南方湿润地区植被叶面积指数快速遥感反演模型
A Fast Remote Sensing Inversion Model for Vegetation Leaf Area Index in Hu-mid Areas, South China
DOI: 10.12677/WJF.2022.114023, PDF,   
作者: 张丹丹：韶关宏大勘测规划设计有限公司，广东 韶关；张志新：水利部信息中心，北京；田 程：核工业230研究所，湖南 长沙
关键词: 植被；叶面积指数；遥感反演模型；植被覆盖度；南方湿润地区； Vegetation； Leaf Area Index； Remote Sensing Inversion Model； Vegetation Coverage； Humid Areas of South China
摘要: 植被是城市生态系统的重要组成部分，叶面积指数(LAI)是表征植被冠层结构的最基本的植被生物物理参量。本文应用WinScanopy林地冠层分析仪(具有180˚鱼眼镜头)对广东省多个地面点进行植被参数测量并建立快速遥感反演模型，结果表明植被叶面积指数(LAI)与植被覆盖度的关系为LAI = −1.3206 ln(1 − Av) − 0.0206，拟合优度R2高达0.933。这可为我国南方湿润地区叶面积指数(LAI)遥感监测业务化提供有力的理论与技术支撑。
Abstract: Vegetation is an important part of urban ecosystem, and leaf area index (LAI) is the most basic vegetation biophysical parameter to characterize vegeta-tion canopy structure. In this paper, a WinScanopy forest canopy analyzer (with 180˚ fish eye lens) was used to measure vegetation parameters at several ground points in Guangdong Province, and a fast remote sensing inversion model was established. The results showed that the relationship be-tween vegetation leaf area index (LAI) and vegetation coverage was LAI = −1.3206 ln(1 − Av) − 0.0206, and The goodness of fit R2 is as high as 0.933. This can provide strong theoretical and tech-nical support for the commercialization of leaf area index (LAI) remote sensing monitoring in the humid areas of South China.
文章引用：张丹丹, 张志新, 田程. 南方湿润地区植被叶面积指数快速遥感反演模型[J]. 林业世界, 2022, 11(4): 188-192. https://doi.org/10.12677/WJF.2022.114023

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