Mapping 10-m harvested area in the major winter wheat-producing regions of China from 2018 to 2022

Winter wheat constitutes approximately 20% of China's total cereal production. However, calculations of total production based on multiplying the planted area by the yield have tended to produce overestimates. In this study, we generated sample points from existing winter wheat maps and obtained samples for different years using a temporal migration method. Random forest classifiers were then constructed using optimized features extracted from spectral and phenological characteristics and elevation information. Maps of the harvested and planted areas of winter wheat in Chinese eight provinces from 2018 to 2022 were then produced. The resulting maps of the harvested areas achieved an overall accuracy of 95.06% verified by the sample points, and the correlation coefficient between the CROPGRIDS dataset is about 0.77. The harvested area was found to be about 13% smaller than the planted area, which can primarily be attributed to meteorological hazards. This study represents the first attempt to map the winter wheat harvested area at 10-m resolution in China, and it should improve the accuracy of yield estimation.

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Publication Details

Journal
Scientific Data
Published
2024-09-27
DOI
https://doi.org/10.1038/s41597-024-03867-z
Citations
17
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
7.80

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article

Mapping 10-m harvested area in the major winter wheat-producing regions of China from 2018 to 2022

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17 citations
Scientific Data
Remote Sensing in Agriculture
7.80
article

Mapping 10-m harvested area in the major winter wheat-producing regions of China from 2018 to 2022

Jinkang Hu, Yunlong Tan, Shengwei Liu, Jianxi Huang, Bin Zhao, Enhui Cheng, Zihang Lou, Bing Zhang, Wenjuan Zhang, Songlin Yang, Yulong Lv, Yong Li, Dailiang Peng
article en
17 citations

Abstract

Winter wheat constitutes approximately 20% of China's total cereal production. However, calculations of total production based on multiplying the planted area by the yield have tended to produce overestimates. In this study, we generated sample points from existing winter wheat maps and obtained samples for different years using a temporal migration method. Random forest classifiers were then constructed using optimized features extracted from spectral and phenological characteristics and elevation information. Maps of the harvested and planted areas of winter wheat in Chinese eight provinces from 2018 to 2022 were then produced. The resulting maps of the harvested areas achieved an overall accuracy of 95.06% verified by the sample points, and the correlation coefficient between the CROPGRIDS dataset is about 0.77. The harvested area was found to be about 13% smaller than the planted area, which can primarily be attributed to meteorological hazards. This study represents the first attempt to map the winter wheat harvested area at 10-m resolution in China, and it should improve the accuracy of yield estimation.

Scientific DataVol. 11(1)
Chinese Academy of Sciences (CN), Beijing Institute of Big Data Research (CN), Aerospace Information Research Institute (CN), Nanjing Surveying and Mapping Research Institute (China) (CN), University of Chinese Academy of Sciences (CN), Henan Polytechnic University (CN), China Agricultural University (CN), Shandong Agricultural University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Zero hunger
Openalex Percentile: Top 2%
Remote Sensing in Agriculture
7.80
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