Making Finland a global leader of sustainable mineral industry requires continuous improvement of expertise in mining indstry. Mineral extraction industry demands for fast, cost efficient and safe remote sensing methods. This research aims at developing novel remote sensing techniques including active 3-dimensional hyperspectral imaging, background-free Raman, and laser induced breakdown spectroscopy (LIBS) combined with multisensor positioning. These new technologies enable automatic identification, classification, and mapping of minerals as well as improving the mining safety. Compared to the state-of-the-art passive optical imaging currently used in mining industry, our technologies enable remote sensing from distances reaching hundreds of meters. We will also make use of the 3D laser scanning information to enhance and automate the identification of mineral deposits, thus allowing for efficient mining of mineral deposits that are challenging for current extraction techniques.
Our project in Tekes Challenge Finland project gallery
Kaivos project booth at Mines and Technology Helsinki 2018: VTT’s active hyperspectral imaging device scanning on Outokumpu rocks, and distinguishing between ore and gangue.
The spectra of minerals and gangue in the visible spectral region. The different minerals show different reflectance trends.
24.-27.9. 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nantes, France, paper submitted by FGI
10.-13.9. SPIE remote sensing, Berlin. Presentation: ‘A continuously tunable NIR laser and its applications in material classification’ by Priit Jaanson
22.-27.7.2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2018, Valencia, Spain. Invited presentation: ‘Multispectral Terrestrial Laser Scanning: New Developments and Applications‘ by Sanna Kaasalainen et al.
12.6. 3rd steering group meeting, VTT
29.-31.5. Mines and Technology Helsinki 2018, the Kaivos project was one of the exhibitors
23.-24.5. Pohjoinen Teollisuus, Oulu, VTT were demonstrating the new instrument
16.-18.4.2018 Workshop on Challenges in Arctic Navigation, Olos, Lapland. Poster presentation on the project: ‘Efficient & safe identification of minerals – Smart real-time methods’. Sanna Kaasalainen, Tuomo Malkamäki, Laura Ruotsalainen
4.4.2018 Progress meeting 4
17.1.2018 The project is now on Twitter: @KaivosProject
10.-12.1.2018 Nordic Geological Winter Meeting, Copenhagen. Presentation ‘Towards Real-Time Ore Grade Evaluation using Laser-Induced Breakdown Spectroscopy‘, Lasse Kangas, Roel van Toorenenburg, and Jussi Leveinen
14.12. 2017 Progress meeting 3
14.11.2017 2nd steering group meeting, NLS, Pasila
Nov 2017: Questionnaire on sensor technology for people working in geosciences (in Finnish)! Click here.
15.9.2017 Progress meeting 2
9.6.2017 Progress meeting 1
12.4.2017 Visit to Outokumpu Kemin Mine (FGI, CC)
21.3.2017 1st steering group meeting, VTT, Espoo
Kangas L., et al., 2016. Identification of rocks using a hyperspectral supercontinuum lidar. 35:th International Geological Congress proceedings, paper 4995.
Kaasalainen, S., Ruotsalainen, L., Kirkko-Jaakkola, M., Nevalainen, O., and Hakala, T., 2017. Towards Multispectral, Multi-Sensor Indoor Positioning and Target Identification. Electronics Letters, Volume 53, Issue 15, 20 July 2017, .
Andrea Della Monica, Politecnico di Torino, Italia: GNSS and multi-sensor integration, MSc Thesis, 2017
Suksi Teemu, Aalto University: Hardness Classification of Rocks Using Spectroscopy, MSc Thesis, 2017
Della Monica, A., Ruotsalainen, R., and Dovis, F., 2018. Multisensor Navigation in Urban Environment, Position, Location and Navigation Symposium (PLANS), 2018 IEEE/ION
Kaasalainen, S., et al., 2018. Multispectral terrestrial laser scanning: New developments and applications, accepted to IGARSS, 2018
Jaanson, P., et al., 2018 A continuously tunable NIR laser and its applications in material classification, accepted to SPIE Remote Sensing, 2018.
Research Professor Sanna Kaasalainen: sanna.kaasalainen(at)nls.fi
Dr. Priit Jaanson: priit.jaanson(at)vtt.fi
Professor Jussi Leveinen: Jussi.Leveinen(at)aalto.fi