| More

A preliminary approach on the use of satellite hyperspectral data for geological mapping

Views: 87 Downloads: 57
G. K. Nikolakopoulos, D. A. Vaiopoulos, G. A. Skianis
G. K. Nikolakopoulos, D. A. Vaiopoulos, G. A. Skianis


During the last decades remote sensing imagery has contributed significantly to mineral exploration. Motivated by the increasing importance of hyperspectral remote sensing, this study investigates the potential of the current-generation satellite hyperspectral data for geological mapping. A narrow-band Hyperion image, acquired in summer 2001, was used. The study area is situated at Milos island. Two different approaches were used for the reduction of the Hyperion bands. First, on the basis of histogram statistics the uncalibrated bands were selected and removed. Then the Minimum Noise Fraction was used to classify the bands according to their signal to noise ratio. The noisiest bands were removed and sixty bands were selected for further processing. In order to make meaningful comparisons between image spectra and laboratory reflectance spetra, the image radiance values must be corrected (calibrated) to reflectance by removing the atmospheric effects. Atmospheric corrections techniques were applied to the selected Hyperion bands. The comparison of the Hyperion hyperspectral data with the JPL spectral library gave quite encouraging results. Further processing of the data has to be done using the image analysis algorithms that have been developed specifically to exploit the extensive information contained in hyperspectral imagery.


Hyperion; Milos; Atmospheric corrections; Spectral libraries

Full Text:



Adams, J. B., Smith, M. O., and Johnson, P.E., 1986. Spectral mixture modelling: A new analysis of rock and soil types at the Viking Lander 1 site, Journal of Geophysical Research, 91(B8), 8090-8112.

Ben-Dor, E., Patkin, K., Banin, Α., and Karnieli, Α., 2002. Mapping of several soil properties using DAIS-7915 hyperspectral scanner data — a case study over soils in Israel, International Journal of Remote Sensing 23 (6), 1043-1062.

Boardman, J. W., 1989. Inversion of imaging spectrometry data using singular value decomposition, Proceedings of the Twelfth Canadian Symposium on Remote Sensing, 4., 2069-2072.

Boardman, J. W., Kruse, F. Α., and Green, R. O., 1995. Mapping target signatures via partial unmixing of AVIRIS data". In Summaries of the Fifth JPL Airborne Earth Science Worhhop, JPL Publication 95-1, v. 1, 23-26pp.

Clark, R. N., Swayze, G. Α., Gallagher, Α., Gorelick, N., and Kruse, F. Α., 1991. Mapping with imaging spectrometer data using the complete band shape leastsquares algorithm simultaneously fit to multiple spectral features from multiple materials. In Proceedings of the Third Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, JPL Publication 91-28, 2-3pp.

Cròsta, A. P., Sabine, C, & Taranik, J. V., 1998. Hydrothermal alteration mapping at Bodie, California, using AVIRIS hyperspectral data, Remote Sensing of Environment, 65(3), 309-319.

Debba, P., van Ruitenbeek, F.J.A., van der Meer, F.D., Carranza, E.J.M., and Stein, Α., 2005. Optimal field sampling for targeting minerals using hyperspectral data, Remote Sensing of Environment 99 (2005) 373 - 386.

Envi, 2005. Envi User's Manual, Research Systems Ine, Pearl East Circle.

Ganas, Ath., and Ferrier, Graham, 2002. Mapping of diagnostic clay mineralsin epithermal gold deposits of Milos Island (Greece) using hyperspectral data from the DAIS airborne radiometer, 6th Pan-Hellenic Geographical Congress, Thessaloniki, Volume II, 118 - 126pp.

Green, A.A, Berman, M., Switzer, P., and Craig, M.D., 1988. A transformation for ordering multispectral data in terms of image quality with implications for noise removal, IEEE Transactions on geoscience and remote sensing, 26, 65-74.

Haboudane, Dr, Miller, J.R., Pattey, E., Zarco-Tejada, P.J., and Strachan, LB., 2004. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture, Remote Sensing of Environment 90 (2004) 337-352.

Hubbard E.B., and Crowley, J.K., 2005. Mineral mapping on the Chilean-Bolivian Altipiano using co-orbital ALI, ASTER and Hyperion imagery: Data dimensionality issues and solutions, Remote Sensing of Environment 99 (2005), 173 - 186.

Kruse, F. Α., and Boardman, J. W., 1997. Characterization and mapping of kimberlites and related diatremes in Utah, Colorodo, and Wyoming, USA, using the airborne visible/infrared imaging spectrometer (AVIRIS), ERIM Proceedings of the 12th international conference on applied geologic remote sensing, 21-2 8pp.

Liao, L., Jarecke, P., Gleichauf, D., and Hedman, T., 2000. Performance Characterization of the Hyperion Imaging Spectrometer Instrument, Proc. of SPIE, 4101, 22-26.

Lewis, M., Jooste, V., and de Gasparis, A.A., 2001. Discrimination of Arid Vegetation with Airborne Multispectral Scanner Hyperspectral Imagery, IEEE Transactions On Geoscience And Remote Sensing, 39(7), 1471-1479.

Richards, J.A., and Jia, X., 1999. Remote Sensing Digital Image Analysis, an Introduction, Third Edition. Springer-Verlag: Berlin.

Richter, R., 1996. "A spatially adaptive fast atmospheric correction algorithm" Int. J. Remote Sensing, 17, 1201-1214.

Richter, R., 1996. "Atmospheric correction of satellite data with haze removal including a haze/clear transition region", Computers & Geosciences, 22, 675-681.

Richter R., 1998. "Correction of satellite imagery over mountainous terrain", Applied Optics, 37, 4004-4015.

Rowan, L. C, Crowley, J. K., Schmidt, R. G., Ager, C. M., and Mars, J. C. 2000. Mapping hydrothermally altered rocks by analyzing hyperspectral image (AVIRIS) data of forested areas in the Southeastern United States, Journal of Geochemical Exploration, 68(3), 145- 166.

Sabins, F. F., 1999. Remote sensing for mineral exploration, Ore Geology Reviews, 14 (Issues 3 -4), 157-183.

Shrestha, D.P., Margate, D.E., van der Meer, F., and Anh, H.V., 2005. Analysis and classification of hyperspectral data for mapping land degradation: An application in southern Spain, International Journal of Applied Earth Observation and Geoinformation, 7 (2005), 85-96.

TNTMIPS, 2005. Introduction to Hyperspectral Imaging, Microimages, Inc. Lincoln, Nebraska, USA, 24pp.

Tomoaki M., Huete Α., and Yoshioka, H., 2006. An empirical investigation of cross-sensor relationships of NDVI and red/near-infrared reflectance using EO-1 Hyperion data, Remote Sensing of Environment 100, 223 - 236.

Van der Meer, Freek, 2006. The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery, International Journal of Applied Earth Observation and Geoinformation, 8(2006), 3-17.

Vaughan, R. G., Calvin, W. M., and Taranik, J. V., 2003. SEBASS hyperspectral thermal infrared data: Surface emissivity measurement and mineral mapping, Remote Sensing of Environment, 85(1), 48- 63.

Yuhas, R.H., Goetz, A. F. H., and Boardman, J. W., 1992. Discrimination among semiarid landscape endmembers using the spectral angle mapper (SAM) algorithm. In Summaries of the Third Annual JPL Airborne Geoscience Workshop, JPL Publication 92-14, vol. 1, 147-149pp.


  • There are currently no refbacks.

Copyright (c) 2018 G. K. Nikolakopoulos, D. A. Vaiopoulos, G. A. Skianis

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.