以内蒙古锡林河流域典型草原为研究对象,在群落调查和光谱观测数据的基础上,引入主成分分析方法(PCA)研究了与草场健康有关的各生物参数间关系,提出一种草场健康状况监测的新方法:(1)从包含12个反映群落各方面信息的变量中提取出3个有特定生态学意义的主成分,并进一步对其进行分析组合,得出一个能比较敏感、全面反映群落健康状况的新指标—草场健康指数(GHI);其意义在于:它不仅可以反映草场的生物量信息,而且可以反映群落的结构组成信息。(2)从6波段的植被光谱反射数据中提取出2个主成分:可见光因子和红外光因子,它们可以较好反映植被信息。(3)表征群落总量、放牧退化的主成分和GHI与植被光谱反射值有相当的相关性,由此得到GHI与可见光、红外光因子的回归模型。此模型可利用植被光谱较好地反映草场健康状况。

A method to monitor grassland vegetation health was used in this study.The relations of grassland bio-parameters related with grassland health were analyzed by Principal Component Analysis(PCA) on the basis of combining community survey and vegetation spectrum in Xilin River basin,Inner Mongolia.1.Three specific Principal Components(PCs) with specific ecological meaning were extracted from a 12-variables data set that contains community information using principal component analysis(PCA).Based on the three PCs,we proposed a new index-GHI,which is proved to be qualified for monitoring grassland vegetation health condition,and sensitive to degradation.2.We extracted two PCs: visible light component and infrared light component from 6-band vegetation spectral reflection data.3.We got the regression models of GHI and visible light/infrared light,based on the PCs correlated to plot spectral reflection and GHI,which indicate community gross and grazing degradation.The model can be used to monitor grassland health condition by vegetation spectrum.