A New Hyperspectral Index for Estimating Copper Content in an Indicative Plant for the Exploration of Copper Deposit
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With the rapid development of hyperspectral technology, estimating metal content in plants by establishing the relationship between vegetation indices and metal content has become popular. However, few researchers have studied whether the vegetation index can be used to estimate the metal content in Seriphidium terrae-albae. It is essential to estimate the metal content in S. terrae-albae because the geochemical information gathered in its body can provide reference for the exploration of concealed deposits. To propose a new vegetation index with which to estimate copper content, this study first analyzes the relationships between three types of vegetation indices, including the ratio, difference, and normalized vegetation index, constructed by the combination of two arbitrary bands in the range of 400–1300 nm and the copper content in S. terrae-albae. The results show that (R747.5 − R572.5)/(R747.5 + R572.5) and R752.5/R517.5 have greater relationships with copper content than other vegetation indices. This method’s applicability for estimating copper content using these two types of vegetation indices is compared from three different angles: the accuracy of the metal content estimation, the sensitivity of the vegetation index to the metal content, and the influence of spectral scale. The results reveal that R752.5/R517.5 has a more stable spectral width than (R747.5 − R572.5)/(R747.5 + R572.5), and it can also be used to easily detect subtle changes in copper content. Finally, we determine that R752.5/R517.5 is the best vegetation index for estimating the copper content in S. terrae-albae.
KeywordsSeriphidium terrae-albae Copper content Vegetation indices Spectral scale
This research is funded by National Natural Science Foundation of China (Grant Nos. U1503291, 41402296), International cooperation project of the Xinjiang Uygur Autonomous Region (Grant No. 20156017), Key Laboratory fund of Xinjiang Uygur Autonomous Region (Grant No. 2016D03006). The “one belt and one road” team of the Chinese Academy of Sciences (2017-XBZG-BR-002), Key R&D Program of Xinjiang Uygur Autonomous Region (2017B03017-2).
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Conflict of interest
The authors declare that they have no conflict of interest.
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