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基于无人机遥感的农作物病害监测研究进展

曹英丽 张弘泽 郭福旭 冯帅 杨璐璐 魏松红

沈阳农业大学学报2024,Vol.55Issue(5):616-628,13.
沈阳农业大学学报2024,Vol.55Issue(5):616-628,13.DOI:10.3969/j.issn.1000-1700.2024.05.012

基于无人机遥感的农作物病害监测研究进展

Research Progress of Crop Disease Monitoring Based on UAV Remote Sensing

曹英丽 1张弘泽 2郭福旭 2冯帅 1杨璐璐 2魏松红3

作者信息

  • 1. 沈阳农业大学信息与电气工程学院,沈阳 110161||国家数字农业区域创新分中心(东北),沈阳 110161||辽宁省智慧农业技术重点实验室,沈阳 110161
  • 2. 沈阳农业大学信息与电气工程学院,沈阳 110161
  • 3. 沈阳农业大学植物保护学院,沈阳 110161
  • 折叠

摘要

Abstract

Efficient and precise monitoring of crop diseases is not only critical for ensuring agricultural production safety but also plays a pivotal role in shaping national food security policies.In recent years,with the rapid advancement of unmanned aerial vehicle(UAV)technology,UAV remote sensing has gained widespread application in agricultural crop disease monitoring due to its advantages of high spatial resolution,timeliness,and relatively low cost.This paper first introduces the background of UAV remote sensing in crop disease monitoring and summarizes the commonly used UAV equipment in agricultural production,along with the sensors they carry for crop monitoring.Next,it systematically reviews the specific applications and achievements of UAV remote sensing in crop disease monitoring,from the dual perspectives of technical methods and research progress.Finally,key factors affecting the accuracy of UAV-based disease monitoring are discussed in detail,the current technical bottlenecksare analyzed,and the future development direction of UAV remote sensing for crop disease monitoring is also envisioned.This study aims to provide theoretical support and practical guidance for the development of crop disease monitoring platforms and related technologies in China.

关键词

作物/病害/无人机遥感/深度学习/目标检测/语义分割

Key words

crop/disease/UAV remote sensing/deep learning/target detection/semantic segmentation

分类

天文与地球科学

引用本文复制引用

曹英丽,张弘泽,郭福旭,冯帅,杨璐璐,魏松红..基于无人机遥感的农作物病害监测研究进展[J].沈阳农业大学学报,2024,55(5):616-628,13.

基金项目

国家水稻产业技术体系项目(CARS-01) (CARS-01)

辽宁省科技厅博士科研启动项目(2023-BSBA-282) (2023-BSBA-282)

沈阳农业大学学报

OA北大核心CSTPCD

1000-1700

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