A 10m spatial resolution dataset for the spatial distribu-tion of cropland resources in the three northeastern provinces from 2020 to 2022

Timely and accurate acquisition of cropland spatial distribution data is of great significance for agri-cultural production management, planting structure adjustment and food security. In this study, three northeastern provinces (Heilongjiang, Jilin and Liaoning) were selected as the research area. Based on massive Sentinel-2 data, a 12-month Normalized Difference Vegetation Index (NDVI) dataset of culti-vated land and non-cultivated land samples in a specific year was established in each province. The Google Earth Engine remote sensing computing platform was used to conduct supervised classification according to the difference characteristics of NDVI between cropland and non-cropland samples, and the spatial distribution data set of cropland resources with 10m spatial resolution in the three northeast-ern provinces during 2020-2022 was obtained. The data set is an update of the latest available cropland resource data set, which can provide data support and scientific services for the scientific protection of phaeozem in Northeast China, the implementation of the strategy of "storing grain in the land, storing grain in technology" and the guarantee of food security.