Cropland abandonment, driven by urbanization and demographic transitions, is a global land-use change. Although its driving factors, extent, and spatial patterns have been widely documented, spatially explicit and temporally continuous estimates of how abandonment translates into losses of food-production capacity remain scarce, particularly at the national scale. This study aims to develop a remote-sensing method for tracking identified abandonment within the 2001 baseline cropland cohort in mainland China and to systematically quantify its spatiotemporal characteristics as well as its impact on agricultural productivity. A remote-sensing identification approach using land-use trajectories was developed to track abandonment among cropland pixels spanning 2001 to 2020. These records were coupled with a baseline of potential grain production to quantify the impact of persistent cropland abandonment on agricultural productivity. Within the 2001 baseline cropland cohort, the annual area of confirmed abandonment ranged from 36,399.30 to 226,873.77 km 2 , equivalent to 3.64–22.69 Mha, with an average abandonment rate of 8.25%, showing a significant upward trend. Spatially, confirmed abandonment within the baseline cohort followed a gradient pattern of “low in the east, high in the west”, with notable clustering in ecologically fragile regions and traditional agricultural areas in the west. The loss of potential grain production associated with confirmed abandonment within the baseline cropland cohort fluctuated, rising from 10.08 million tons in 2004 to a peak of 67.60 million tons in 2018, with a long-term annual average loss of 5.24%, indicating that the long-term abandonment of existing cropland may damage China's food-production capacity and increase its food-system vulnerability. The identification method and quantitative findings of this study provide empirical evidence and methodological foundation for monitoring persistent cropland abandonment and supporting food security governance.
Song et al. (2026) studied this question.
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