Hyperspectral imaging

Geosciences [Uni Research CIPR]

 

Hyperspectral imaging in geoscience

Hyperspectral imaging is a powerful method for remote analysis of an object’s composition. In geoscience applications, mapping material content and distribution can give important insights that can be difficult to obtain from traditional sampling or conventional photographs. In outcrop geology, mapping mineral and rock types can be a vital first step towards understanding petrophysical properties (e.g. porosity and permeability) of an exposed section. Where physical sampling can be expensive and time-consuming, especially in inaccessible and remote field areas, hyperspectral imaging is an efficient way to quantitatively map materials remotely. Using non-visible parts of the electromagnetic spectrum, sampled with extremely high spectral resolution, allows material differences to be identified that may be very difficult to see on conventional photographs or in the field.

 

Hyperspectral imaging field setup.

 

The VOG Group has pioneered the use of spectral imaging in geology, with experience built up over the last decade. Our expertise includes the scanning of near-vertical cliff sections (such as geological outcrops and mine faces), tunnels, buildings facades, as well as spectral analysis of drill cores and samples. The method is increasingly valuable for a broadening range of applications within our project portfolio, including CO2 sequestration, characterising clay materials in subterranean storage sites for hazardous waste, mapping economically-viable materials in historic mine waste, geohazards, cultural heritage and in the natural world.

 

Hyperspectral imaging of carbonate quarry in Cantabria, Spain, showing mapped material classes (limestone, dolomite types, calcite etc) overlaid on photorealistic 3D model using in-house LIME software (see Buckley et al., 2013).

 

A fundamental part of the VOG Group’s work has been the tight coupling of the spectral mapping results with geometric methods, such as lidar and photogrammetry. In-house software allows registration of the two data types and visualisation of multi-layered textured models. Linking the two allows material distributions to be obtained in 3D space, which makes it possible to measure and perform quantitative analysis, as well as develop novel visual products to communicate end results.

 

Overlay of hyperspectral results on photorealistic lidar model. Left: mapped rock types; right: vector class representing carbonate nodules projected into 3D space for area calculation. Height of cliff is c. 10 m. Image based on Kurz et al. (2013).

 

Using portable imaging equipment, hyperspectral methods offer added value both in the field and in the laboratory, by allowing non-contact and high resolution identification and description of material.

 

Map of iron content in cross section through historic mine waste material, for potential recycling of economically-viable ore. Image based on Denk et al. (2015), collaboration with the Department of Geography and Geoscience, Martin Luther University Halle-Wittenberg, funded through the Research Council of Norway and DAAD.

 

Related publications (Journal papers)

DENK, M., GLÄßER, C., KURZ, T.H., BUCKLEY, S.J., and DRISSEN, P., 2015. Mapping of iron and steelwork by-products using close range hyperspectral imaging: A case study in Thuringia, Germany. European Journal of Remote Sensing, 48: 489-509. doi:10.5721/EuJRS20154828.

SIMA, A.A., BUCKLEY, S.J., KURZ, T.H. and SCHNEIDER, D., 2014. Semi-automated registration of close range hyperspectral scans using oriented digital camera imagery and a 3D model. Photogrammetric Record, 29(145): 10-29. doi:10.1111/phor.12049.

BUCKLEY, S.J., KURZ, T.H., HOWELL, J.A. and SCHNEIDER, D., 2013. Terrestrial lidar and hyperspectral data fusion products for geological outcrop analysis. Computers & Geosciences, 54: 249-258. doi:10.1016/j.cageo.2013.01.018.

SIMA, A.A. and BUCKLEY, S.J., 2013. Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images. Remote Sensing, 5(5): 2037-2056. doi:10.3390/rs5052037.

KURZ, T.H., BUCKLEY, S.J. and HOWELL, J.A., 2013. Close-range hyperspectral imaging for geological field studies: workflow and methods. International Journal of Remote Sensing, 34(5): 1798-1822. doi:10.1080/01431161.2012.727039.

SIMA, A.A., BUCKLEY, S.J., KURZ, T.H., and SCHNEIDER, D., 2012. Semi-automatic integration of panoramic hyperspectral imagery with photorealistic lidar models. Photogrammetrie, Fernerkundung, Geoinformation, 2012(4): 439-450.

KURZ, T.H., DEWIT, J., BUCKLEY, S.J., THURMOND, J.B., HUNT, D.W. and SWENNEN, R., 2012. Hyperspectral image analysis of different carbonate lithologies (limestone, karst and hydrothermal dolomites): the Pozalagua Quarry case study (Cantabria, North-west Spain). Sedimentology, 59(2): 623-645. doi:10.1111/j.1365-3091.2011.01269.x.

KURZ, T.H., BUCKLEY, S.J., HOWELL, J.A. and SCHNEIDER, D., 2011. Integration of panoramic hyperspectral imaging with terrestrial lidar data. Photogrammetric Record, 26(134): 212-228. doi:10.1111/j.1477-9730.2011.00632.x.

 

Related publications (Conference proceedings papers)

DENK, M., GLÄßER, C., KURZ, T.H., BUCKLEY, S.J., MUDERSBACH, D., and DRISSEN, P., 2014. Detection of raw materials in waste sites from iron and steel production using multi-scale spectral and lidar measurement: Case study from Thuringia, Germany. In: Humair F., Matasci B., et al. (eds.). Vertical Geology, from remote sensing to 3D geological modelling. Proceedings of the first Vertical Geology Conference, 5 - 7 February 2014, University of Lausanne, Switzerland, 33-36.

KURZ, T.H., BUCKLEY, S.J., and HOWELL, J.A., 2014. State of the art of ground-based hyperspectral imaging in geo-science applications. In: Humair F., Matasci B., et al. (eds.). Vertical Geology, from remote sensing to 3D geological modelling. Proceedings of the first Vertical Geology Conference, 5 - 7 February 2014, University of Lausanne, Switzerland, 3-6.

KURZ, T.H., BUCKLEY, S.J., and HOWELL, J.A., 2012. Close range hyperspectral imaging integrated with terrestrial lidar scanning applied to rock characterisation at centimetre scale. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 39(B5): 417-422. doi:10.5194/isprsarchives-XXXIX-B5-417-2012.

BUCKLEY, S.J., KURZ, T.H., and SCHNEIDER, D., 2012. The benefits of terrestrial laser scanning and hyperspectral data fusion products. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 39(B7): 541-546. doi:10.5194/isprsarchives-XXXIX-B7-541-2012.

KURZ, T.H., BUCKLEY, S.J., SCHNEIDER, D., SIMA, A.A., and HOWELL, J.A., 2011. Ground-based hyperspectral and lidar scanning: a complementary method for geoscience research. International Association of Mathematical Geosciences Conference, 5-9th September, Salzburg, Austria.

KURZ, T.H., BUCKLEY, S.J., HOWELL, J.A., and SCHNEIDER, D., 2009. Close range hyperspectral and lidar data integration for geological outcrop analysis. Proceedings of First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009 (WHISPERS '09), 26-28th August, 2009, Grenoble, France. doi:10.1109/WHISPERS.2009.5288998.

KURZ, T.H., BUCKLEY, S.J., HOWELL, J.A., and SCHNEIDER, D., 2008. Geological outcrop modelling and interpretation using ground based hyperspectral and laser scanning data fusion. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B8): 1229-1234.

Contact

For more information, please contact
Dr Simon Buckley or Dr Tobias Kurz.

 

Our collaborators

  • BG Group
  • Martin Luther University Halle-Wittenberg
  • MIBRAG
  • NAGRA
  • NEO
  • NPD
  • PDO
  • Research Council of Norway
  • Statoil
  • Swisstopo
  • University College Dublin
  • University of Bergen
  • University of Oslo
cp: 2017-12-15 12:18:19