以长白山牡丹岭典型阔叶木本植被为研究对象, 通过冠层高光谱和微分光谱数据确定叶变色期, 利用红边参数建立光谱与叶变色期的反演模型.研究结果表明：冠层高光谱反射比曲线可以准确反映植被秋季叶变色期的变化, 并表现为三种基本类型：叶开始变色期——叶全部变色期——干枯但不落叶, 叶开始变色期——部分变黄并开始落叶——未完全变黄但落叶结束, 叶开始变色期——叶全部变色期——落叶; 一阶微分光谱曲线与高光谱曲线线能够更清晰的显示出叶开始变色期和叶完全变色期的具体日期; 建立红边参数—叶变色期的反演模型, R2均在0.9以上, 且不同植被适合不同形式的拟合方程.对利用遥感方法定量监测山地秋季物候具有重要理论意义和广泛应用前景.

Based on the canopy hyperspectra and derivative spectra of typical hardwoods in Mudan valley, Changbai Mountain, red edge characteristics were used to determine leaf coloring date and to establish regression models of spectra and leaf coloring date. The results show that the canopy hyperspectral reflectance can accurately reflect the change of vegetation autumn leaf coloring date. The states of the leaves of typical hardwoods can be divided into three categories: the dry leaves not falling after leaf coloring date, the leaves falling out before leave full coloring date, and the leaves falling after leaf full coloring date. The first derivative spectral curves and hyperspectral curves take clear advantage over the specific date of leaf first coloring date and leaf full coloring date. The variances of inversion models of red edge parameters and leaf coloring date are all above 0.9, and each vegetation is suitable for different forms of fitting equation. The research shows important theoretical significance and extensive application prospect on using quantitative remote sensing to monitor mountain autumn phenology.