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Mapping 10-m harvested area in the major winter wheat-producing regions of China from 2018 to 2022.
Hu, Jinkang; Zhang, Bing; Peng, Dailiang; Huang, Jianxi; Zhang, Wenjuan; Zhao, Bin; Li, Yong; Cheng, Enhui; Lou, Zihang; Liu, Shengwei; Yang, Songlin; Tan, Yunlong; Lv, Yulong.
Afiliação
  • Hu J; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China.
  • Zhang B; International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
  • Peng D; College of Resource and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
  • Huang J; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China. zhangbing@aircas.ac.cn.
  • Zhang W; International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China. zhangbing@aircas.ac.cn.
  • Zhao B; College of Resource and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China. zhangbing@aircas.ac.cn.
  • Li Y; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China. pengdl@aircas.ac.cn.
  • Cheng E; International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China. pengdl@aircas.ac.cn.
  • Lou Z; College of Land Science and Technology, China Agricultural University, Beijing, 100083, China.
  • Liu S; Airborne Remote Sensing Center, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China.
  • Yang S; School of Information Science and Engineering, Shandong Agricultural University, Taian, 271018, China.
  • Tan Y; National Key Laboratory of Wheat Improvement and College of Agronomy, Shandong Agricultural University, Taian, 271018, China.
  • Lv Y; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China.
Sci Data ; 11(1): 1038, 2024 Sep 27.
Article em En | MEDLINE | ID: mdl-39333510
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.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sci Data Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sci Data Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China