%0 Journal Article
%T 南方湿润地区植被叶面积指数快速遥感反演模型<br> A Fast Remote Sensing Inversion Model for Vegetation Leaf Area Index in Hu-mid Areas, South China
%A 张丹丹
%A 张志新
%A 田程
%J World Journal of Forestry
%P 188-192
%@ 2169-2440
%D 2022
%I Hans Publishing
%R 10.12677/WJF.2022.114023
%X 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 ？ A<sub>v</sub>) ？ 0.0206，拟合优度R<sup>2</sup>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。<br />
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 ？ A<sub>v</sub>) ？ 0.0206, and The goodness of fit R<sup>2</sup> 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.
%K 植被，叶面积指数，遥感反演模型，植被覆盖度，南方湿润地区<br> Vegetation
%K Leaf Area Index
%K Remote Sensing Inversion Model
%K Vegetation Coverage
%K Humid Areas of South China
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=56581