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TAILING MODELLED AND MEASURED SPECTRUM FOR MINE TAILING MAPPING IN TUNISIAN SEMI-ARID CONTEXT

RME. TAILING MODELLED AND MEASURED SPECTRUM FOR MINE TAILING MAPPING IN TUNISIAN SEMI-ARID CONTEXT. N. Mezned 1,2 , S. Abdeljaouad 1 , M. R. Boussema 3. 1 RME/FST, ( Tunis , Tunisia ). 2 Isepbg ( Tunis , Tunisia ). 3 LTSIRS/ENIT, ( Tunis , Tunisia ). Context.

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TAILING MODELLED AND MEASURED SPECTRUM FOR MINE TAILING MAPPING IN TUNISIAN SEMI-ARID CONTEXT

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  1. RME TAILING MODELLED AND MEASURED SPECTRUM FOR MINE TAILING MAPPING IN TUNISIAN SEMI-ARID CONTEXT N. Mezned1,2, S. Abdeljaouad1 , M. R. Boussema3 1RME/FST, (Tunis, Tunisia) 2Isepbg (Tunis, Tunisia) 3 LTSIRS/ENIT, (Tunis, Tunisia) 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  2. Context Mine tailing impact Soils Ecologic Systems Water quality Vegetation Ba/Fl HammamZriba mine site Tunisia Pb/Zn Jebel Hallouf-Bouaouane mine site Tunisia Pb/Zn Jebel Ressas mine site Tunisia Pb/Zn Jebel Ressas mine site Tunisia Human life 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  3. Context • North of Tunisia: several types of mine (Pb, Zn, Fl, …, etc.) • Mejerda river watershed: precious source of water Environment risks a a a 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  4. Context • Necessity of mine tailing mapping • Advantages: low costs • spatial coverage • Remotesensing: satellite data 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  5. OUTLINES • Context • Study area and problematic • The used data • The proposed approach • Experimental results • Conclusion and perspectives 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  6. Study area and problematic Mine tailings KassabWady JebelHallouf-Bouaouane Mine 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july Mejerda River

  7. Study area and problematic JebelHallouf-Bouaouane • 188 mille tonnes of metal (84 Pb et 64 Zn) in 1952 • Abandonedsince 1986 Importantquantityoftailing Mine activity Environmentimpact 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july Terrain subsidence

  8. OUTLINES • Context • Study area and problematic • Work positioning • The used data • The proposed approach • Experimental results • Conclusion and perspectives 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  9. 3) Work positioning • Passive Remote sensed data • Multispectral data • (landsat TM, ETM+, ASTER, etc.) • Hyperspectral data (Hyperion,HyMap, etc.) Mine site mappingusingHyMap(Taylor and Vukovic, 2001) and Probe data (Staenz et al., 2003) • Mineral mapping using Landsat TMdata, (Zhang et al., 2007) + • Mineral mapping using Landsat ETM+ data and field spectra measured with ASD spectroradiometer , (Liu et al., 2003) fieldmeasuredspectra or spectra from publicly library 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  10. 3) Work positioning • Passive Remote sensed data • Problems : • Mine tailing risks on environment and human health • Objective: • Mine tailing mapping using multispectral data • Tailing modelledspectra with respect to the field truth SMA overcome the luck of spectroradimeter 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  11. OUTLINES • Context • Study area and problematic • Work positioning • The used data • The proposed approach • Experimental results • Conclusion and perspectives 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  12. 3) The used data • Multispectral data: Landsat ETM+ • 6 bands, • 30 m, Landsat ETM+ (05/03/2000) • Publically library: JPL spectral data • Field campaign data: Mineral identification and abundance estimation • 18 samples/dyke = 54 tailing measurements, 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  13. OUTLINES • Context • Study area: Soil salinity, the problematic • The used data • Work positioning • The proposed approach • Experimental results • Conclusion and perspectives 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  14. 5) The proposed approach • Tailing modeling spectrum for ETM+ classification: spectral unmixing 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  15. 5) The proposed approach • Tailing modeling spectrum for ETM+ classification: spectral unmixing • Vegetation • Soils • Tailing component spectrum? • Direct mean: Measured by spectroradiometer • Indirect mean: Modelled with respect of field truth 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  16. 5) The proposed approach • Tailing modeling spectrum for ETM+ classification: spectral unmixing • Linear spectral unmixing Vegetation Soils Mine tailings • 3 fraction maps • Measured • spectrum • Modelled spectrum 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  17. 5) The proposed approach • Tailing modeling spectrum for ETM+ classification: spectral unmixing • Comparison • RMS errors 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  18. OUTLINES • Context • Study area: Soil salinity, the problematic • The used data • Work positioning • The proposed approach • Experimental results • Conclusion and perspectives 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  19. 5) Experimental results Tailing modelledspectrum: SMA Quartz Kaolinite Pyrite JPL library Resampledspectra to Landsat ETM+ band passes linearcombination Galena Sphalerite Hematite Calcite Goethite TailingModelledspectrum N. Mezned 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  20. 5) Experimental results Tailing mlodelled spectrum: SMA Sampling 18 samplesfor eachdyke = 54 samples Laboratoryanalysis Identification and % of minerals - X Ray Diffraction XRD - Calcimetry N. Mezned 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july - Counting on polished sections

  21. 5) Experimental results ETM+ Linear spectral unmixing • We used both ASD measured and SMA modelled spectra in the classification processes, Mine tailing fraction maps generated from the ETM+ linear spectral unmixing using: (a) the measured spectrumwith ASD spectroradiometer and (b) the modelled tailing spectrum and (c) N. Mezned 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  22. 5) Experimental results Classification validation 99.6 % of pixels have an RMS errors: < 2.6 10-5 using the modelled spectrum, tailing map < 1.9 10-5 using the measured spectrum. < 3.3 10-5 using derived ETM+ spectrum N. Mezned 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  23. 5) Experimental results Classification validation 99.6 % of pixels have an RMS errors: < 2.6 10-5 using the modelled spectrum, tailing map < 1.9 10-5 using the measured spectrum. < 3.3 10-5 using derived ETM+ spectrum N. Mezned 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  24. 5) Experimental results Classification validation 99.6 % of pixels have an RMS errors: < 2.6 10-5 using the modelled spectrum, tailing map < 1.9 10-5 using the measured spectrum. < 3.3 10-5 using derived ETM+ spectrum N. Mezned 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  25. OUTLINES • Context • Study area: Soil salinity, the problematic • The used data • Work positioning • The proposed approach • Experimental results • Conclusion and perspectives 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  26. 6) Conclusion and perspectives Conclusion • The results comparison indicate that the modelled spectrum can even better characterize the tailings in the case of semi-arid context, • The SMA approach can be an optimal solution to replace the lack of the spectroradiometer and can be applied successfully to multispectral data analysis, particularly those acquired during previous periods. Perspectives • We plan for more campaign, • We propose to test the SMA approach for different mining sites. 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

  27. Thanks for your attention 2011 IEEE InternaionalGeoscience and Remote Sensing Symposium- 29 july

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