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Estimation of rock Fe content based on hyperspectral indices

  • Geography, geology and natural resources in Central Asia (Guest Editorial Board Member: Prof. Dr. XIAO Wenjiao)
  • Published:
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Abstract

Information on the Fe content of bare rocks is needed for implementing geochemical processes and identifying mines. However, the influence of Fe content on the spectra of bare rocks has not been thoroughly analyzed in previous studies. The Saur Mountain region within the Hoboksar of the Russell Hill depression was selected as the study area. Specifically, we analyzed six hyperspectral indices related to rock Fe content based on laboratory measurements (Dataset I) and field measurements (Dataset II). In situ field measurements were acquired to verify the laboratory measurements. Fe content of the rock samples collected from different fresh and weathered rock surfaces were divided into six levels to reveal the spatial distributions of Fe content of these samples. In addition, we clearly displayed wavelengths with obvious characteristics by analyzing the spectra of these samples. The results of this work indicated that Fe content estimation models based on the fresh rock surface measurements in the laboratory can be applied to in situ field or satellite-based measurements of Fe content of the weathered rock surfaces. It is not the best way to use only the single wavelengths reflectance at all absorption wavelengths or the depth of these absorption features to estimate Fe content. Based on sample data analysis, the comparison with other indices revealed that the performance of the modified normalized difference index is the best indicator for estimating rock Fe content, with R2 values of 0.45 and 0.40 corresponding to datasets I and II, respectively. Hence, the modified normalized difference index (the wavelengths of 2220, 2290, and 2370 nm) identified in this study could contribute considerably to improve the identification accuracy of rock Fe content in the bare rock areas. The method proposed in this study can obviously provide an efficient solution for large-scale rock Fe content measurements in the field.

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Acknowledgements

This study was funded by the Xinjiang Science and Technology Major Project (2021A03001-3), the National Key R&D Program of China (2018YFC0604001-3), the B&R Team of Chinese Academy of Sciences (2017-XBZG-BR-002), and the National Natural Science Foundation of China (U1803117, U1803241).

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Authors and Affiliations

  1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China

    Jinlin Wang, Wei Wang, Yinyi Cheng, Zhixin Zhang, Shanshan Wang & Kefa Zhou

  2. Xinjiang Key Laboratory of Mineral Resources and Digital Geology, Urumqi, 830011, China

    Jinlin Wang, Wei Wang, Yinyi Cheng, Zhixin Zhang, Shanshan Wang & Kefa Zhou

  3. Xinjiang Research Centre for Mineral Resources, Chinese Academy of Sciences, Urumqi, 830011, China

    Jinlin Wang, Wei Wang, Yinyi Cheng, Zhixin Zhang, Shanshan Wang & Kefa Zhou

  4. University of Chinese Academy of Sciences, Beijing, 100049, China

    Jinlin Wang, Wei Wang, Yinyi Cheng, Zhixin Zhang, Shanshan Wang & Kefa Zhou

  5. Zhejiang A & F University, Hangzhou, 311300, China

    Pingheng Li

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  1. Jinlin Wang
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  2. Wei Wang
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  3. Yinyi Cheng
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Correspondence to Wei Wang.

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Wang, J., Wang, W., Cheng, Y. et al. Estimation of rock Fe content based on hyperspectral indices. J. Arid Land 13, 1287–1298 (2021). https://doi.org/10.1007/s40333-021-0110-5

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  • DOI: https://doi.org/10.1007/s40333-021-0110-5

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