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Early-season mapping of winter wheat in China based on Landsat and Sentinel images

物候学 冬小麦 环境科学 生长季节 作物 植被(病理学) 农业 空间分布 中国 产量(工程) 农学 自然地理学 地理 遥感 生物 病理 材料科学 冶金 考古 医学
作者
Jie Dong,Yangyang Fu,Jingjing Wang,Haifeng Tian,Shan Fu,Zheng Niu,Wei Han,Yi Zheng,Jianxi Huang,Wenping Yuan
出处
期刊:Earth System Science Data [Copernicus Publications]
卷期号:12 (4): 3081-3095 被引量:127
标识
DOI:10.5194/essd-12-3081-2020
摘要

Abstract. Early-season crop identification is of great importance for monitoring crop growth and predicting yield for decision makers and private sectors. As one of the largest producers of winter wheat worldwide, China outputs more than 18 % of the global production of winter wheat. However, there are no distribution maps of winter wheat over a large spatial extent with high spatial resolution. In this study, we applied a phenology-based approach to distinguish winter wheat from other crops by comparing the similarity of the seasonal changes of satellite-based vegetation index over all croplands with a standard seasonal change derived from known winter wheat fields. Especially, this study examined the potential of early-season large-area mapping of winter wheat and developed accurate winter wheat maps with 30 m spatial resolution for 3 years (2016–2018) over 11 provinces, which produce more than 98 % of the winter wheat in China. A comprehensive assessment based on survey samples revealed producer's and user's accuracies higher than 89.30 % and 90.59 %, respectively. The estimated winter wheat area exhibited good correlations with the agricultural statistical area data at the municipal and county levels. In addition, the earliest identifiable time of the geographical location of winter wheat was achieved by the end of March, giving a lead time of approximately 3 months before harvest, and the optimal identifiable time of winter wheat was at the end of April with an overall accuracy of 89.88 %. These results are expected to aid in the timely monitoring of crop growth. The 30 m winter wheat maps in China are available via an open-data repository (DOI: https://doi.org/10.6084/m9.figshare.12003990, Dong et al., 2020a).
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