Winter Wheat Maturity Prediction via Sentinel-2 MSI Images

Jibo Yue, Ting Li, Jianing Shen, Yihao Wei, Xin Xu, Yang Liu, Haikuan Feng, Xinming Ma, Changchun Li, Guijun Yang, Hongbo Qiao, Hao Yang () and Qian Liu ()
Additional contact information
Jibo Yue: College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China
Ting Li: College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China
Jianing Shen: College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China
Yihao Wei: College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China
Xin Xu: College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China
Yang Liu: Key Lab of Smart Agriculture System, Ministry of Education, China Agricultural University, Beijing 100083, China
Haikuan Feng: College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
Xinming Ma: College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China
Changchun Li: Institute of Quantitative Remote Sensing and Smart Agriculture, Henan Polytechnic University, Jiaozuo 454000, China
Guijun Yang: Key Laboratory of Quantitative Remote Sensing in Agriculture, Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
Hongbo Qiao: College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China
Hao Yang: Key Laboratory of Quantitative Remote Sensing in Agriculture, Ministry of Agriculture and Rural Affairs, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
Qian Liu: College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China

Agriculture, 2024, vol. 14, issue 8, 1-22

Abstract: A timely and comprehensive understanding of winter wheat maturity is crucial for deploying large-scale harvesters within a region, ensuring timely winter wheat harvesting, and maintaining grain quality. Winter wheat maturity prediction is limited by two key issues: accurate extraction of wheat planting areas and effective maturity prediction methods. The primary aim of this study is to propose a method for predicting winter wheat maturity. The method comprises three parts: (i) winter wheat planting area extraction via phenological characteristics across multiple growth stages; (ii) extraction of winter wheat maturity features via vegetation indices (VIs, such as NDVI, NDRE, NDII1, and NDII2) and box plot analysis; and (iii) winter wheat maturity data prediction via the selected VIs. The key findings of this work are as follows: (i) Combining multispectral remote sensing data from the winter wheat jointing-filling and maturity-harvest stages can provide high-precision extraction of winter wheat planting areas (OA = 95.67%, PA = 91.67%, UA = 99.64%, and Kappa = 0.9133). (ii) The proposed method can offer the highest accuracy in predicting maturity at the winter wheat flowering stage ( R 2 = 0.802, RMSE = 1.56 days), aiding in a timely and comprehensive understanding of winter wheat maturity and in deploying large-scale harvesters within the region. (iii) The study’s validation was only conducted for winter wheat maturity prediction in the North China Plain wheat production area, and the accuracy of harvesting progress information extraction for other regions’ wheat still requires further testing. The method proposed in this study can provide accurate predictions of winter wheat maturity, helping agricultural management departments adopt information-based measures to improve the efficiency of monitoring winter wheat maturation and harvesting, thus promoting the efficiency of precision agricultural operations and informatization efforts.

Keywords: wheat; maturity; remote sensing; crop growth stage (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/14/8/1368/pdf (application/pdf)
https://www.mdpi.com/2077-0472/14/8/1368/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:14:y:2024:i:8:p:1368-:d:1456992

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().