Integrated Geological and Geophysical Mapping of a Carbonatite-Hosting Outcrop in Siilinjarvi, Finland, Using Unmanned Aerial Systems

被引:29
作者
Jackisch, Robert [1 ]
Lorenz, Sandra [1 ]
Kirsch, Moritz [1 ]
Zimmermann, Robert [1 ]
Tusa, Laura [1 ]
Pirttijarvi, Markku [2 ]
Saartenoja, Ari [2 ]
Ugalde, Hernan [3 ]
Madriz, Yuleika [1 ]
Savolainen, Mikko [4 ]
Gloaguen, Richard [1 ]
机构
[1] Helmholtz Inst Freiberg Resource Technol, Div Explorat Technol, Helmholtz Zentrum Dresden Rossendorf, Chemnitzer Str 40, D-09599 Freiberg, Germany
[2] Radai Oy, Teknol 18, Oulu 90590, Finland
[3] DIP Geosci, 100 Burris St, Hamilton, ON L8M 2J5, Canada
[4] Yara Suomi Oy, Nilsiantie 50, Siilinjarvi 71801, Finland
关键词
unmanned aerial systems; hyperspectral; multispectral; magnetic; geologic mapping; drones; UAV; MINERAL EXPLORATION; ISOTOPE COMPOSITION; GEOCHEMICAL DATA; AIRCRAFT SYSTEM; PHOTOGRAMMETRY; REFLECTANCE; TECHNOLOGY; MULTISCALE; ELEMENT; SIGNAL;
D O I
10.3390/rs12182998
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Mapping geological outcrops is a crucial part of mineral exploration, mine planning and ore extraction. With the advent of unmanned aerial systems (UASs) for rapid spatial and spectral mapping, opportunities arise in fields where traditional ground-based approaches are established and trusted, but fail to cover sufficient area or compromise personal safety. Multi-sensor UAS are a technology that change geoscientific research, but they are still not routinely used for geological mapping in exploration and mining due to lack of trust in their added value and missing expertise and guidance in the selection and combination of drones and sensors. To address these limitations and highlight the potential of using UAS in exploration settings, we present an UAS multi-sensor mapping approach based on the integration of drone-borne photography, multi- and hyperspectral imaging and magnetics. Data are processed with conventional methods as well as innovative machine learning algorithms and validated by geological field mapping, yielding a comprehensive and geologically interpretable product. As a case study, we chose the northern extension of the Siilinjarvi apatite mine in Finland, in a brownfield exploration setting with plenty of ground truth data available and a survey area that is partly covered by vegetation. We conducted rapid UAS surveys from which we created a multi-layered data set to investigate properties of the ore-bearing carbonatite-glimmerite body. Our resulting geologic map discriminates between the principal lithologic units and distinguishes ore-bearing from waste rocks. Structural orientations and lithological units are deduced based on high-resolution, hyperspectral image-enhanced point clouds. UAS-based magnetic data allow an insight into their subsurface geometry through modeling based on magnetic interpretation. We validate our results via ground survey including rock specimen sampling, geochemical and mineralogical analysis and spectroscopic point measurements. We are convinced that the presented non-invasive, data-driven mapping approach can complement traditional workflows in mineral exploration as a flexible tool. Mapping products based on UAS data increase efficiency and maximize safety of the resource extraction process, and reduce expenses and incidental wastes.
引用
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页数:31
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