A new high-resolution crop yield dataset has been released, providing detailed insights into maize, rice, and soybean production across Northeast China from 2016 to 2021. With a spatial resolution of 10 meters, the dataset represents a significant advancement in agricultural monitoring and food security research for one of China’s most important grain-producing regions. Developed using a combination of satellite remote sensing data, statistical yield records, and advanced modeling techniques, the dataset captures fine-scale spatial variability in crop yields. This level of detail allows researchers, policymakers, and agricultural planners to better understand yield patterns, productivity differences, and long-term trends across provinces such as Heilongjiang, Jilin, and Liaoning. The dataset covers three major staple and cash crops:
By spanning six consecutive growing seasons, the dataset enables analysis of interannually variability, climate impacts, and management practices influencing crop performance. It also supports applications such as yield gap assessment, climate change impact studies, precision agriculture, and regional food supply forecasting. Researchers highlight that the 10 m spatial resolution bridges the gap between field-level observations and regional statistics, making the dataset particularly valuable for local-scale decision-making and model validation. Compared with coarser global products, this dataset offers improved accuracy in heterogeneous agricultural landscapes. The release is expected to support ongoing efforts in sustainable agriculture, crop monitoring, and policy evaluation, while also serving as a benchmark dataset for future studies in Northeast China and beyond.
