摘 要
随着全球生态环境问题日益严峻，遥感技术在生态环境监测中的应用受到广泛关注。本研究旨在结合无人机遥感与卫星遥感的优势，构建一种多尺度、高精度的生态环境监测方法，以弥补单一遥感手段在空间分辨率、时间分辨率和覆盖范围上的不足。研究通过整合高分辨率无人机影像与大范围覆盖的卫星遥感数据，提出了一种基于数据融合与机器学习的综合分析框架。该框架首先利用无人机遥感获取局部区域的高精度生态参数，随后结合卫星遥感数据进行区域扩展，并通过深度学习算法实现地表覆盖分类与变化检测。实验结果表明，无人机与卫星遥感数据的融合显著提高了监测精度，尤其是在植被健康评估、土地利用动态监测及灾害影响评价等方面表现出优异性能。本研究的创新点在于提出了一个多源遥感协同监测体系，不仅提升了数据的空间分辨率和时间连续性，还为复杂生态环境的精细化管理提供了技术支持。此外，研究开发的自动化处理流程大幅降低了数据分析的人力成本，增强了方法的可操作性。总体而言，本研究为生态环境监测提供了一种高效、灵活的技术路径，对推动遥感技术在生态保护与可持续发展中的应用具有重要意义。
关键词：无人机遥感；卫星遥感；数据融合
ABSTRACT
With the increasing severity of global ecological and environmental issues, the application of remote sensing technology in ecological and environmental monitoring has attracted extensive attention. This study aims to integrate the advantages of unmanned aerial vehicle (UAV) remote sensing and satellite remote sensing to develop a multi-scale, high-precision method for ecological and environmental monitoring, addressing the limitations of single remote sensing approaches in spatial resolution, temporal resolution, and coverage extent. By combining high-resolution UAV imagery with satellite remote sensing data that provide broad-area coverage, a comprehensive analytical fr amework based on data fusion and machine learning is proposed. This fr amework first acquires high-accuracy ecological parameters for local regions using UAV remote sensing, then extends these findings to larger areas by integrating satellite remote sensing data, and finally applies deep learning algorithms for land cover classification and change detection. Experimental results demonstrate that the fusion of UAV and satellite remote sensing data significantly enhances monitoring accuracy, particularly in vegetation health assessment, dynamic land use monitoring, and disaster impact evaluation. The innovation of this study lies in the development of a multi-source remote sensing collaborative monitoring system, which not only improves the spatial resolution and temporal continuity of data but also provides technical support for the refined management of complex ecological environments. Additionally, the automated processing workflow developed in this study substantially reduces the labor costs associated with data analysis and enhances the operability of the method. Overall, this research offers an efficient and flexible technical approach for ecological and environmental monitoring, contributing significantly to the promotion of remote sensing technology in ecological conservation and sustainable development.
Keywords: Unmanned Aerial Vehicle Remote Sensing; Satellite Remote Sensing; Data Fusion
目 录
摘 要 I
ABSTRACT II
第1章 绪论 1
1.1 无人机遥感与卫星遥感结合的背景 1
1.2 生态环境监测研究的意义 1
1.3 国内外研究现状分析 2
1.4 本文研究方法概述 2
第2章 无人机与卫星遥感技术基础 3
2.1 遥感技术的基本原理 3
2.2 无人机遥感的技术特点 3
2.3 卫星遥感的技术优势 4
2.4 无人机与卫星遥感的互补性分析 4
2.5 技术集成的关键问题 5
第3章 生态环境监测中的数据融合方法 6
3.1 数据融合的基本概念 6
3.2 多源遥感数据的获取与预处理 6
3.3 数据融合算法的选择与优化 7
3.4 融合数据在生态环境监测中的应用 7
3.5 数据质量评估与改进策略 8
第4章 案例分析与实践验证 9
4.1 研究区域与目标选择 9
4.2 数据采集与处理流程 9
4.3 监测结果的对比分析 10
4.4 实践中的技术难点与解决方案 10
4.5 案例研究的总结与启示 11
结论 12
参考文献 13
致 谢 14
