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Land use and land cover change (LUCC) is not only a vital form of global change, but through biogeophysical and biogeochemical mechanisms, it also has a strong impact on the global and regional climate and environment change. The existing historical LUCC datasets still have many uncertainties that cause errors in climate and environment simulations. Reconstruction of historical LUCC on the regional scale is essential for improving the precision of global and national LUCC. In this study, we combined existing datasets with historical statistics and survey data to reconstruct cropland change in North China Plain Area over the past 300 years. Following systematic steps, a range of original methods from data sources and methods comparison, data re-calibration, time slices selection, data supplement, to cropland area fraction calculation were used. The cropland area at the county level was allocated into grid cells of 10 km × 10 km so as to achieve a high spatial resolution and precision. The results show that the cropland area change in North China Plain Area can be classified into two main stages: steady increase before 1954 and rapid decrease after 1954. The spatial distribution of cropland change over the past 300 years corresponded to the patterns of the total cropland change in North China Plain Area. From the late 17th century to the 1980s, the cropland area fraction in the plains increased and the cropland expanded to the hilly and coastal areas gradually. After that, the cropland area fraction in the plains decreased, especially in the southeastern of North China Plain Area. The total cropland area in North China Plain Area of our study is close to the results of most previous studies but the maps generated based on our dataset present local difference of cropland distribution more clearly than a recent important global dataset HYDE3.2. Our dataset of cropland area at 10 km × 10 km grid scale can also be used directly in climate and environment simulations to improve the data precision in North China Plain Area.