Abstract

In remote sensing, information about an object of interest is most frequently derived by analysing the spectral characteristics of the electromagnetic energy emanating from it. In this context, the spectral characteristics of soils and rocks can provide useful information about their chemical and mineralogical composition. In this study, an investigation is conducted in order to examine the relationship between the spectral data as obtained by a spectroradiometer and the chemical and mineralogical composition of soils originated from mafic/ultramafic rocks. In order to help in understanding this relationship, the Karhunen–Loève (KL) transformation, also known as principal components (PC) transformation, was applied to the data to determine the relationship between spectral reflectance patterns and the soil's chemical and mineralogical composition. The first three principal components (PC1, PC2 and PC3), i.e. the components associated with the three largest eigenvalues, were analysed. The experiments have shown that a clear interpretation can be assigned to each of the three components. The first component (PC1) can be related to the sample albedo. The second component (PC2) conveys information with respect to the slope of the sample's spectral reflectance curve, from the visible to the infrared portions of the spectrum. The third component (PC3) relates to the contents of iron-bearing and calcium/magnesium-bearing minerals in the soil sample. The approach proposed in this study may help to better understand the relationship between the sample's spectral pattern and its chemical and mineralogical composition.

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