无人机遥感监测作物病虫害研究进展

doi:10.11963/1002-7807.sycb.20210429

摘要/Abstract

摘要：

病虫对作物生产构成了巨大的威胁,可直接或间接导致作物减产甚至绝收。快速、高效地掌握病虫的发生动态并及时防控,对作物增产保收具有重要意义。无人机遥感是现阶段监测作物病虫害的一项重要技术,具有实时、快速、高效、客观、大面积、无损监测等优点,将推动农业生产向优质、高效、安全、信息化以及智慧化方向发展。本文从无人机遥感监测作物病虫害概况、数据源种类、数据获取方法、数据处理流程及方法等方面进行归纳分析;指出无人机遥感监测作物病虫害中存在的病虫害特征选择、病虫害分类识别、传感器优化以及数据处理等主要问题,针对存在的问题提出了深化病虫害特征选择算法、建立专属病虫害光谱数据库、开发专一的病虫害监测传感器以及研发病虫害数据处理平台等发展策略,以期为无人机遥感监测作物病虫害的相关研究提供参考。

关键词: 作物; 病虫害; 无人机; 遥感; 监测方法; 数据处理; 特征提取; 人工智能

Abstract:

In the process of crop production, pests and diseases pose a great threat to crop production, which can directly or indirectly lead to yield reduction or even crop failure. Rapid and efficient grasping of the dynamics of occurrence of pests and diseases and timely prevention and control are important for crop yield and income. Unmanned aerial vehicle (UAV) remote sensing is an important technology for monitoring crop pests and diseases at this stage. It has the advantages of real-time, fast, efficient, objective, large-area, non-destructive monitoring, which will promote the development of agricultural production in the direction of high quality, high efficiency, safety, informatization and wisdom. We summarize the situation, data source types, data acquisition methods, data processing procedure and methods of UAV remote sensing monitoring of crop diseases and insect pests, etc.; also point out the main problems of pest and disease feature selection, pest and disease classification identification, sensor optimization and data processing in UAV remote sensing monitoring of crop pests and diseases. In view of the existing problems, this paper puts forward an algorithm to deepen the selection of pest and disease characteristics, establishes an exclusive pest and disease spectrum database, develops a dedicated pest and disease monitoring sensor, and develops a platform for processing pest, in order to provide a reference for the research related to UAV remote sensing monitoring of crop pests and diseases.

Key words: crops; pests and diseases; unmanned aerial vehicle; remote sensing; monitoring method; data processing; feature extraction; artificial intelligence

宋勇,陈兵,王琼,苏维,孙乐鑫,赵静,韩焕勇,王方永. 无人机遥感监测作物病虫害研究进展[J]. 棉花学报, 2021, 33(3): 291-306.

Song Yong,Chen Bing,Wang Qiong,Su Wei,Sun Lexin,Zhao Jing,Han Huanyong,Wang Fangyong. Research advances of crop diseases and insect pests monitoring by unmanned aerial vehicle remote sensing[J]. Cotton Science, 2021, 33(3): 291-306.

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链接本文: http://journal.cricaas.com.cn/Jweb_mhxb/CN/10.11963/1002-7807.sycb.20210429

http://journal.cricaas.com.cn/Jweb_mhxb/CN/Y2021/V33/I3/291

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传感器 Sensor type	波长范围/nm Wavelength range/nm	优点 Advantages	缺点 Disadvantages	文献编号 Reference number
多光谱仪 Multi-spectral sensor	390~3 000	波段多、信息量大、成本低、类型多样化等 Multiple bands, large amount of information, low cost, diversified camera types, etc.	波段易饱和、成像速度慢和图像质量差等 Band saturation, slow imaging speed and poor image quality, etc.	[28,30]
高光谱仪 Hyper-spectral sensor	10~5 000	光谱信息量丰富、分辨率高、准确度高等 Rich in spectral information, high resolution and high accuracy, etc.	价格较昂贵等 More expensive, etc.	[18,23]
数码相机 Digital camera	390~770	使用方便、成本低、类型多样化等 Easy to use, low cost, diversified camera types, etc.	信息量少、分辨率低,波段少等 Less information, low resolution, few bands, etc.	[26]
红外热成像仪 Infrared thermal imaging sensor	3 000~18 000	对目标物温湿度敏感、便于监测作物蒸腾及旱情等 Sensitive to target temperature and humidity, easy to monitor crop transpiration and drought, etc.	图像分辨率低、信噪比低,受外界环境因素干扰大等 Low image resolution, low signal-to- noise ratio, and interference from external environmental factors, etc.	[44-45]
激光雷达 Light detection and ranging sensor	10⁶~10¹⁰	获取作物冠层点云信息、作物水平和垂直冠层结构参数反演等 Obtain point cloud information of crop canopy, inversion of crop horizontal and vertical canopy structure parameters, etc.	价格昂贵、数据处理量大等 High price and large amount of data processing, etc.	[46]

传感器 Sensor type	电磁波类型 Type of electromagnetic wave	测量指标 Measurement index standard	应用领域 Application fields
多光谱仪 Multi-spectral sensor	可见光、红边、近红外光 Visible light, red edge, near infrared light	覆盖度、叶面积、氮素营养、生物量等 Coverage, leaf area, nitrogen nutrition, biomass, etc.	病虫害监测、作物分类、UAV 应用、作物图谱等 Disease and pest monitoring, crop classification, UAV application, crop map, etc.
高光谱仪 Hyper-spectral sensor	可见光、近红外光、中红外光 Visible light, near infrared light, mid-infrared	覆盖度、叶面积、生物量、产量等 Coverage, leaf area, crop biomass, crop biomass, etc.	病虫害监测、作物分类、UAV 应用、作物图谱等 Disease and pest monitoring, crop classification, UAV application, crop map, etc.
红外热成像仪 Infrared thermal imaging	红外光 Infrared light	气孔导度、水分胁迫等 Stomatal conductance, water stress, etc.	作物冠层温度、蒸腾、旱情、病虫害监测等 Crop canopy temperature, transpiration, drought, disease and pest monitoring, etc.
数码相机 Digital camera	红光、绿光、蓝光 Red light, green light, blue-ray	覆盖度、倒伏等 Crop coverage, crop lodging, etc.	农业、地理测绘、拍照等 Agriculture, geographic mapping, take pictures, etc.
激光雷达 Light detection and ranging sensor	脉冲电磁波 Pulsed electromagnetic wave	作物株高、生物量、叶面积等Crop height, crop biomass, leaf area, etc.	农作物分类、估产、参数反演等 Crop classification, yield estimation, inversion of growth parameters, etc.

机型Drone type	优点Advantages	缺点Disadvantages
固定翼无人机 Fixed-wing drone	巡航面积大;速度快;飞行高度高等 Large cruising area, fast speed, high flying altitude, etc.	不能悬停获取影像;飞行灵活度低;操作难度大;风险高;成本高等 Unable to hover to obtain continuous images, low flight flexibility, difficult to operate, high risk, high cost, etc.
混合翼无人机 Hybrid wing drone	良好的可操作性;稳定性高;可随意降落等 Good maneuverability, high stability, free landing, etc.	飞行速度低;到达指定地点慢;价格昂贵等 Low flying speed, slow to reach the designated location, expensive, etc.
无人直升机 Unmanned Helicopter	可靠性高;可低空、低速飞行等 High reliability, low altitude and low speed, etc.	振动、噪声高;维护检修工作量较大;成本高,速度较低;航程短等 High vibration and noise, heavy maintenance and repair work, high cost and low speed, short voyage, etc.
多旋翼无人机 Multi-rotor drone	种类多;可操控性强、可靠性高;勤务性高;安全系数高等 Wide variety, strong maneuverability, high reliability, high serviceability, high safety factor, etc.	成本高;灵活性不高等 High cost, low flexibility, etc.