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A critical review on applications of hyperspectral remote sensing in crop monitoring

Published online by Cambridge University Press:  25 July 2022

Huan Yu Open the ORCID record for Huan Yu [Opens in a new window] ,
Bo Kong ,
Yuting Hou ,
Xiaoyu Xu ,
Tao Chen  and
Xiangmeng Liu
Huan Yu*
Affiliation:
College of Earth Sciences, Chengdu University of Technology, 610059, Chengdu, China
Bo Kong
Affiliation:
Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, 610041, Chengdu, China
Yuting Hou
Affiliation:
College of Earth Sciences, Chengdu University of Technology, 610059, Chengdu, China
Xiaoyu Xu
Affiliation:
Department of Geography and Environmental Resources, Southern Illinois University Carbondale, Carbondale, IL 62901, USA Environmental Resources and Policy, Southern Illinois University Carbondale, Carbondale, IL 62901, USA
Tao Chen
Affiliation:
College of Earth Sciences, Chengdu University of Technology, 610059, Chengdu, China
Xiangmeng Liu
Affiliation:
College of Earth Sciences, Chengdu University of Technology, 610059, Chengdu, China
*
*Corresponding author. Email: yuhuan0622@126.com
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Summary

Numerous technologies have contributed to the recent development of agriculture, especially the advancement in hyperspectral remote sensing (HRS) constituted a revolution in crop monitoring. The widespread use of HRS to obtain crop parameters suggests the need for a review of research advances in this area. HRS offers new theories and methods for studying crop parameters, but much work needs to be done both experimentally and theoretically before we can truly understand the physical and chemical processes that predict these crop parameters. The study focuses on the following elements: 1) The article provides a relatively comprehensive introduction to HRS and how it can be applied to crop monitoring; 2) Current state-of-the-art techniques are summarized and analyzed to inform further advances in crop monitoring; 3) Opportunities and challenges for crop monitoring applications using HRS are discussed, and future research is summarized. Finally, through a comprehensive discussion and analysis, the article proposes new directions for using HRS to study crop characteristics, such as new data mining techniques including deep learning provide opportunities for efficient processing of large amounts of HRS data; combining the temporal and dynamic characteristics of crop parameters and vegetation growth processes will greatly improve the accuracy of crop parameter detection and monitoring; multidata fusion and multiscale data assimilation will become HRS monitoring. Multidata fusion and multiscale data assimilation will become another research hotspot for HRS monitoring of crop parameters.

Keywords

Precision agricultureCrop monitoringCrop parametersHyperspectral remote sensing
Type
Review
Information
Experimental Agriculture , Volume 58 , 2022 , e26
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Copyright
© The Author(s), 2022. Published by Cambridge University Press

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