30 m-resolution annual crop type maps in Northeast China from 2001 to 2022

Northeast China, a crucial agricultural region contributing one-third of China's commodity grain production, lacks detailed, high-resolution crop maps pre-2013 due to limited satellite observations. To bridge this gap, this study developed annual 30 m crop type maps for Northeast China (2001-2022) using all available Landsat and MODIS imagery and the Highly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm. The accuracy of crop-type maps was assessed using three complementary approaches. First, validation against ground-truth data (2017-2022) yielded overall accuracies of 80.7%-91%. Second, validation using 'trusted pixels' from existing crop-mapping products (2001-2020) produced overall accuracies of 85%-95%. Third, comparison with government statistics (2001-2022) showed average R² of 0.98 (paddy rice), 0.83 (maize), and 0.90 (soybean). The generated maps were found to be the most consistent with government statistics compared to pre-existing crop maps, while providing comprehensive spatial and temporal details. This dataset is an important contribution to long-term fine-resolution crop mapping at the regional scale in China, which provide valuable guidance for sustainable agriculture practices in China's primary grain-producing region.