基于改进的PRI方法对植被冠层叶绿素含量的反演

叶绿素是植被光合作用的重要色素，对植被的健康状况有直接的指示作用。利用遥感技术准确、快速地获取植被叶绿素含量对精准农业具有重要意义。文章在对各种光化学植被指数（Photochemical Reflectance Index，PRI）与叶绿素含量进行敏感性分析的基础上，提取出对叶绿素变化较为敏感的组合形式，并考虑土壤背景的影响，提出了一种改进的PRI模型，同时利用在小汤山试验田获取的地面采样数据和实用模块化成像光谱仪（Operative Modular Imaging Spectrometer，OMIS）数据进行验证。结果表明，基于OMIS高光谱数据，模型能够很好地对植被冠层的叶绿素含量进行反演，反演的叶绿素含量与实测值具有较好的相关性。

Estimation of Chlorophyll Contents of Canopy with Advanced PRI Method

Chlorophyll is an important photosynthesis pigment that directly indicates vegetation’s health status. Using remote sensing technology to estimate chlorophyll content accurately and quickly is important for precision agriculture. On the basis of sensitivity analysis between various photochemical reflectance index （PRI） and chlorophyll content, by extracting more sensitive combination form to chlorophyll and considering the impact of soil background, this paper proposes an improved PRI model. The study tries to use the ground sample data acquisition and synchronization Xiaotangshan airborne hyperspectral sensors OMIS （Operative Modular Imaging Spectrometer） data for validation. The results show that based on the OMIS hyperspectral data, the model can be well used to estimate the chlorophyll contents of vegetation canopy, which have good correlation with the measured values.