无人机遥感监测作物病虫害胁迫方法与最新研究进展

doi:10.12133/j.smartag.SA202201008

摘要/Abstract

摘要：

病虫害是作物生产面临的主要胁迫之一。近年来，随着无人机产业的快速发展，无人机农业遥感因其图像空间分辨率高、数据获取时效性强和成本低等特点，在作物病虫害胁迫监测应用中发挥了重要作用。本文首先介绍了利用无人机遥感监测作物病虫害胁迫的相关背景；其次对目前无人机遥感监测作物病虫害胁迫中的常用方法进行了概述，主要探讨无人机遥感监测作物病虫害胁迫的数据获取方式和数据处理方法；之后从可见光成像遥感、多光谱成像遥感、高光谱成像遥感、热红外成像遥感、激光雷达成像遥感和多遥感融合与对比六个方面重点综述了近期国内外无人机遥感监测作物病虫害胁迫的研究进展。最后提出了无人机遥感监测作物病虫害胁迫研究与应用中尚未解决的关键技术问题与未来的发展方向。本文为把握无人机遥感监测作物病虫害胁迫研究热点、应用瓶颈、发展趋势提供借鉴和参考，以期助力中国无人机遥感监测作物病虫害胁迫更加标准化、信息化、精准化和智能化。

关键词: 无人机, 遥感监测, 病虫害胁迫, 数据获取, 数据处理, 深度学习, 多遥感融合

Abstract:

Diseases and pests are main stresses to crop production. It is necessary to accurately and quickly monitor and control the stresses dynamically, so as to ensure the food security and the quality and safety of agricultural products, protect the ecological environment, and promote the sustainable development of agriculture. In recent years, with the rapid development of the unmanned aerial vehicle (UAV) industry, UAV agricultural remote sensing has played an important role in the application of crop diseases and pests monitoring due to its high image spatial resolution, strong data acquisition timeliness and low cost. The relevant background of UAV remote sensing monitoring of crop disease and pest stress was introduced, then the current methods commonly used in remote sensing monitoring of crop disease and pest stress by UAV was summarized. The data acquisition method and data processing method of UAV remote sensing monitoring of crop disease and pest stress were mainly discussed. Then, from the six aspects of visible light imaging remote sensing, multispectral imaging remote sensing, hyperspectral imaging remote sensing, thermal infrared imaging remote sensing, LiDAR imaging remote sensing and multiple remote sensing fusion and comparison, the research progress of remote sensing monitoring of crop diseases and pests by UAV worldwide was reviewed. Finally, the unresolved key technical problems and future development directions in the research and application of UAV remote sensing monitoring of crop disease and pest stress were proposed. Such as, the performance of the UAV flight platform needs to be optimized and upgraded, as well as the development of low-cost, lightweight, modular, and more adaptable airborne sensors. Convenient and automated remote sensing monitoring tasks need to be designed and implemented, and more remote sensing monitoring information can be obtained. Data processing algorithms or software should be designed and developed with greater applicability and wider applicability, and data processing time should be shortened by using 5G-based communication networks and edge computing devices. The applicability of the algorithm or model for UAV remote sensing monitoring of crop disease and pest stress needs to be stronger, so as to build a corresponding method library. We hope that this paper can help Chinese UAV remote sensing monitoring of crop diseases and pests to achieve more standardization, informatization, precision and intelligence.

Key words: unmanned aerial vehicle, remote sensing monitoring, diseases and pests stress, data acquisition, data processing, deep learning, multiple remote sensing fusion

中图分类号:

S-435

杨国峰, 何勇, 冯旭萍, 李禧尧, 张金诺, 俞泽宇. 无人机遥感监测作物病虫害胁迫方法与最新研究进展[J]. 智慧农业(中英文), 2022, 4(1): 1-16.

YANG Guofeng, HE Yong, FENG Xuping, LI Xiyao, ZHANG Jinnuo, YU Zeyu. Methods and New Research Progress of Remote Sensing Monitoring of Crop Disease and Pest Stress Using Unmanned Aerial Vehicle[J]. Smart Agriculture, 2022, 4(1): 1-16.

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