DOI: 10.57760/sciencedb.ecodb.00202
title: In-season Winter Wheat Distribution Dataset in China at 10 m Resolution(WinterWheat-CN10m-2025)
title: 中国冬小麦10m分辨率的季中种植分布数据集WinterWheat-CN10m(2025)

description: Accurate early-stage monitoring of crops is crucial for assessing growth and predicting yields. 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. The data are provided in raster format, where a pixel value of 0 represents other crops or non-cropland, and a value of 1 indicates winter wheat. It should be noted that due to missing Sentinel-1 imagery in some regions (e.g., Sichuan, Hubei, Shaanxi and Gansu) in 2025, the mapping results for these areas are incomplete.1. WinterWheat-CN10m-2025-01.tifContains: Xinjiang2. WinterWheat-CN10m-2025-02.tifContains: Shandong, Hebei, Shanxi, Henan, Jiangsu, Anhui, Beijing, Tianjin3. WinterWheat-CN10m-2025-03.tifContains Hubei, Sichuan, Gansu, and Shaanxi(Note: some areas are missing in this image) In Version 2, the winter wheat distribution maps for Jiangsu and Xinjiang have been updated.
description: Accurate early-stage monitoring of crops is crucial for assessing growth and predicting yields. 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. The data are provided in raster format, where a pixel value of 0 represents other crops or non-cropland, and a value of 1 indicates winter wheat. It should be noted that due to missing Sentinel-1 imagery in some regions (e.g., Sichuan, Hubei, Shaanxi and Gansu) in 2025, the mapping results for these areas are incomplete.1. WinterWheat-CN10m-2025-01.tifContains: Xinjiang2. WinterWheat-CN10m-2025-02.tifContains: Shandong, Hebei, Shanxi, Henan, Jiangsu, Anhui, Beijing, Tianjin3. WinterWheat-CN10m-2025-03.tifContains Hubei, Sichuan, Gansu, and Shaanxi(Note: some areas are missing in this image) In Version 2, the winter wheat distribution maps for Jiangsu and Xinjiang have been updated.