A 30-m resolution distribution map of maize for China based on Landsat and Sentinel images

As the second largest producer of maize, China contributes 23% of global maize production and plays an important role in guaranteeing maize markets stability. In spite of its importance, there is no 30 m spatial resolution distribution map of maize for all of China. This study used a time-weighted dynamic time warping method to identify planting areas of maize by comparing the similarity of time series of a satellite-based vegetation index at each pixel with a standard time series derived from known maize fields and mapped maize distribution from 2016 to 2020 over 22 provinces accounting for more than 99% of the maize planting area in China. Based on 18800 field-surveyed pixels at 30-meter spatial resolution, the distribution map yields 76.15% and 81.59% of producer’s and user’s accuracies averaged over the entire investigated provinces, respectively. Municipality- and county-level census data also show a good performance in reproducing the spatial distribution of maize. This study provides an approach to mapping maize over large areas based on a small volume of field survey data. 1: maize classification system: 0: non-maize <br> Ruoque Shen, Jie Dong, Wenping Yuan, Wei Han, Tao Ye, Wenzhi Zhao, "A 30 m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel Images", <em>Journal of Remote Sensing</em>, vol. 2022, Article ID 9846712, 12 pages, 2022. https://doi.org/10.34133/2022/9846712中国作为全球第二大玉米生产国，贡献了全球23%的玉米总产量，在保障全球玉米市场稳定方面发挥着关键作用。尽管玉米产业的重要性不言而喻，但目前尚无覆盖全中国全域的30米空间分辨率玉米分布地图。本研究采用时间加权动态时间规整（time-weighted dynamic time warping）方法，通过将每个像素的卫星遥感植被指数时间序列与已知玉米田的标准时间序列进行相似度比对，识别玉米种植区域。本研究以2016至2020年为研究时段，针对占中国玉米总种植面积99%以上的22个省份完成了玉米分布制图。 基于18800个30米空间分辨率的野外调查像素点，该玉米分布地图在全部调研省份的生产者精度与使用者精度平均值分别达到76.15%和81.59%。市、县级普查数据也验证了该地图能够较好地复现玉米种植的空间分布格局。本研究提供了一种基于少量野外调查数据的大区域玉米分布制图方法。 1: 玉米 分类体系： 0: 非玉米 沈若雀, 董杰, 袁文平, 韩伟, 叶涛, 赵文智. 基于Landsat与Sentinel影像的中国30米分辨率玉米分布地图[J]. 遥感学报, 2022, 卷2022, 文章编号9846712, 共12页. https://doi.org/10.34133/2022/9846712