Xiao Han, Chen Xiu-Wan, Yang Zhen-Yu, Li Huai-Yu, Zhu Han
Guang Pu Xue Yu Guang Pu Fen Xi. 2014 Nov;34(11):3075-8.
Comparing the methods of existing remote sensing research on the estimation of chlorophyll content, the present paper confirms that the vegetation index is one of the most practical and popular research methods. In recent years, the increasingly serious problem of grassland degradation. This paper, firstly, analyzes the measured reflectance spectral curve and its first derivative curve in the grasslands of Songpan, Sichuan and Gongger, Inner Mongolia, conducts correlation analysis between these two spectral curves and chlorophyll content, and finds out the regulation between REP (red edge position) and grassland chlorophyll content, that is, the higher the chlorophyll content is, the higher the REIP (red-edge inflection point) value would be. Then, this paper constructs GCI (grassland chlorophyll index) and selects the most suitable band for retrieval. Finally, this paper calculates the GCI by the use of satellite hyperspectral image, conducts the verification and accuracy analysis of the calculation results compared with chlorophyll content data collected from field of twice experiments. The result shows that for grassland chlorophyll content, GCI has stronger sensitivity than other indices of chlorophyll, and has higher estimation accuracy. GCI is the first proposed to estimate the grassland chlorophyll content, and has wide application potential for the remote sensing retrieval of grassland chlorophyll content. In addition, the grassland chlorophyll content estimation method based on remote sensing retrieval in this paper provides new research ideas for other vegetation biochemical parameters' estimation, vegetation growth status' evaluation and grassland ecological environment change's monitoring.
对比现有遥感研究中估算叶绿素含量的方法，本文证实植被指数是最实用且最受欢迎的研究方法之一。近年来，草地退化问题日益严重。本文首先分析了四川松潘和内蒙古贡格尔草原实测的反射光谱曲线及其一阶导数曲线，对这两条光谱曲线与叶绿素含量进行相关性分析，找出红边位置（REP）与草地叶绿素含量之间的规律，即叶绿素含量越高，红边拐点位置（REIP）值越高。然后，本文构建了草地叶绿素指数（GCI）并选择最适合反演的波段。最后，利用卫星高光谱影像计算GCI，并将计算结果与两次实地实验采集的叶绿素含量数据进行对比验证及精度分析。结果表明，对于草地叶绿素含量，GCI比其他叶绿素指数具有更强的敏感性，且估算精度更高。GCI是首次提出用于估算草地叶绿素含量的，在草地叶绿素含量的遥感反演方面具有广阔的应用潜力。此外，本文基于遥感反演的草地叶绿素含量估算方法为其他植被生化参数估算、植被生长状况评价及草地生态环境变化监测提供了新的研究思路。
