Your SlideShare is downloading. ×
0
RME                 TAILING MODELLED AND              MEASURED SPECTRUM FOR                MINE TAILING MAPPING IN        ...
Context                                                    Mine tailing impact                Soils           Vegetation E...
Context North of Tunisia: several types of mine(Pb, Zn, Fl, …, etc.) Mejerda river watershed: precioussource of water   ...
Context Necessity of mine tailing mapping Advantages: low costs              spatial coverage             Remote sensing...
OUTLINES1) Context2) Study area and problematic3) The used data4) The proposed approach5) Experimental results6) Conclusio...
2) Study area and problematic                                        Mine tailings             Kassab Wady                ...
2) Study area and problematic             Jebel Hallouf-Bouaouane              188 mille tonnes of metal (84 Pb et 64 Zn)...
OUTLINES1) Context2) Study area and problematic3) Work positioning4) The used data5) The proposed approach6) Experimental ...
3) Work positioning        Passive Remote sensed data         Multispectral data                                    Hyper...
3) Work positioning        Passive Remote sensed data              Problems :                • Mine tailing risks on env...
OUTLINES1) Context2) Study area and problematic3) Work positioning4) The used data5) The proposed approach6) Experimental ...
3) The used data                        Multispectral data: Landsat ETM+                             • 6 bands,          ...
OUTLINES1) Context2) Study area: Soil salinity, the problematic3) The used data4) Work positioning5) The proposed approach...
5) The proposed approach        Tailing modeling spectrum for ETM+          classification: spectral unmixing   ETM+ image...
5) The proposed approach        Tailing modeling spectrum for ETM+          classification: spectral unmixing   ETM+ image...
5) The proposed approach        Tailing modeling spectrum for ETM+          classification: spectral unmixing   ETM+ image...
5) The proposed approach        Tailing modeling spectrum for ETM+          classification: spectral unmixing   ETM+ image...
OUTLINES1) Context2) Study area: Soil salinity, the problematic3) The used data4) Work positioning5) The proposed approach...
5) Experimental results    1.   Tailing modelled spectrum: SMA               Hematite                  JPL library        ...
5) Experimental results    1.   Tailing mlodelled spectrum: SMA               Sampling         18 samples for each dyke = ...
5) Experimental results    2.   ETM+ Linear spectral unmixing             • We used both ASD measured and SMA modelled spe...
5) Experimental results    2.   Classification validation                    99.6 % of pixels have an RMS errors:         ...
5) Experimental results    2.   Classification validation                    99.6 % of pixels have an RMS errors:         ...
5) Experimental results    2.   Classification validation                    99.6 % of pixels have an RMS errors:         ...
OUTLINES1) Context2) Study area: Soil salinity, the problematic3) The used data4) Work positioning5) The proposed approach...
6) Conclusion and perspectivesConclusion The results comparison indicate that the modelled spectrum can evenbetter charac...
Thanks for your         attentionN. Mezned   2011 IEEE Internaional Geoscience and   27             Remote Sensing Symposi...
Upcoming SlideShare
Loading in...5
×

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

374

Published on

Published in: Travel, Technology
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
374
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
4
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Transcript of "TAILING MODELLED AND MEASURED SPECTRUM FOR MINE TAILING MAPPING IN TUNISIAN SEMI-ARID CONTEXT.pptx"

  1. 1. RME TAILING MODELLED AND MEASURED SPECTRUM FOR MINE TAILING MAPPING IN TUNISIAN SEMI-ARID CONTEXT N. Mezned1,2, S. Abdeljaouad1 , M. R. Boussema3 1 RME/FST, 2Isepbg 3 LTSIRS/ENIT, (Tunis, Tunisia) (Tunis, Tunisia) (Tunis, Tunisia) 2011 IEEE Internaional Geoscience and RemoteN. Mezned 1 Sensing Symposium- 29 july
  2. 2. Context Mine tailing impact Soils Vegetation Ecologic Systems Water qualityBa/Fl Hammam Zriba mine site Pb/Zn Jebel Hallouf-Bouaouane mine Pb/Zn Jebel Ressas mine site Tunisia Pb/Zn Jebel Ressas mine site Tunisia Tunisia site Tunisia Human life 2011 IEEE Internaional Geoscience and N. Mezned Remote Sensing Symposium- 29 july 2
  3. 3. Context North of Tunisia: several types of mine(Pb, Zn, Fl, …, etc.) Mejerda river watershed: precioussource of water a Environment risks a a 2011 IEEE Internaional Geoscience and N. Mezned Remote Sensing Symposium- 29 july 3
  4. 4. Context Necessity of mine tailing mapping Advantages: low costs spatial coverage Remote sensing: satellite data 2011 IEEE Internaional Geoscience and N. Mezned Remote Sensing Symposium- 29 july 4
  5. 5. OUTLINES1) Context2) Study area and problematic3) The used data4) The proposed approach5) Experimental results6) Conclusion and perspectives 2011 IEEE Internaional Geoscience and N. Mezned Remote Sensing Symposium- 29 july 5
  6. 6. 2) Study area and problematic Mine tailings Kassab Wady Jebel Hallouf-Bouaouane Mine Mejerda River N. Mezned 2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july 6
  7. 7. 2) Study area and problematic Jebel Hallouf-Bouaouane  188 mille tonnes of metal (84 Pb et 64 Zn) in 1952  Abandoned since 1986 Important quantity of tailing Mine activity Environment impact Terrain subsidence N. Mezned 2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july 7
  8. 8. OUTLINES1) Context2) Study area and problematic3) Work positioning4) The used data5) The proposed approach6) Experimental results7) Conclusion and perspectives N. Mezned 2011 IEEE Internaional Geoscience and 8 Remote Sensing Symposium- 29 july
  9. 9. 3) Work positioning  Passive Remote sensed data Multispectral data Hyperspectral data (landsat TM, ETM+, ASTER, etc.) (Hyperion,HyMap, etc.) Mine site mapping using HyMapMineral mapping using Landsat TM (Taylor and Vukovic, 2001) anddata, (Zhang et al., 2007) Probe data (Staenz et al., 2003) Mineral mapping using Landsat ETM+ data and field spectra measured with + ASD spectroradiometer , (Liu et al., 2003) field measured spectra or spectra from publicly library N. Mezned 2011 IEEE Internaional Geoscience and 9 Remote Sensing Symposium- 29 july
  10. 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 modelled spectra with respect to the field truth SMA overcome the luck of spectroradimeter N. Mezned 2011 IEEE Internaional Geoscience and 10 Remote Sensing Symposium- 29 july
  11. 11. OUTLINES1) Context2) Study area and problematic3) Work positioning4) The used data5) The proposed approach6) Experimental results7) Conclusion and perspectives N. Mezned 2011 IEEE Internaional Geoscience and 11 Remote Sensing Symposium- 29 july
  12. 12. 3) The used data  Multispectral data: Landsat ETM+ • 6 bands, • 30 m, Landsat ETM+  Publically library: JPL spectral data (05/03/2000)  Field campaign data: Mineral identification and abundance estimation • 18 samples/dyke = 54 tailing measurements, N. Mezned 2011 IEEE Internaional Geoscience and 12 Remote Sensing Symposium- 29 july
  13. 13. OUTLINES1) Context2) Study area: Soil salinity, the problematic3) The used data4) Work positioning5) The proposed approach6) Experimental results7) Conclusion and perspectives N. Mezned 2011 IEEE Internaional Geoscience and 13 Remote Sensing Symposium- 29 july
  14. 14. 5) The proposed approach Tailing modeling spectrum for ETM+ classification: spectral unmixing ETM+ image endmember pre- Classification Validation processing selection N. Mezned 2011 IEEE Internaional Geoscience and 14 Remote Sensing Symposium- 29 july
  15. 15. 5) The proposed approach Tailing modeling spectrum for ETM+ classification: spectral unmixing ETM+ image endmember pre- Classification Validation processing selection Vegetation Soils Tailing component spectrum? Direct mean: Measured by spectroradiometer Indirect mean: Modelled with respect of field truth N. Mezned 2011 IEEE Internaional Geoscience and 15 Remote Sensing Symposium- 29 july
  16. 16. 5) The proposed approach Tailing modeling spectrum for ETM+ classification: spectral unmixing ETM+ image endmember pre- Classification Validation processing selection Linear spectral unmixing 1. Vegetation 3 fraction maps 2. Soils 3. Mine tailings Measured Modelled spectrum spectrum N. Mezned 2011 IEEE Internaional Geoscience and 16 Remote Sensing Symposium- 29 july
  17. 17. 5) The proposed approach Tailing modeling spectrum for ETM+ classification: spectral unmixing ETM+ image endmember pre- Classification Validation processing selection Comparison RMS errors N. Mezned 2011 IEEE Internaional Geoscience and 17 Remote Sensing Symposium- 29 july
  18. 18. OUTLINES1) Context2) Study area: Soil salinity, the problematic3) The used data4) Work positioning5) The proposed approach6) Experimental results7) Conclusion and perspectives N. Mezned 2011 IEEE Internaional Geoscience and 18 Remote Sensing Symposium- 29 july
  19. 19. 5) Experimental results 1. Tailing modelled spectrum: SMA Hematite JPL library Kaolinite Goethite Pyrite Re sampled spectra to Landsat ETM+ band passes Galena linear combination Quartz Calcite Sphalerite Tailing Modelled spectrum N. Mezned 2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july 19
  20. 20. 5) Experimental results 1. Tailing mlodelled spectrum: SMA Sampling 18 samples for each dyke = 54 samples Laboratory analysis - X Ray Diffraction XRD Identification - Calcimetry and - Counting on polished sections % of minerals N. Mezned 2011 IEEE Internaional Geoscience and 20 Remote Sensing Symposium- 29 july
  21. 21. 5) Experimental results 2. 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 spectrum with ASD spectroradiometer and (b) the modelled tailing spectrum and (c) 21 N. Mezned 2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
  22. 22. 5) Experimental results 2. 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 22 N. Mezned 2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
  23. 23. 5) Experimental results 2. 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 23 N. Mezned 2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
  24. 24. 5) Experimental results 2. 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 24 N. Mezned 2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
  25. 25. OUTLINES1) Context2) Study area: Soil salinity, the problematic3) The used data4) Work positioning5) The proposed approach6) Experimental results7) Conclusion and perspectives N. Mezned 2011 IEEE Internaional Geoscience and 25 Remote Sensing Symposium- 29 july
  26. 26. 6) Conclusion and perspectivesConclusion The results comparison indicate that the modelled spectrum can evenbetter characterize the tailings in the case of semi-arid context, The SMA approach can be an optimal solution to replace the lack of thespectroradiometer and can be applied successfully to multispectral dataanalysis, particularly those acquired during previous periods.PerspectivesWe plan for more campaign, We propose to test the SMA approach for different mining sites. N. Mezned 2011 IEEE Internaional Geoscience and 26 Remote Sensing Symposium- 29 july
  27. 27. Thanks for your attentionN. Mezned 2011 IEEE Internaional Geoscience and 27 Remote Sensing Symposium- 29 july
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×