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TAILING MODELLED AND MEASURED SPECTRUM FOR
MINE TAILING MAPPING INTUNISIAN SEMI-ARID CONTEXT
N. Mezned1,2, S. Abdeljaouad1 , M. R. Boussema3
12011 IEEE Internaional Geoscience and Remote
Sensing Symposium- 29 julyN. Mezned
1 RME/FST, (Tunis, Tunisia)
3 LTSIRS/ENIT, (Tunis, Tunisia)
2 Isepbg (Tunis, Tunisia)
RME
Context
22011 IEEE Internaional Geoscience and
Remote Sensing Symposium- 29 julyN. Mezned
Mine tailing impact
Water qualitySoils Vegetation Ecologic Systems
Ba/Fl Hammam Zriba 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
Context
Mejerda river watershed: precious source of water
3
North of Tunisia: several types of mine (Pb, Zn, Fl, …, etc.)
Environment risksa
a
a
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 julyN. Mezned
Context
4
Necessity of mine tailing mapping
Advantages: low costs spatial coverage
Remote sensing: satellite data2011 IEEE Internaional Geoscience and
Remote Sensing Symposium- 29 julyN. Mezned
1) Context
2) Study area and problematic
3) The used data
4) The proposed approach
5) Experimental results
6) Conclusion and perspectives
OUTLINES
52011 IEEE Internaional Geoscience and
Remote Sensing Symposium- 29 julyN. Mezned
2) Study area and problematic
6
Mine tailings
Kassab Wady
Mejerda River
Jebel Hallouf-Bouaouane Mine
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
2) Study area and problematic
7
188 mille tonnes of metal (84 Pb et 64 Zn) in 1952
Abandoned since 1986
Jebel Hallouf-Bouaouane
Environment impactMine activity
Important quantity of tailing
Terrain subsidence
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
1) Context
2) Study area and problematic
3) Work positioning
4) The used data
5) The proposed approach
6) Experimental results
7) Conclusion and perspectives
OUTLINES
82011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
3) Work positioning
9
Passive Remote sensed data
Multispectral data
(landsat TM, ETM+, ASTER, etc.)
Mineral mapping using Landsat ETM+ data and field spectra measured with ASD spectroradiometer , (Liu et al., 2003)
Mineral mapping using Landsat TM
data, (Zhang et al., 2007)
Mine site mapping using HyMap (Taylor and Vukovic, 2001) and Probe data (Staenz et al., 2003)
Hyperspectral data
(Hyperion,HyMap, etc.)
+field measured spectra
or spectra from publicly library
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
3) Work positioning
10
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
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
1) Context
2) Study area and problematic
3) Work positioning
4) The used data
5) The proposed approach
6) Experimental results
7) Conclusion and perspectives
OUTLINES
112011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
3) The used data
12
Multispectral data: Landsat ETM+
• 6 bands,
• 30 m,
Field campaign data: Mineral identification and abundance estimation
• 18 samples/dyke = 54 tailing measurements,
Landsat ETM+
(05/03/2000) Publically library: JPL spectral data
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
1) Context
2) Study area: Soil salinity, the problematic
3) The used data
4) Work positioning
5) The proposed approach
6) Experimental results
7) Conclusion and perspectives
OUTLINES
132011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
5) The proposed approach
14
Tailing modeling spectrum for ETM+ classification: spectral unmixing
ETM+ image pre-
processing
endmember select
ion
Classification
Validation
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
5) The proposed approach
15
Tailing modeling spectrum for ETM+ classification: spectral unmixing
ETM+ image pre-
processing
endmember select
ion
Classification
Validation
Tailing component spectrum?
Direct mean: Measured by spectroradiometer
Indirect mean: Modelled with respect of field truth
Vegetation Soils
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
5) The proposed approach
16
Tailing modeling spectrum for ETM+ classification: spectral unmixing
ETM+ image pre-
processing
endmember select
ion
Classification
Validation
Linear spectral unmixing
1. Vegetation2. Soils3. Mine tailings
3 fraction maps
Measured spectrum
Modelled spectrum
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
5) The proposed approach
17
Tailing modeling spectrum for ETM+ classification: spectral unmixing
ETM+ image pre-
processing
endmember select
ion
Classification
Validation
Comparison RMS errors
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
1) Context
2) Study area: Soil salinity, the problematic
3) The used data
4) Work positioning
5) The proposed approach
6) Experimental results
7) Conclusion and perspectives
OUTLINES
182011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
19
5) Experimental results
1. Tailing modelled spectrum: SMA
Re sampled spectra to Landsat ETM+ band passes
linear combination
JPL library
Pyrite
Quartz
Calcite
Galena
Hematite
Goethite
Kaolinite
Sphalerite
Tailing Modelled spectrum
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
20
5) Experimental results
1. Tailing mlodelled spectrum: SMA
Sampling
18 samples for each dyke = 54 samples
- X Ray Diffraction XRD
- Counting on polished sections
- CalcimetryIdentification
and
% of minerals
Laboratory analysis
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
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)
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
22
5) Experimental results
2. Classification validation
< 2.6 10-5
< 3.3 10-5
< 1.9 10-5
99.6 % of pixels have an RMS errors:
using the modelled spectrum,
using the measured spectrum.
using derived ETM+ spectrum
tailing map
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
23
5) Experimental results
2. Classification validation
< 2.6 10-5
< 3.3 10-5
< 1.9 10-5
using the modelled spectrum,
using the measured spectrum.
using derived ETM+ spectrum
tailing map
99.6 % of pixels have an RMS errors:
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
24
5) Experimental results
2. Classification validation
< 2.6 10-5
< 3.3 10-5
< 1.9 10-5
using the modelled spectrum,
using the measured spectrum.
using derived ETM+ spectrum
tailing map
99.6 % of pixels have an RMS errors:
2011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
1) Context
2) Study area: Soil salinity, the problematic
3) The used data
4) Work positioning
5) The proposed approach
6) Experimental results
7) Conclusion and perspectives
OUTLINES
252011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
6) Conclusion and perspectives
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.
Conclusion
Perspectives
We plan for more campaign,
We propose to test the SMA approach for different mining sites.
262011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned
Thanks for your attention
272011 IEEE Internaional Geoscience and Remote Sensing Symposium- 29 july
N. Mezned