The use of geoinformatics in mineral exploration and exploitation
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The document discusses the use of geoinformatics, including remote sensing techniques, in mineral exploration and exploitation. It provides several case studies demonstrating how different remote sensing data and techniques can be used to map surface geology and identify potential mineral deposits. These include using Landsat and ASTER satellite imagery to map surficial mineralogy across large areas, detect hydrothermal alteration zones indicating gold mineralization, and identify geothermal anomalies. Integrating remote sensing data with other spatial datasets in a GIS provides additional insights. Future opportunities discussed include the increasing use of unmanned aerial vehicles and the upcoming Sentinel-2 satellite mission.
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http://www.alexandernubia.com/cms/pages/13 [Accessed 28 February 2015 ]
• Beiranvand Pour,A., & Hashim, M., 2012, The application of ASTER remote sensing data to
porphyry copper and epithermal gold deposits, Ore Geology Reviews, Vol.44, P.1–9.
• Bedini,E., 2011. Mineral mapping in the Kap Simpson complex, central East Greenland,
using HyMap and ASTER remote sensing data, Advances in Space Research, Vol.47, P.60–
73.
• Calvin,W.M., Littlefield,E.F., & Kratt,C., 2015. Remote sensing of geothermal-related
minerals for resource exploration in Nevada, Geothermics, Vol.53, P.517–526.
• Drusch,M., Del Bello,U., Carlier,S., Colin,O., Fernandez,V., Gascon,F., Hoersch,B., Isola,C.,
Laberinti,P., Martimort,P., Meygret,A., Spoto Sy,O., Marchese,F., & Bargellini,P., 2012. Sentinel-
2: ESA's Optical High-Resolution Mission for GMES Operational Services, Remote
Sensing of Environment, Vol.120, P.25–36.
• E.S.A., n.d. ESA > Our Activities > Observing the Earth > Copernicus. Available online at:
http://www.esa.int/Our_Activities/Observing_the_Earth/Copernicus/Sentinel-2 [Accessed 02
February 2015 ]
• Furgo., 2015. EXPERTISE>OUR>SERVICES SURVEY>AERIAL MAPPING>Mining
Development and Management. Available online at: http://www.fugro.com/our-expertise/our-
services/survey/aerial-mapping#tabbed2 [Accessed 28 February 2015 ]
• Gabr,S.,Ghulam,A., & Kusky,T., 2010. Detecting areas of high-potential gold mineralization
using ASTER data, Ore Geology Reviews, Vol.38, P.59–69.
• Garrun,D., 2009. UAVs – Mining’s Eye in The Sky. Available online at: http://www.mining-
technology.com/features/feature60074/ [Accessed 28 February 2015 ]
• Ott,N., Kollersberger,T., and Tassara,A., 2006. GIS analyses and favorability mapping of
optimized satellite data in northern Chile to improve exploration for copper mineral
deposits. Geosphere, Vol.2., Issue.4., P.236-252.](https://image.slidesharecdn.com/4frkiu85riq13ndwbmsp-signature-d20c1a94629a6181381d625775f37a2d27d6b1a0ae2800ddc7cd5d81f77af753-poli-150612232808-lva1-app6891/85/The-use-of-geoinformatics-in-mineral-exploration-and-exploitation-49-320.jpg)
![Bibliography
• Satellite Imaging Corporation, 2001-2014. ASTER Satellite Image of Morenci Mine in
Arizona. Available online at: http://www.satimagingcorp.com/gallery/more-imagery/aster/aster-
arizona-morenci-mine-es/ [Accessed 02 February 2015 ]
• Rockwell, B.W. and Bonham, L.C., 2013, USGS National Map of Surficial Mineralogy: U.S.
Geological Survey Online Map Resource. Available online at:
http://cmerwebmap.cr.usgs.gov/usminmap.html [Accessed 14 March 2015]
• Rockwell, B.W., 2013, Automated mapping of mineral groups and green vegetation from
Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado:
U.S. Geological Survey Scientific Investigations Map 3252, 25-p. pamphlet, 1 map sheet, scale
1:325,000, http://pubs.usgs.gov/sim/3252/
• UNEP, CATHALAC., 2015. La Escondida, Chile. Latin America and the Caribbean – Atlas of
Our Changing Environment. Available online at:
http://www.cathalac.org/lac_atlas/index.php?option=com_content&view=article&id=22:la-
escondida-chile&catid=1:casos&Itemid=5 [Accessed 02 February 2015 ]
• U.S.G.S., 2012, Landsat-A Global Land-Imaging Mission: U.S. Geological Survey Fact Sheet
2012–3072, P.4.
• U.S.G.S., 2014. “Landsat Missions Timeline”, Available online at:
http://landsat.usgs.gov/about_mission_history.php [Accessed 14 March 2015]
• Van der Meer,F.D., Van der Werff,H.M.A., Van Ruitenbeek,F.J.A., Hecker,C.A., Bakker,W.H.,
Noomen,M.F.,Van der Meijde,M., Carranza,E.J.M., Boudewijn de Smeth,J., & Woldai,T., 2012.
Multi- and hyperspectral geologic remote sensing: A review, International Journal of
Applied Earth Observation and Geoinformation, Vol.14, P.112–128.
• Van der Meer,F.D., Van derWerff,H.M.A., & Van Ruitenbeek,F.J.A., 2014. Potential of ESA's
Sentinel-2 for geological applications, Remote Sensing of Environment, Vol.148, P.124–133.](https://image.slidesharecdn.com/4frkiu85riq13ndwbmsp-signature-d20c1a94629a6181381d625775f37a2d27d6b1a0ae2800ddc7cd5d81f77af753-poli-150612232808-lva1-app6891/85/The-use-of-geoinformatics-in-mineral-exploration-and-exploitation-50-320.jpg)
The use of geoinformatics in mineral exploration and exploitation
- 1. The Use of Geoinformatics in Mineral Exploration and Exploitation Marguerite Walsh MSc Geographical Information Systems and Remote Sensing 18th March 2015 Van der Meer, et al, 2014
- 2. Introduction Benefits geologists, scientists and exploration managers Mineral exploration and exploitation is a huge source of employment around the world Main focus on remote sensing
- 3. History of Remote Sensing in Geology Graham Hunt & John Salisbury (1970s/1980s) Based on laboratory spectral analysis of minerals and rocks Geologic Remote Sensing Mineral exploration Hyperspectral geology Mineral resource mapping Seismic activity Dr. F. van der Meer
- 4. Remote Sensing (1) Advantages Classification for mapping Target identification “bird’s eye view” – can cover large areas quickly Can see any patterns or trends – differences in tone, texture and structure
- 5. Remote Sensing (2) Issue Cloud cover Features on the ground can be hidden beneath vegetation Sub surface features Solution Radar Radar Radio Echo Sounding
- 6. Satellite sensors 1000s of options. Archive of data Temporal resolution Orbit of satellite Spectral resolution Spatial resolution Cost
- 7. Spectral Signatures (1) • Multiple bands that show what the human eye cannot see • Visible, near infrared, short- wave infrared and thermal infrared http://www.akitarescueoftulsa.com/label-the-electromagnetic- wave-diagram/ “Many minerals have unique and diagnostic spectral properties, and features such as the band centre, strength, shape, and width are used to identify species with high confidence” (Calvin et al, 2015)
- 8. Spectral Signatures (2) USGS Spectral Library • Multispectral imaging and thematic mapping • Reflection data and absorption properties • Photogeology • USGS Spectral Library
- 9. “Spectrally Active” minerals can be mapped with Remote Sensing Environment of formation Main spectrally active alteration minerals High sulphidation epithermal Alunite, pyrophyllite, dickite, kaolinite, diaspore, zunyite, smectite, illite Low sulphidation epithermal Sericite, illite, smectite, chlorite, cabonate Porphyry: Cu, Cu-Au Biotite, anhydrite, chlorite, sericite, pyrophyllite, zeolite, smectite, canbonate, tourmaline Carlin-type Illite, dickite, kaolinite Volcanogenic massive sulphide Sericite, chlorite, chloritoid, carbonates, anhydrite, gypsum, amphiobole Archean Lode Gold Carbonate, talc, tremolite, muscovite, paragonite Calcic skarn Garnet, clinopyroxene, wollastonite, actinlite Retrograde skarn Calcite, chlorite, hematite, illiteVan der Meer, et al, 2014.
- 10. Landsat (1) “Landsat represents the world's longest continuously acquired collection of space-based moderate- resolution land remote sensing data. ” (USGS, 2013) Operational 1972-present U.S.G.S., 2014.
- 11. Landsat (2) Joint project of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) Data every 16/18 days 11 Bands Resolution 30-60m Free images Easily accessible (U.S.G.S., 2012)
- 12. Case Study 1: USGS National Map of Surficial Mineralogy • Mapping exposed surface mineral groups • 3 applications: • undiscovered mineral deposits • environmental effects associated with mining and • unmined, hydrothermally-altered rocks • Done using: • 180 Landsat scenes and • 1630 ASTER scenes
- 13. Case Study 1: USGS National Map of Surficial Mineralogy • Already done for the western part of the US – extending eastwards • More detailed and accurate mineral and vegetation maps • Active & abandoned mining districts • Done using: • ASTER • (AVIRIS) • HyMap or • SpecTIR • An algorithm was developed to automatically analyse Landsat 8 imagery Rockwell, 2013
- 14. Case Study 1: USGS National Map of Surficial Mineralogy This data is available as GIS shapefiles to add into ArcMap Rockwell, 2013
- 15. ASTER The “work horse” for geologic Remote Sensing (van der Meer, 2014). Mapping of surface mineralogy ASTER band ratios as proxies 14 different wavelengths
- 16. Spectral signatures of different minerals shown through 9 ASTER spectral bands (Beiranvand Pour & Hashim, 2012) ASTER spectral signatures • ASTER has 5 thermal bands – different outcrops of minerals can be identified due to differences in specific heat capacity • Algorithms to extract the spectral information
- 18. Case Study 2: ASTER & Detecting areas of high- potential gold mineralization Hydrothermal alteration zones (gold and copper) Methods: band ratio & mineral extraction method Field mapping was also undertaken Gabr et al, 2010
- 19. Study Site: Abu-Marawat, the Eastern Desert of Egypt • Abu Marawat Deposit is a gold rich, polymetallic deposit • Historical area of gold and copper mining dating back to the time of Pharaohs and Pyramids Alexander Nubia Inc., 2011
- 20. Spectral Signatures Gabr et al, 2010
- 21. Result: ASTER band ratio image The white colour represents mineralized parts of the alteration zone – potential for significant, undiscovered gold ore
- 22. Case Study 3: ASTER & Morenci Mine, Arizona ASTER (15m) Satellite Image of Morenci Mine, Arizona - USA Satellite Imaging Corporation, 2001-2014.
- 23. ASTER Summary Issues of cloud cover and vegetation Each terrain is different and so algorithms and ratios will vary Do not look at the ASTER data in isolation
- 24. Integration with other geoinformatics technologies GIS data layers – to get a better understanding of the site ◦ Topographical ◦ Geophysical ◦ Geochemical data Adding layers on transport, relief, elevation etc Some of the GIS data layers used by the USGS in their geological studies http://woodshole.er.usgs.gov/project- pages/longislandsound/data/gis.html
- 25. Case Study 4: GIS analyses and satellite data in northern Chile to improve exploration for copper mineral deposits • La Escondida mining District • Atacama Desert, Northern Chile • The highest producing copper mine in the world. • Also produces some silver and gold La Escondida mine (left) 1975 before extraction began (right) 2008 with huge expansion UNEP, CATHALAC., 2015.
- 26. Data integration and analyses within a geographic information system Different thematic layers of the database in the vicinity of La Escondida mining district. Upper layers represent optimized Landsat data derived from band ratioing, principal component analysis (PCA), and inverse PCA. Lower layers represent topographic data, lithology, and aeromagnetic data. Bottom layer is one of the calculated favourability maps.Ott et al., 2006.
- 27. The End Result Favourability map of altered rocks at La Escondida mining district
- 28. Case Study 5: Geothermal Resources in Nevada
- 29. ASTER imagery Used both remote sensing and geographical information systems Thermal properties as surface indicators of geothermal resources Spectral data taken in the field using a spectrometer to validate results Integration into GIS databases with other relevant geologic information “to make comparisons and site assessments.” However blind geothermal systems may have very little or no surface expression at
- 30. Thermal Anomalies at the Brady’s Site, Fernley, Nevada.
- 31. The End Result Mineral Map of 4 different areas • Successful in Nevada where there is sparse vegetation cover • In vegetated areas – LiDAR may be more appropriate • UAVs with imaging spectrometers will also help map small scale features
- 32. Furgo Furgo is one of the leading companies when it comes to mining projects. Mining Development and Management – Fugro supports mine information systems by delivering accurate geospatial knowledge over the entire lifecycle of a mine. aerial surveying data - baseline data for feasibility studies, mine mapping and permitting, stock pile calculations and volumes, rehabilitation and waste dump mapping.
- 33. Regional geochemical and geological surveys Airborne geophysics Satellite monitoring and mapping optical radar Multispectral Mapping Site selection Emergency response Aerial mapping Geophysics Photography LiDAR Management and mapping
- 34. The Future UAVs – Unmanned Aerial Vehicles • Unmanned Aerial Systems will improve the ability to map small-scale surface features associated with geothermal systems in remote, rugged or vegetated terrain. (Calvin et al, 2015) • Can also be used to monitor mines for maintenance and efficient business management. • As with all UAV applications there may be different issues with standards, ethics and regulations. On the left is an aerial view of a mine in the USA captured using the INTEGRATOR UAV pictured above on the right
- 35. The Future: Sentinel-2 E.S.A., n.d.
- 36. Sentinel-2 Specifications Sentinel-2A and Sentinel-2B 2A - April 2015 2B - 1st half of 2016 To ensure the continuity of SPOT, Landsat and ASTER imagery High resolution optical imagery Spectral resolution: 13bands Spatial resolution: 10m, 20m and 60m Temporal resolution: 5days
- 37. Sentinel-2 Methods • Band ratios serve as proxies to derive different minerals • A dataset was simulated from a reflectance-at-surface airborne hyperspectral image • Simulation studies
- 38. Case Study 6: Cabo de Gata, SE Spain A volcanic field which consists of calc-alkaline volcanic rocks (andesites & rhyolites)(Van der Meer, et al, 2014.)
- 39. Case study to test the potential of Sentinel-2 Cabo de Gato Volcanic field Metamorphic minerals
- 40. Process Input (airborne hyperspectral data from the HyMAP sensor) Geometric correction Spatial subset Spectral resampling Spatial degradation Comparison of scatterplots Output (Scatter plots)
- 41. Scatterplots between simulated Sentinel-2 and simulated ASTER bands
- 42. CABO DE GATA A. Photograph of the study site B. Interpretation of the geology in the area C. 3D perspective with a natural colour composite image derived from HyMAP D. HyMAP band ratio image showing hydrothermal alteration mineralogy. Van der Meer, et al, 2014.
- 43. Van der Meer, et al, 2014. The End Result Band Ratio Products • Simulated Sentinel-2 • Simulated ASTER • Real ASTER
- 44. Geological & Mineral Interpretation Van der Meer, et al, 2014.
- 45. Results Ratio mapping Scatterplots Good correspondence between the ASTER and Sentinel-2 ratios for ferric/ferrous iron, ferric oxides, ferrous silicates, gossan and NDVI Geologic mapping The simulated Sentinel-2 was visually compared to a geological map & mineral maps. Simulated image products demonstrate a good correspondence between ASTER and Sentinel- 2 VNIR and SWIR bands
- 46. Conclusion Issues • Cloud cover and vegetation Reproducibility Expense – software and datasets / raw images The gap between academia and industry Further study into use of radar in mineral geology
- 47. Conclusion Positives • Geoinformatics – many applications and uses • Long and reliable history • So many different dimensions and components can be considered at once • UAVs and Sentinel-2 in the future
- 49. Bibliography • Alexander Nubia Inc, 2011. Abu Marawat Gold-Copper. Available online at: http://www.alexandernubia.com/cms/pages/13 [Accessed 28 February 2015 ] • Beiranvand Pour,A., & Hashim, M., 2012, The application of ASTER remote sensing data to porphyry copper and epithermal gold deposits, Ore Geology Reviews, Vol.44, P.1–9. • Bedini,E., 2011. Mineral mapping in the Kap Simpson complex, central East Greenland, using HyMap and ASTER remote sensing data, Advances in Space Research, Vol.47, P.60– 73. • Calvin,W.M., Littlefield,E.F., & Kratt,C., 2015. Remote sensing of geothermal-related minerals for resource exploration in Nevada, Geothermics, Vol.53, P.517–526. • Drusch,M., Del Bello,U., Carlier,S., Colin,O., Fernandez,V., Gascon,F., Hoersch,B., Isola,C., Laberinti,P., Martimort,P., Meygret,A., Spoto Sy,O., Marchese,F., & Bargellini,P., 2012. Sentinel- 2: ESA's Optical High-Resolution Mission for GMES Operational Services, Remote Sensing of Environment, Vol.120, P.25–36. • E.S.A., n.d. ESA > Our Activities > Observing the Earth > Copernicus. Available online at: http://www.esa.int/Our_Activities/Observing_the_Earth/Copernicus/Sentinel-2 [Accessed 02 February 2015 ] • Furgo., 2015. EXPERTISE>OUR>SERVICES SURVEY>AERIAL MAPPING>Mining Development and Management. Available online at: http://www.fugro.com/our-expertise/our- services/survey/aerial-mapping#tabbed2 [Accessed 28 February 2015 ] • Gabr,S.,Ghulam,A., & Kusky,T., 2010. Detecting areas of high-potential gold mineralization using ASTER data, Ore Geology Reviews, Vol.38, P.59–69. • Garrun,D., 2009. UAVs – Mining’s Eye in The Sky. Available online at: http://www.mining- technology.com/features/feature60074/ [Accessed 28 February 2015 ] • Ott,N., Kollersberger,T., and Tassara,A., 2006. GIS analyses and favorability mapping of optimized satellite data in northern Chile to improve exploration for copper mineral deposits. Geosphere, Vol.2., Issue.4., P.236-252.
- 50. Bibliography • Satellite Imaging Corporation, 2001-2014. ASTER Satellite Image of Morenci Mine in Arizona. Available online at: http://www.satimagingcorp.com/gallery/more-imagery/aster/aster- arizona-morenci-mine-es/ [Accessed 02 February 2015 ] • Rockwell, B.W. and Bonham, L.C., 2013, USGS National Map of Surficial Mineralogy: U.S. Geological Survey Online Map Resource. Available online at: http://cmerwebmap.cr.usgs.gov/usminmap.html [Accessed 14 March 2015] • Rockwell, B.W., 2013, Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3252, 25-p. pamphlet, 1 map sheet, scale 1:325,000, http://pubs.usgs.gov/sim/3252/ • UNEP, CATHALAC., 2015. La Escondida, Chile. Latin America and the Caribbean – Atlas of Our Changing Environment. Available online at: http://www.cathalac.org/lac_atlas/index.php?option=com_content&view=article&id=22:la- escondida-chile&catid=1:casos&Itemid=5 [Accessed 02 February 2015 ] • U.S.G.S., 2012, Landsat-A Global Land-Imaging Mission: U.S. Geological Survey Fact Sheet 2012–3072, P.4. • U.S.G.S., 2014. “Landsat Missions Timeline”, Available online at: http://landsat.usgs.gov/about_mission_history.php [Accessed 14 March 2015] • Van der Meer,F.D., Van der Werff,H.M.A., Van Ruitenbeek,F.J.A., Hecker,C.A., Bakker,W.H., Noomen,M.F.,Van der Meijde,M., Carranza,E.J.M., Boudewijn de Smeth,J., & Woldai,T., 2012. Multi- and hyperspectral geologic remote sensing: A review, International Journal of Applied Earth Observation and Geoinformation, Vol.14, P.112–128. • Van der Meer,F.D., Van derWerff,H.M.A., & Van Ruitenbeek,F.J.A., 2014. Potential of ESA's Sentinel-2 for geological applications, Remote Sensing of Environment, Vol.148, P.124–133.