Next Article in Journal
Microplastic Extraction from the Sediment Using Potassium Formate Water Solution (H2O/KCOOH)
Previous Article in Journal
Contrasting Modes of Carbonate Precipitation in a Hypersaline Microbial Mat and Their Influence on Biomarker Preservation (Kiritimati, Central Pacific)
 
 
Article

Spectral Angle Mapping and AI Methods Applied in Automatic Identification of Placer Deposit Magnetite Using Multispectral Camera Mounted on UAV †

1
Department of Geosciences, Geotechnology and Materials Engineering for Resources, Graduate School of International Resource Sciences, Akita University, Akita 010-8502, Japan
2
Faculty of International Resource Sciences, Technical Division, Akita University, Akita 010-8502, Japan
3
Department of Geology, University of Botswana, Private Bag UB 0022, Gaborone, Botswana
4
Department of Earth and Environmental Science, Botswana International University of Science and Technology, Private Bag 16, Palapye, Botswana
5
Faculty of Engineering, Division of Sustainable Resources Engineering, Hokkaido University, Hokkaido 060-8628, Japan
*
Author to whom correspondence should be addressed.
This article is an expanded version this conference paper: Sinaice, B.B.; Takanohashi, Y.; Owada, N.; Utsuki, S.; Hyongdoo, J.; Bagai, Z.; Shemang, E.; Kawamura, Y. Automatic magnetite identification at Placer deposit using multi-spectral camera mounted on UAV and machine learning. In Proceedings of the 5th International Future Mining Conference 2021—AusIMM 2021, Online, 6–10 December 2021; pp. 33–42; ISBN 978-1-922395-02-3.
Academic Editor: Yosoon Choi
Minerals 2022, 12(2), 268; https://doi.org/10.3390/min12020268
Received: 21 January 2022 / Revised: 15 February 2022 / Accepted: 18 February 2022 / Published: 20 February 2022
The use of drones in mining environments is one way in which data pertaining to the state of a site in various industries can be remotely collected. This paper proposes a combined system that employs a 6-bands multispectral image capturing camera mounted on an Unmanned Aerial Vehicle (UAV) drone, Spectral Angle Mapping (SAM), as well as Artificial Intelligence (AI). Depth possessing multispectral data were captured at different flight elevations. This was in an attempt to find the best elevation where remote identification of magnetite iron sands via the UAV drone specialized in collecting spectral information at a minimum accuracy of +/− 16 nm was possible. Data were analyzed via SAM to deduce the cosine similarity thresholds at each elevation. Using these thresholds, AI algorithms specialized in classifying imagery data were trained and tested to find the best performing model at classifying magnetite iron sand. Considering the post flight logs, the spatial area coverage of 338 m2, a global classification accuracy of 99.7%, as well the per-class precision of 99.4%, the 20 m flight elevation outputs presented the best performance ratios overall. Thus, the positive outputs of this study suggest viability in a variety of mining and mineral engineering practices. View Full-Text
Keywords: UAV; remote sensing; hyperspectral imaging; multispectral imaging; spectral angle mapping; artificial intelligence; machine learning; deep learning UAV; remote sensing; hyperspectral imaging; multispectral imaging; spectral angle mapping; artificial intelligence; machine learning; deep learning
Show Figures

Figure 1

MDPI and ACS Style

Sinaice, B.B.; Owada, N.; Ikeda, H.; Toriya, H.; Bagai, Z.; Shemang, E.; Adachi, T.; Kawamura, Y. Spectral Angle Mapping and AI Methods Applied in Automatic Identification of Placer Deposit Magnetite Using Multispectral Camera Mounted on UAV. Minerals 2022, 12, 268. https://doi.org/10.3390/min12020268

AMA Style

Sinaice BB, Owada N, Ikeda H, Toriya H, Bagai Z, Shemang E, Adachi T, Kawamura Y. Spectral Angle Mapping and AI Methods Applied in Automatic Identification of Placer Deposit Magnetite Using Multispectral Camera Mounted on UAV. Minerals. 2022; 12(2):268. https://doi.org/10.3390/min12020268

Chicago/Turabian Style

Sinaice, Brian Bino, Narihiro Owada, Hajime Ikeda, Hisatoshi Toriya, Zibisani Bagai, Elisha Shemang, Tsuyoshi Adachi, and Youhei Kawamura. 2022. "Spectral Angle Mapping and AI Methods Applied in Automatic Identification of Placer Deposit Magnetite Using Multispectral Camera Mounted on UAV" Minerals 12, no. 2: 268. https://doi.org/10.3390/min12020268

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop