文献类型： 外文期刊
作者： Yue, Jibo 1 ; Yao, Yihan 1 ; Shen, Jianing 1 ; Li, Ting 1 ; Xu, Nianxu 2 ; Feng, Haikuan 3 ; Wei, Yihao 1 ; Xu, Xin 1 ; Lin, Yinghao 5 ; Guo, Wei 1 ; Fu, Yuanyuan 1 ; Qiao, Hongbo 1 ; Ma, Xinming 1 ; Wang, Jian 1 ;
作者机构： 1.Henan Agr Univ, Coll Informat & Management Sci, 63 Agr Rd, Zhengzhou 450002, Henan, Peoples R China
2.Jiangsu Police Inst, Dept Publ Secur Management, 48 Shifo San Gong, Nanjing 210031, Jiangsu, Peoples R China
3.Nanjing Agr Univ, Coll Agr, Nanjing, Jiangsu, Peoples R China
4.Beijing Acad Agr & Forestry Sci, Informat Technol Res Ctr, Key Lab Quantitat Remote Sensing Agr, Minist Agr & Rural Affairs, Beijing, Peoples R China
5.Henan Univ, Shenzhen Res Inst, Shenzhen, Guangdong, Peoples R China
6.Henan Univ, Sch Comp & Informat Engn, Henan Key Lab Big Data Anal & Proc, 2 Yuexing 3rd Rd, Shenzhen 518000, Guangdong, Peoples R China
关键词： Wheat; maturity; harvest; monitoring; vegetation index
期刊名称：INTERNATIONAL JOURNAL OF REMOTE SENSING （ 影响因子：2.6； 五年影响因子：2.9 ）
ISSN： 0143-1161
年卷期： 2025 年 46 卷 6 期
页码：
收录情况： SCI
摘要： Wheat is one of the most important staple crops globally. Timely mapping and monitoring of wheat harvests are essential for efficiently scheduling large-scale harvesters, ensuring the timely completion of the harvest, and maintaining grain quality. Traditional manual survey methods for obtaining wheat harvest information are neither highly accurate nor cost-effective and do not meet the needs of agricultural management departments. This study introduces two novel indices for wheat harvest detection: the optical-band brightness harvest index (OBHI) and the visible-band brightness harvest index (VBHI). The research is structured into three primary components: (1) Extraction of wheat planting areas, utilizing phenological features from multiple growth stages; (2) Extraction of wheat harvesting features, where the proposed OBHI and VBHI are analysed using the box plot method to identify the harvesting characteristics of wheat croplands; and (3) Wheat harvest detection, employing the OBHI, VBHI, and a threshold method to determine the harvest status. The key findings are as follows: (1) Combining the OBHI with a threshold method achieves the highest accuracy in detecting wheat harvest using Sentinel-2 MSI images; (2) Integrating Sentinel-2 multispectral remote sensing imagery with the OBHI threshold method enables real-time monitoring of wheat harvest progress. In the study area, the wheat harvest commenced on 1 June 2023 (0.62%) and was nearly complete by 13 June 2023 (97.94%). The OBHI and VBHI proposed in this study have the potential to assist agricultural management departments in improving the efficiency of wheat harvest supervision. However, further research and validation are necessary to determine the generalizability and applicability of this method.
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