Abstract
Farmland use policy in China has evolved substantially over the past 70 years, undergoing five stages from communal (1950 s-1980 s) to household-based (1980 s-1990 s), land circulation (1990 s-2000 s), family farms (2000 s-2010 s), and then cooperative systems (2010 s-present). Among many benefits and consequences that have been explored in previous studies, an overlooked impact is the effective farmland planting area (EFPA), resulting from farmland fragmentation at different stages. We used remotely sensed imagery to quantify farmland fragmentation and EFPA in a representative agricultural area in northeast China. Specifically, we used the K-means (WKKM) and the regression decision trees (CART) classification methods to extract patch size of planted areas and crop planted information in the Google Earth Engine (GEE) environment, and compared the results with field measurements to assess the classification accuracy, and calculated the EFPA. The results showed that the total number of patches increased rapidly after the dissolution of the communal system but declined until the cooperative policy was implemented. The EFPA was negatively related to the number of patches, with an average of 90% EFPA during the commune period, ∼70% in the household responsibility period and ∼86% during the cooperative period. In conclusion, land use policy played a key role in balancing the EFPA and farmers’ incentives and thus affected the EFPA in northeast China.
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