorly understood, particularly in the developing world.The multidimensionality of land use intensity should be considered by jointly using input, output, and system metrics.A range of cropland intensity metrics exist, but existing data are often uncertain.Large data gaps remain for grazing and forestry intensity.Research priorities should include first, better integration of satellite-based and ground based data, second, validating and better documentation of datasets, and third, creation of consistent time series.