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Spectral Characteristics of Reclaimed Vegetation in a Rare Earth Mine and Analysis of its Correlation with the Chlorophyll Content
Journal of Applied Spectroscopy ( IF 0.8 ) Pub Date : 2020-07-15 , DOI: 10.1007/s10812-020-01038-7
H. Li , Zh. Wei , X. Wang , F. Xu

Due to special mining technology, ionic rare earth mines easily change the surrounding surface soil properties and cause damage to the ecosystem, which leads to difficulties in vegetation ecological restoration. In this paper, tung trees, bamboo willow, and slash pine were selected as reclamation vegetation, and their spectral characteristics under ecological environmental stress were compared. In addition, by analyzing the correlation between their chlorophyll contents and spectral parameters, a theoretical basis for hyperspectral remote sensing for monitoring rare earth reclaimed vegetation growth is provided. The results show that the reflectance of the visible bands in the three vegetation types is less than 0.15, and there are different degrees of "redshifting" in the green peaks and red valleys; correlation analysis was carried out between the chlorophyll contents of the three vegetation types and the original spectra and derivative spectra. The optimal band in the original spectra was concentrated near the red valley. The first-order derivative spectra are more dispersed than the original spectra; the tung tree signal is concentrated in the red edge region, the slash pine signal is located in the near-infrared band, and the bamboo willow signal is located near the green peak and the red edge band. The three vegetation types have some of the same but also different chlorophyll-sensitive parameters. Among them, REP is the maximum parameter for the tung tree, Dr is the maximum parameter for slash pine, and SDr – SDb/SDb + SDr is the maximum parameter for bamboo willow, which can provide a reference for the construction of inversion models of different vegetation chlorophyll contents.

中文翻译:

稀土矿山复垦植被的光谱特征及其与叶绿素含量的相关性分析

由于特殊的采矿技术,离子型稀土矿很容易改变周围表层土壤的特性,并对生态系统造成破坏,从而给植被生态恢复带来困难。本文选择了桐树,竹柳和阔叶松作为复垦植被,并比较了它们在生态环境胁迫下的光谱特征。此外,通过分析其叶绿素含量与光谱参数之间的相关性,为高光谱遥感监测稀土再生植被生长提供了理论依据。结果表明,三种植被类型的可见带反射率均小于0.15,绿峰和红谷存在不同程度的“红移”。对三种植被类型的叶绿素含量与原始光谱和导数光谱进行了相关分析。原始光谱中的最佳谱带集中在红色山谷附近。一阶导数谱比原始谱更​​分散。桐树信号集中在红色边缘区域,斜线松树信号位于近红外带,竹柳信号位于绿色峰值和红色边缘带附近。这三种植被类型具有一些相同但也不同的叶绿素敏感参数。其中,REP是桐树的最大参数D 原始光谱中的最佳谱带集中在红色山谷附近。一阶导数谱比原始谱更​​分散。桐树信号集中在红色边缘区域,斜线松树信号位于近红外带,竹柳信号位于绿色峰值和红色边缘带附近。这三种植被类型具有一些相同但也不同的叶绿素敏感参数。其中,REP是桐树的最大参数D 原始光谱中的最佳谱带集中在红色山谷附近。一阶导数谱比原始谱更​​分散。桐树信号集中在红色边缘区域,斜线松树信号位于近红外带,竹柳信号位于绿色峰值和红色边缘带附近。这三种植被类型具有一些相同但也不同的叶绿素敏感参数。其中,REP是桐树的最大参数D 这三种植被类型具有一些相同但也不同的叶绿素敏感参数。其中,REP是桐树的最大参数D 这三种植被类型具有一些相同但也不同的叶绿素敏感参数。其中,REP是桐树的最大参数Dr是阔叶松的最大参数,SD r – SD b / SD b + SD r是竹柳的最大参数,可为构建不同植被叶绿素含量的反演模型提供参考。
更新日期:2020-07-15
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