In-season Winter Wheat Distribution Dataset in China at 10 m Resolution(WinterWheat-CN10m-2025)

This study proposed a method for constructing classification rules using Sentinel-1/2 time-series imagery and developed a robust and efficient Automated In-season Winter Wheat Mapping (AIWM) approach. By synergistically integrating optical and radar time-series information, the method introduced the Automatic In-season Winter Crop Index (AIWC) and the Crop Structure Difference Index (CSDI), which were successfully applied to identify winter wheat planting areas in China.

Without requiring ground samples, the method enabled large-scale, spatiotemporally continuous crop mapping across regions and years, resulting in the generation of the China Mid-season Winter Wheat Distribution Dataset. This dataset will be updated and released annually by mid-April.The dataset provides information on the spatial distribution of winter wheat in China during the mid-growing season at a 10 m resolution. It was generated using the AIWM approach, which integrates Sentinel-1 and Sentinel-2 time-series imagery.