摘 要
森林病虫害是威胁全球森林生态系统健康和可持续发展的重要因素，传统监测手段存在效率低、覆盖范围有限等问题。本研究旨在利用无人机技术构建高效、精准的森林病虫害监测系统，以提升监测能力和响应速度。研究采用搭载多光谱与高分辨率可见光传感器的无人机平台，结合图像处理算法和机器学习模型，实现了对森林病虫害的自动化识别与评估。通过设计针对性的数据采集方案和优化飞行路径规划，显著提高了数据获取的效率和质量。实验结果表明，该系统能够准确检测多种典型病虫害类型，其精度达到92%以上，并能快速生成病虫害分布图，为林业管理部门提供科学决策依据。本研究的主要创新点在于将多源遥感数据融合与智能分析技术相结合，突破了传统方法的空间限制，同时降低了人力成本。研究成果为森林资源保护提供了新的技术手段，具有重要的应用价值和推广前景。
关键词：森林病虫害监测; 无人机技术; 多光谱传感器; 机器学习; 遥感数据融合
Abstract
Forest pests and diseases are significant factors threatening the health and sustainable development of global forest ecosystems, while traditional monitoring methods suffer from low efficiency and limited coverage. This study aims to construct an efficient and precise forest pest and disease monitoring system by utilizing unmanned aerial vehicle (UAV) technology, thereby enhancing monitoring capabilities and response speed. A UAV platform equipped with multispectral and high-resolution visible light sensors was employed, combined with image processing algorithms and machine learning models, to achieve automated identification and assessment of forest pests and diseases. By designing targeted data acquisition schemes and optimizing flight path planning, the efficiency and quality of data collection were significantly improved. Experimental results indicate that the system can accurately detect multiple typical types of forest pests and diseases, achieving a precision rate of over 92%, and can rapidly generate pest and disease distribution maps, providing scientific decision-making support for forestry management departments. The primary innovation of this study lies in the integration of multi-source remote sensing data fusion and intelligent analytical techniques, which overcome spatial limitations of traditional methods while reducing labor costs. The research findings offer new technical approaches for forest resource protection, demonstrating important application value and broad prospects for promotion.
Key words:Forest Pest Monitoring; Unmanned Aerial Vehicle Technology; Multispectral Sensor; Machine Learning; Remote Sensing Data Fusion
目 录
中文摘要 I
英文摘要 II
引 言 1
第1章、无人机技术在森林监测中的应用基础 2
1.1、无人机技术发展现状 2
1.2、森林监测的技术需求 2
1.3、无人机技术的优势分析 2
第2章、森林病虫害监测系统设计框架 4
2.1、系统总体架构设计 4
2.2、数据采集与传输机制 4
2.3、图像处理与分析方法 4
第3章、关键技术实现与优化策略 6
3.1、高精度定位技术研究 6
3.2、多源数据融合算法 6
3.3、实时监测与预警机制 7
第4章、系统测试与实际应用案例分析 8
4.1、测试环境与评估标准 8
4.2、应用案例分析与效果评价 8
4.3、系统改进与未来展望 9
结 论 10
参考文献 11
森林病虫害是威胁全球森林生态系统健康和可持续发展的重要因素，传统监测手段存在效率低、覆盖范围有限等问题。本研究旨在利用无人机技术构建高效、精准的森林病虫害监测系统，以提升监测能力和响应速度。研究采用搭载多光谱与高分辨率可见光传感器的无人机平台，结合图像处理算法和机器学习模型，实现了对森林病虫害的自动化识别与评估。通过设计针对性的数据采集方案和优化飞行路径规划，显著提高了数据获取的效率和质量。实验结果表明，该系统能够准确检测多种典型病虫害类型，其精度达到92%以上，并能快速生成病虫害分布图，为林业管理部门提供科学决策依据。本研究的主要创新点在于将多源遥感数据融合与智能分析技术相结合，突破了传统方法的空间限制，同时降低了人力成本。研究成果为森林资源保护提供了新的技术手段，具有重要的应用价值和推广前景。
关键词：森林病虫害监测; 无人机技术; 多光谱传感器; 机器学习; 遥感数据融合
Abstract
Forest pests and diseases are significant factors threatening the health and sustainable development of global forest ecosystems, while traditional monitoring methods suffer from low efficiency and limited coverage. This study aims to construct an efficient and precise forest pest and disease monitoring system by utilizing unmanned aerial vehicle (UAV) technology, thereby enhancing monitoring capabilities and response speed. A UAV platform equipped with multispectral and high-resolution visible light sensors was employed, combined with image processing algorithms and machine learning models, to achieve automated identification and assessment of forest pests and diseases. By designing targeted data acquisition schemes and optimizing flight path planning, the efficiency and quality of data collection were significantly improved. Experimental results indicate that the system can accurately detect multiple typical types of forest pests and diseases, achieving a precision rate of over 92%, and can rapidly generate pest and disease distribution maps, providing scientific decision-making support for forestry management departments. The primary innovation of this study lies in the integration of multi-source remote sensing data fusion and intelligent analytical techniques, which overcome spatial limitations of traditional methods while reducing labor costs. The research findings offer new technical approaches for forest resource protection, demonstrating important application value and broad prospects for promotion.
Key words:Forest Pest Monitoring; Unmanned Aerial Vehicle Technology; Multispectral Sensor; Machine Learning; Remote Sensing Data Fusion
目 录
中文摘要 I
英文摘要 II
引 言 1
第1章、无人机技术在森林监测中的应用基础 2
1.1、无人机技术发展现状 2
1.2、森林监测的技术需求 2
1.3、无人机技术的优势分析 2
第2章、森林病虫害监测系统设计框架 4
2.1、系统总体架构设计 4
2.2、数据采集与传输机制 4
2.3、图像处理与分析方法 4
第3章、关键技术实现与优化策略 6
3.1、高精度定位技术研究 6
3.2、多源数据融合算法 6
3.3、实时监测与预警机制 7
第4章、系统测试与实际应用案例分析 8
4.1、测试环境与评估标准 8
4.2、应用案例分析与效果评价 8
4.3、系统改进与未来展望 9
结 论 10
参考文献 11
