农作物病虫害遥感监测关键技术研究进展与展望

病虫害是影响农作物健康生长、产量和质量的制约因素之一,加强农作物病虫害的监测,对农作物病虫害进行精准防控,对保障粮食安全,提高农产品产量和质量具有重要意义。随着信息技术的发展,农作物病虫害监测由传统的人工监测逐渐向自动化、信息化和智能化方向发展。农作物病虫害监测平台、监测传感器技术以及相关的数据分析和处理技术是研究农作物病虫害遥感监测的关键技术,这些关键技术的发展水平,决定了农作物病虫害遥感监测技术的发展水平。本文从监测平台、监测传感器技术和相关数据分析与处理技术3方面对农作物病虫害监测技术研究进展进行综述。在监测平台方面,归纳总结了地面监测平台、航空监测平台和卫星监测平台的国内外研究现状,并分析了上述平台优缺点;在监测传感器技术方面,综述了雷达传感器、图像传感器、热成像传感器和光谱传感器等在作物病虫害领域的研究进展;在相关数据分析与处理技术方面,阐述了经典统计算法、计算机图像处理算法、机器学习算法和深度学习算法在农作物病虫害监测领域的研究成果。最后提出了监测平台、监测传感器技术和相关数据分析与处理技术的未来发展趋势,以期为进一步促进我国农作物病虫害监测平台及相关技术的发展提供参考。

Research Progress and Prospect of Key Technologies in Crop Disease and Insect Pest Monitoring

Diseases and insect pest are the most restricting factors affecting the crop health, the improvement of the crop yield and quality. It is of great significant to strengthen the development of crop disease and insect pest monitoring. Therefore, to undertake the precise prevent and control on the crop disease and insect pest is key for ensuring the food safety, and improve the yield and quality of crop. The traditional disease and insect pest monitoring mainly relies on the manual field investigation, with low efficiency and quality, which can no longer meet the needs of efficient, intelligent and professional modern agriculture. With the development of information technology, the monitoring of crop diseases and insect pest has gradually developed from the traditional manual monitoring to remote sensing monitoring. Crop monitoring platform, monitoring sensor technology, data analysis and processing technology are key technologies for the development of remote sensing monitoring of crop diseases and insect pest. The development of the above technologies determined the development of remote sensing monitoring technology of crop disease and insect pest. The research progress of monitoring platform, monitoring sensor technology, data analysis and processing technology for crop disease and insect pests were summarized. In terms of monitoring platform, the research status of ground machinery platform, aircraft platform, and satellite platform was summarized. In the monitoring sensor technology, the research progress of radar sensor, image sensor, thermal imaging sensor and spectral sensor for crop diseases and pests monitoring was summarized. In data analysis and processing technology, the research achievements of classical statistical algorithms, computer image processing algorithms, machine learning algorithms and deep learning algorithms in crop diseases and insect pests monitoring were expounded. Furthermore, recommendations were proposed for further promoting the development of crop diseases and insect pests monitoring, including building multi-scale integrated application monitoring platform, promoting the development of multi-scale data fusion sensor, and continuous optimizing multidisciplinary theory and algorithm structure research.