基于流形学习的阔叶树叶面积指数的研究

Study of Broad-leaved Trees LAI Based on Mani-fold Learning

叶面积指数(LAI)是一个量化植物绿色指数的重要参数之一。精确测量叶面积指数对研究生态系统的功能结构特性具有重要的意义。植物生存环境影响植物叶子的形态,叶舒展、卷曲、病虫害引起缺损等几何形态的变化,对于测量带来很大不便。本论文鉴于在传统的叶面积指数的测量方法存在许多弊端,借助于流形学习方法,将三维数据降为二维数据,在二维空间进行数据的精确测量,得到相当准确的叶面积指数,从而获得植物精确的参数有了一定科学依据。

Leaf area index（ LAI） is one of the important parameters for green rating. The precise measurement of LAI has great significance to study the functional structure characteristics of ecosystems. The living environment can affect the form of leafs and the leaf stretch,curly,plant diseases and insect pests also cause the change of leaf form,which is not convenient to the measurement of leafs. In this paper,in consideration of the drawbacks of traditional measurement methods of leaf area index,the mani-fold learning method was used to reduce the three-dimensional data to two-dimensional data and realize precise measurement. In this way,a fairly accurate LAI can be obtained,which provides scientific basis for the accurate measurement of the parameter.