Mines are typical harsh workplaces with high demand for unmanned and automated operations. Thus, major mining companies in the United States of America (USA) and Australia are developing and applying smart mining technologies, including unmanned mines1,2,3,4,5,6,7. Smart mining enables optimal and efficient mining and very high level of safety by minimizing manpower input for mining, […]
Mines are typical harsh workplaces with high demand for unmanned and automated operations. Thus, major mining companies in the United States of America (USA) and Australia are developing and applying smart mining technologies, including unmanned mines1,2,3,4,5,6,7. Smart mining enables optimal and efficient mining and very high level of safety by minimizing manpower input for mining, transportation, drilling and blasting through state of art sensing technologies and unmanned automation technology. For automated smart mining, it is necessary to determine the value of rocks as minerals at the mine end site and also to figure out the spatial distribution of useful minerals in near real time. In other words, for smart mining, it is necessary to obtain information about the geological structure and mineral composition of the mining end in near real time. However, until now, the collection of information on the mineral composition and distribution at a mine site relies almost entirely in site visual inspection by geologists and geochemical analysis of some rock samples8. This paper presents research into the development of a 3D hyperspectral scanning system for underground spaces.
From Nature by H. Baik et al.
Recently, hyperspectral remote sensing technology has attracted considerable attention as a technology that can replace the fieldwork of geological experts9. The ability of hyperspectral remote sensing technology to detect and discriminate geologic materials has the advantages of expert level in terms of accuracy and speed, and expanding and developing an element sensing technology for smart mining is easy.
Hyperspectral imaging is a technology that acquires tens to hundreds of continuous spectral information of materials located in each pixel of an image by spectroscopy of light incident on a sensor10,11,12. From hyperspectral images (HSI), unique optical properties exist for each material, and the absorption and reflection characteristics can be analyzed. Owing to these advantages, hyperspectral imaging has recently been adopted in the mining industry13,14. In particular, drone-based hyperspectral remote sensing technology has been confirmed as a highly useful tool in open-pit mining sites for mineral detection and monitoring15.
For the complete article on 3D hyperspectral scanning CLICK HERE.
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Gene V. Roe founded Lidar News in 2008 with two family members and is the founder of MPN Components, Inc., a geomatics consulting firm specializing in applied research, strategic marketing, branding, and technology development. As both a Professional Engineer and Land Surveyor, Gene has dedicated his career to advancing the field of geomatics and currently serves as Chair of the ASTM 3D Imaging Systems committee, where he led the development of the widely adopted E57 3D lidar data interoperability format. He has long been a thought leader in the adoption of transformative technologies, including CAD, GIS, GPS, and 3D laser scanning and lidar, primarily supporting innovation in the transportation industry.
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