3D remote sensing of mines
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The document discusses advancements in 3D remote sensing technologies for mining, highlighting the benefits of improved productivity, risk management, and environmental monitoring. Various methods such as UAVs, lasers, and satellites are explored for capturing intricate data, including terrain models and environmental impacts. The future of mining may involve fully autonomous operations supported by these advanced technologies.
3D remote sensing of mines
- 1. 3D Remote Sensing of Mines Eija Honkavaara, Anttoni Jaakkola, Roope Näsi, Tomi Rosnell, FGI Jussi Kirjasniemi, Pentti Ruokokoski, Lentokuva Vallas Oy Timo Brander, Aalto yliopisto
- 2. 3D Modeling and Virtual Worlds *Lingli Zhu Remote Sensing Electronics *Yuwei Chen Mobile Mapping & Laser Scanning *Anttoni Jaakkola Spectrophotogrammetry *Eija Honkavaara Finnish Geospatial Research Institute, Department of Remote Sensing & Photogrammetry Research Groups Head of department, Prof. Juha Hyyppä
- 3. What is 3D Remote sensing? • Remote data capture, without touching the object • 3D Shape: • Terrain model (DTM), • Surface model (DSM), • Canopy height model (CHM) • Internal structure • Spectrum • Classification of materials, identification of anomalies etc. • Passive and active sensors DTM DSM CHM= DTM-DSM
- 4. Space based observations Ground based observations Airborne observations Earth remote sensing technologies
- 5. UAS Satellite Airborne Terrestrial Large Small HighLow Coverage Flexibility Remote sensing application potential
- 6. Central objectives of utilization of 3D remote sensing in mining • Improving the productivity • Mapping the quality and amount of ore • Measuring the bulk material volume, the open pit volume • Risk management in mine operation: Landslides, Traffic, Blasting • Monitoring of environmental impacts • Water management: Monitoring the enrichment pool, mine water runoff forecasting, forecasting disturbances • Monitoring the nature and biodiversity, the growth and healthy of trees • Caves: Indoor mapping… • Improving the level of automation, Autonomous mine • Data capture -> Data processig -> Model generation -> Analysis
- 8. Radar and Optical Satellites 8 • Global monitoring of the mine and the environment • Optical multi- and hyperspectral, stereoscopic • VHRS: Spatial resolution 0.3-1 m • HRS: Spatial resolution 5-20 m • Sentinel 2, Landsat, free, resolution 10-20 m • SAR • Detecting millimeter changes using SAR interferometry time series • Not weather dependent • Sentinel 1, 12 days, free, 10-20 m resolution • Cosmo Sky med, 10 km x 10 km, best resolution 1 m • TerraSarX , best resolution 1 m
- 9. Aerial Photogrammetry and imaging 9 • Operational since beginning of 1900 • Basis of maps • Stereoimages and orthophotos • 3D point clouds • 1 to 1000 points /m • Accuracy 1 cm - • Low to high altitude imaging • Also hyperspectral imaging • Manned airborne vehicle (MAV)
- 10. Airborne Laser Scanning (ALS) 31.1.12 • 3D point clouds 0.5 to 100 points /m2; • As an example the National Laser Scanning model with point density of 0.5 points/m2 • Terrain and canopy models • Accuracy 1 cm - on well defined, hard surfaces • Day and night, Highly water resistant, Not in rain or smog • Wider area measurements • In future also Multi spectral laser scanning
- 11. UAV Photogrammetry and imaging • Low cost technology • Accurate 3D point clouds, color images, Repetitive measurements <daily resolution • Also hyperspectral and thermal • Rapidly developing technology
- 12. UAV Laser Scanning 31.1.12 • New and rapidly developing technology • Very high density 3D point cloud data, e.g. 1000 points/m2 • Repetitive measurements <daily resolution • Rapidly developing tehcnology
- 13. Terrestrial & Personal Laser Scanning 13 • Static and mobile • Very high density 3D point cloud data • Rapidly developing technology • Repetitive measurements
- 14. Success stories of MMEA UAV Work Packet Cost efficient 3D modelling and watershed management of mining environment. • Co-operation: Mining pilot Identifying Insect invasions in forests using hyperspectral UAV and MAV A new method for detecting thermal leaks of buildings • Co-operation: Energy efficient indoor environments
- 15. 1. Case study by Lentokuva Vallas Oy Monitoring and Risk Management in Mining Industry using REMOTE SENSING Image capture – about 1000 images - 10 cm/pixel Cessna, Nikon D3X, GPS By Pentti Ruokokoski, Lentokuva Vallas Oy
- 16. Monitoring and Risk Management in Mining Industry using REMOTE SENSING IMAGE MOSAICS - 10cm/pixel By Pentti Ruokokoski, Lentokuva Vallas Oy
- 17. By Pentti Ruokokoski, Lentokuva Vallas Oy DSM
- 18. Watershed analysis 18 Main watersheds Watersheds+ standard basins Main watersheds + main flows Flow accumulation By Pentti Ruokokoski, Lentokuva Vallas Oy
- 19. 2. Monitoring of bark beetle infestation in forest using hyperspectral UAV imaging • Serious forest death in spruce forests due to bark beetle in Southern Finland • Objective: Early detection of infestion using hyperspectral images from manned and unmanned aircrafts • Feasibility of the novel Fabry-Pérot interferometer based hyperspectral imager • Co-operation: University of Helsinki, Lentokuva Vallas, MMEA-program 19
- 20. 20 Field reflectance reference Data capture Image pre- processing Image orientation DSM generation Radiometric block adjustment Individual tree detection Spectral characteristics of trees Classification Mosaic generation Forest reference plots ALS DTM Processing flow UAV Näsi, R. et al. Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level. Remote Sens. 2015, 7, 15467-15493.
- 21. 3. Using UAVs for detecting thermal leaks of buildings • Thermal camera Flir Photon 320 • 324x256 pix, GSD 20 cm • Weigh < 1 kg • RGB camera • Two flights 4.5.2013, takeoff 5:13 and 21:42 local time • Four flight lines, altitude 70 m, Also building facades • Speed 4 m/s • Co-operation with Energy efficient indoor environments 3D model of VTT test building in Otaniemi Jaakkola, A., Kauppinen, T., 2014. Lämpökuvauksella tietoa rakennusten kunnosta. Positio 3/2014.
- 22. Results Jaakkola, A., Kauppinen, T., 2014. Lämpökuvauksella tietoa rakennusten kunnosta. Positio 3/2014. 5:13 21:42 21:12
- 23. Conclusion • New data capture technology provides new possibilities for improving productivity, safety and environmental monitoring of mines • Affordable and repeatable monitoring • Future monitoring integrates satellites, MAVs, UAVs and terrestrial technologies • Also indoor 3D mapping • Towards better monitoring of mining environments, autonomous mine • Department of Remote Sensing and Photogrammetry focuses future remote sensing measurement and analysis technologies. • Suitable also for monitoring of open pit mines and underground mines, as well as assessment of environmental impacts
Editor's Notes
- #3: Department includes all levels of Remote sensing. From electronc instruments to data collection to 3d modeling
- #4: Volume, mass changes Spectrum which is data about reflection of objects
- #5: Overview of Platforms Environmental monitoring
- #6: This chart show potential for application potentials Orbits are what they are; we can not change it And other extrimity is terrsestrial measurements Platforms
- #7: Kaivostoiminnassa keskeiset kaukokartoitusteknologiaan liittyvä kehitystarpeet liittyvät kaivoksen Tuottavuuden parantaminen: malmin laatu, malmin määrä, irtomateriaalitilavuudet, avolouhostilavuudet, automaatioasteen parantaminen Riskien minimointiin: turvallisuus, sortumavaarat, liikenne, räjäytykset Ympäristövaikutusten seurantaan: rikastusaltaan seuranta, kaivosvesien valumien ennakointi, häiriöiden ennakointi, luonnon ja luonnon monimuotoisuuden seuranta, puiden ja pensaiden kasvun seuranta
- #8: Missä kauha liikkuu, mitä sinne menee, mihin kaadetaan, mistä otetaan Where are excavators? Ore? Where it should be Lot of sensors which are integrated each other. 3d-cameras, scanners, gps.. Next remote sensor techonoligies
- #9: 5-10 mm/1 Savi –clay Cosmo Sky med, 5000 €,
- #10: Images and 3D point clouds 1 to 1000 points /m2; Accuracy 1 cm to 20 cm well defined, Day time, uses sun light. Pentti tells more
- #11: 3D point clouds 0.5 to 100 points /m2; Accuracy 1 cm to 20 cm well defined, hard surfaces Day and night, Highly water resistant, Not in rain or smog
- #12: Rikola produce and cell the new camera Specim 1990-
- #13: World first mini-uav laser scanni9ng was development in fgi
- #14: Quad bike -mönkijä
- #15: 2013-2015 mukana UAV-paketissa. Vesistöt, lämpökuvaus, kaivos, metsätuhot