农业无人机高光谱成像遥感研究现状和进展

Research on the current and progress of hyperspectral imaging remote sensing for UAVs on agriculture

关键词:  无人机  遥感  高光谱成像  精准农业

Key words:  Unmanned Aerial Vehicle (UAV)  Remote sensing  Hyperspectral imaging  Precision agriculture

摘要:

【目的】随着计算机、无人机、光谱技术和遥感技术的迅速进步，无人机高光谱成像遥感在精准农业中的应用潜力巨大，已成为推动精准农业发展的重要方向之一。利用无人机搭载高光谱成像仪进行农作物信息监测，不仅在技术发展和应用上具有重要意义，还为大面积精准农业生产管理提供了科学的决策依据。与传统监测手段相比，高光谱成像仪具有高分辨率和多光谱带的优势，能够提供更为详细准确的数据支持。【方法】文章综述了无人机高光谱遥感系统及其在农业领域的应用现状和发展趋势。【结果】介绍了常见的无人机平台和机载高光谱成像仪。详细探讨了该技术在农作物产量测定、长势诊断、病虫害监测和作物识别等方面的应用实例，并简要介绍了高光谱遥感图像信息处理的步骤和方法，以及图像处理过程中面临的主要问题。最后，该文提出了该技术在农业领域应用中存在的问题和未来的发展方向。【结论】通过技术创新和应用实践，无人机高光谱成像遥感技术将在农业领域发挥更大的作用，为精准农业的发展提供强有力的支持。这将有助于实现更高效的农业生产管理，提高作物产量和品质，促进农业的可持续发展。

Abstract:

［Purpose］With the rapid advancements in computer technology, drones, spectral technology, and remote sensing, UAV-based hyperspectral imaging has demonstrated significant potential in precision agriculture, emerging as a crucial direction for its advancement. The deployment of drones equipped with hyperspectral imagers for crop monitoring is essential for both technological innovation and practical application, providing a scientific foundation for large-scale precision agricultural production management. This sophisticated technology supports the development of precision agriculture by enabling more accurate and detailed monitoring of crop health, soil conditions, and environmental factors. The enhanced data obtained through hyperspectral imaging allows for the precise application of inputs such as water, fertilizers, and pesticides, optimizing their use and reducing waste. UAV hyperspectral imagers capture detailed information on crop growth status, pest infestations, and nutritional needs, thereby aiding farmers and agricultural managers in precise crop management. By capturing the spectral data reflected by plants, this technology analyzes crop health and identifies issues such as diseases and nutritional deficiencies. Compared to traditional monitoring methods, hyperspectral imagers offer high resolution and multiple spectral bands, providing more detailed and accurate data.One of the key advantages of UAV-based hyperspectral imaging is its ability to detect subtle differences in crop conditions that are not visible to the naked eye or detectable by conventional sensors. This capability allows for the early identification of variations in plant health due to nutrient deficiencies or the onset of diseases, enabling timely and targeted interventions. Moreover, the flexibility and mobility of UAVs allow for frequent and extensive monitoring of large agricultural areas, providing real-time data that supports dynamic decision-making. This is particularly beneficial for precision agriculture, where timely and accurate information is critical for optimizing inputs such as water, fertilizers, and pesticides, ultimately enhancing crop yield and quality while reducing environmental impact.［Method］This paper reviews the current research status and development trends of UAV hyperspectral remote sensing systems and their applications in the agricultural field. ［Result］It introduces common UAV platforms and airborne hyperspectral imagers available on the market and discusses their application examples in crop yield deter mination, growth diagnosis, pest and disease monitoring, and crop identification. Additionally, it briefly outlines the steps and methods involved in hyperspectral remote sensing image information processing and addresses the main challenges in the image processing workflow.Finally, this paper highlights the existing challenges and future development directions for the application of this technology in agriculture, providing a reference for the future development of agricultural UAV hyperspectral imaging remote sensing technology.［Conclusion］Through continuous technological innovation and practical application, UAV hyperspectral imaging remote sensing technology is poised to play an increasingly significant role in agriculture. It will provide robust support for precision agriculture, helping achieve more efficient agricultural production management, improving crop yield and quality, and promoting sustainable agricultural practices. The future development of this technology promises to transform agricultural monitoring and management, making far ming more precise, efficient, and sustainable.