Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.
Sci Data. 2021 Feb 2;8(1):41. doi: 10.1038/s41597-021-00827-9.
Northeast China is the leading grain production region in China where one-fifth of the national grain is produced; however, consistent and reliable crop maps are still unavailable, impeding crop management decisions for regional and national food security. Here, we produced annual 10-m crop maps of the major crops (maize, soybean, and rice) in Northeast China from 2017 to 2019, by using (1) a hierarchical mapping strategy (cropland mapping followed by crop classification), (2) agro-climate zone-specific random forest classifiers, (3) interpolated and smoothed 10-day Sentinel-2 time series data, and (4) optimized features from spectral, temporal, and texture characteristics of the land surface. The resultant maps have high overall accuracies (OA) spanning from 0.81 to 0.86 based on abundant ground truth data. The satellite estimates agreed well with the statistical data for most of the municipalities (R ≥ 0.83, p < 0.01). This is the first effort on regional annual crop mapping in China at the 10-m resolution, which permits assessing the performance of the soybean rejuvenation plan and crop rotation practice in China.
中国东北地区是中国的主要粮食生产区,产量占全国的五分之一;然而,该地区一直缺乏一致和可靠的作物图,这阻碍了区域和国家粮食安全的作物管理决策。在这里,我们利用(1)分层制图策略(耕地制图后进行作物分类)、(2)特定于农业气候带的随机森林分类器、(3)插值和平滑的 10 天哨兵-2 时间序列数据以及(4)从土地表面的光谱、时间和纹理特征中优化的特征,制作了 2017 年至 2019 年中国东北地区主要作物(玉米、大豆和水稻)的年度 10 米作物图。生成的地图具有基于丰富地面实况数据的高总体精度(OA),范围从 0.81 到 0.86。卫星估计与大多数直辖市的统计数据吻合较好(R≥0.83,p<0.01)。这是中国首次在 10 米分辨率下进行区域年度作物制图,可评估中国大豆复壮计划和轮作实践的效果。