摘 要
森林病虫害是全球生态系统中威胁森林健康的重要因素，其动态变化的监测对森林资源保护和可持续管理具有重要意义。本研究旨在利用遥感技术实现对森林病虫害动态变化的高效监测，以克服传统地面调查方法效率低、覆盖范围有限的问题。研究采用多源遥感数据，结合机器学习算法和时间序列分析方法，构建了一套适用于大尺度森林病虫害监测的技术框架。通过对比分析不同波段和指数的敏感性，选取最佳特征组合用于病虫害识别，并验证了模型在多种森林类型中的适用性。结果表明，该方法能够以较高的精度捕捉病虫害的空间分布及时间演变特征，尤其在早期预警方面表现出显著优势。本研究的主要创新点在于将高分辨率遥感影像与长时间序列数据相结合，实现了病虫害动态变化的精细化监测，为森林资源管理和生态安全评估提供了科学依据和技术支持。
关键词：森林病虫害; 遥感技术; 机器学习; 时间序列分析; 早期预警
Abstract
Forest pests and diseases are significant threats to forest health in global ecosystems, and monitoring their dynamic changes is crucial for the protection and sustainable management of forest resources. This study aims to utilize remote sensing technology for efficient monitoring of forest pest and disease dynamics, addressing the limitations of traditional ground survey methods, such as low efficiency and limited coverage. By employing multi-source remote sensing data integrated with machine learning algorithms and time series analysis, a technical fr amework was developed for large-scale monitoring of forest pests and diseases. Through comparative sensitivity analyses of different bands and indices, an optimal feature combination was selected for pest and disease identification, and the model's applicability across various forest types was validated. The results demonstrate that this method can accurately capture the spatial distribution and temporal evolution characteristics of forest pests and diseases, showing particular advantages in early warning systems. A key innovation of this study lies in combining high-resolution remote sensing images with long-time-series data to achieve refined monitoring of pest and disease dynamics, providing scientific evidence and technical support for forest resource management and ecological security assessment.
Key words:Forest Pest And Disease; Remote Sensing Technology; Machine Learning; Time Series Analysis; Early Warning
目 录
中文摘要 I
英文摘要 II
引 言 1
第1章、遥感技术基础与应用 3
1.1、遥感技术原理概述 3
1.2、森林监测中的遥感应用 3
1.3、遥感数据获取与处理方法 4
第2章、森林病虫害特征分析 5
2.1、病虫害对森林的影响机制 5
2.2、病虫害的光谱响应特性 5
2.3、不同类型病虫害的识别标志 6
第3章、遥感监测技术实现路径 7
3.1、数据采集与预处理流程 7
3.2、图像分类与变化检测方法 7
3.3、监测模型的构建与优化 8
第4章、动态变化评估与案例研究 9
4.1、时间序列分析方法 9
4.2、典型区域的动态变化监测 9
4.3、结果验证与误差分析 9
结 论 11
参考文献 12
森林病虫害是全球生态系统中威胁森林健康的重要因素，其动态变化的监测对森林资源保护和可持续管理具有重要意义。本研究旨在利用遥感技术实现对森林病虫害动态变化的高效监测，以克服传统地面调查方法效率低、覆盖范围有限的问题。研究采用多源遥感数据，结合机器学习算法和时间序列分析方法，构建了一套适用于大尺度森林病虫害监测的技术框架。通过对比分析不同波段和指数的敏感性，选取最佳特征组合用于病虫害识别，并验证了模型在多种森林类型中的适用性。结果表明，该方法能够以较高的精度捕捉病虫害的空间分布及时间演变特征，尤其在早期预警方面表现出显著优势。本研究的主要创新点在于将高分辨率遥感影像与长时间序列数据相结合，实现了病虫害动态变化的精细化监测，为森林资源管理和生态安全评估提供了科学依据和技术支持。
关键词：森林病虫害; 遥感技术; 机器学习; 时间序列分析; 早期预警
Abstract
Forest pests and diseases are significant threats to forest health in global ecosystems, and monitoring their dynamic changes is crucial for the protection and sustainable management of forest resources. This study aims to utilize remote sensing technology for efficient monitoring of forest pest and disease dynamics, addressing the limitations of traditional ground survey methods, such as low efficiency and limited coverage. By employing multi-source remote sensing data integrated with machine learning algorithms and time series analysis, a technical fr amework was developed for large-scale monitoring of forest pests and diseases. Through comparative sensitivity analyses of different bands and indices, an optimal feature combination was selected for pest and disease identification, and the model's applicability across various forest types was validated. The results demonstrate that this method can accurately capture the spatial distribution and temporal evolution characteristics of forest pests and diseases, showing particular advantages in early warning systems. A key innovation of this study lies in combining high-resolution remote sensing images with long-time-series data to achieve refined monitoring of pest and disease dynamics, providing scientific evidence and technical support for forest resource management and ecological security assessment.
Key words:Forest Pest And Disease; Remote Sensing Technology; Machine Learning; Time Series Analysis; Early Warning
目 录
中文摘要 I
英文摘要 II
引 言 1
第1章、遥感技术基础与应用 3
1.1、遥感技术原理概述 3
1.2、森林监测中的遥感应用 3
1.3、遥感数据获取与处理方法 4
第2章、森林病虫害特征分析 5
2.1、病虫害对森林的影响机制 5
2.2、病虫害的光谱响应特性 5
2.3、不同类型病虫害的识别标志 6
第3章、遥感监测技术实现路径 7
3.1、数据采集与预处理流程 7
3.2、图像分类与变化检测方法 7
3.3、监测模型的构建与优化 8
第4章、动态变化评估与案例研究 9
4.1、时间序列分析方法 9
4.2、典型区域的动态变化监测 9
4.3、结果验证与误差分析 9
结 论 11
参考文献 12
