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监测地表植被的雷达植被指数:发展,挑战和趋势

Xueqian Hu¹, Li Li¹, Jianxi Huang¹

¹College of Land Science and Technology, China Agricultural University, Beijing 100083, China; Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture and Rural Affairs, Beijing 100083, China.

The Science of the total environment

|June 19, 2024

概括

雷达植被指数 (RVI) 为监测表面植被,克服天气和照明限制的光学方法提供了强大的替代方案. 本综述系统地分析了RVI,指导其环境和生态系统研究的应用和未来发展.

科学领域:

环境科学环境科学
遥感技术遥感技术遥感技术
林业和生态林业和生态

背景情况:

由于照明和天气条件,光学遥感方法在地表植被监测方面存在局限性.
雷达植被指数 (RVI) 使用微波数据来评估植被特性,为一致的监测提供了替代方案.
在环境保护,灾害预防和碳捕获评估方面,RVI至关重要.

研究的目的:

系统地审查和总结雷达植被指数 (RVI).
分析RVI的原则,发展,类别和应用.
为RVI利用提供全面指南,并预测未来的趋势.

主要方法:

系统的文献审查和对现有的雷达植被指数的分析.
讨论RVI原则,发展,分类和应用范围.
对RVI的挑战,适用性和未来趋势的分析.

主要成果:

RVI对于各种尺度的植被监测是有效的,描述介电性质和形态.
选择合适的RVI取决于数据类型,地形,位置和植被类型.
诸如指数性能,传感器和数据质量等因素影响RVI的有效性.

结论:

RVIs提供了一种可靠的表面植被监测方法,补充了光学方法.
人工智能和高分辨率SAR技术的未来进步将增强RVI的能力.
对陆地生态系统研究和环境管理来说,RVI至关重要.

关键词:

背向散射系数是指背向散射的系数.生态监测生态监测微波电波公司的微波.两极化分解的分解雷达植被指数雷达植被指数

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