Spectral Signature Characterization and Remote Mapping of Oman Exotic Limestones for Industrial Rock Resource Assessment
Abstract
:1. Introduction
2. The Exotic Limestone of Oman
3. Materials and Methods
3.1. Image Data-Set
3.2. Characterization of Spectral Signature of the Exotic Limestone
3.3. Image Elaboration Methodologies
4. Results
Field and Laboratory Studies
5. Discussion
6. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Sensor Characters | Landsat 7 (ETM+) | VNIR | ASTER SWIR | TIR |
---|---|---|---|---|
Spectral bands with range (µm) | Band1 0.45–0.52 | Band 01 0.52–0.60 Nadir looking | Band 04 1.6–1.7 | Band 10 8.125–8.475 |
Band2 0.52–0.60 | Band 02 0.63–0.69 Nadir looking | Band 05 2.145–2.185 | Band 11 8.475–8.825 | |
Band3 0.63–0.69 | Band 03N 0.76–0.86 Nadir looking | Band 06 2.185–2.225 | Band 12 8.925–9.275 | |
Band4 0.77–0.90 | Band 03B 0.76–0.86 Backward looking | Band 07 2.235–2.285 | Band 13 10.25–10.95 | |
Band5 1.55–1.75 | Band 08 2.295–2.365 | Band 14 10.95–11.65 | ||
Band6 10.40-12.50 * | Band 09 2.36–2.43 | |||
Band7 2.09–2.35 | ||||
Band8 0.52-0.90 ** | ||||
Spatial Resolution (m) | 30 | 15 | 30 | 90 |
Swath width (km) | 180 | 60 | 60 | 60 |
Radiometric Resolution (bits) | 8 | 8 | 8 | 12 |
Cross Track Pointing | ±318 km (±24 deg) | ±116 km (±8.55 deg) | ±116 km (±8.55 deg) |
Carbonate Band | Calcite * Absorption (µm) | Exotic Limestones Absorption (µm) | Dolomite * Absorption (µm) | Dolostones Absorption (µm) |
---|---|---|---|---|
1 | 2.530–2.541 | 2.491 | 2.503–2.518 | 2.472 |
2 | 2.333–2.340 | 2.341 | 2.312–2.322 | 2.328 |
3 | 2.254–2.272 | - | 2.234–2.248 | - |
4 | 2.167–2.179 | 2.154 | 2.150–2.170 | 2.144 |
5 | 1.974–1.995 | 1.992 | 1.971–1.979 | 1.981 |
6 | 1.871–1.885 | 1.875 | 1.853–1.882 | 1.863 |
7 | 1.753–1.885 | 1.752 | 1.735–1.740 | - |
Class | G | P | HD | WG | Ka | Sa | Ma | Sq | Ex | TQ | V | Total | User’s Accuracy |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
(a) Confusion matrix of MLC algorithm | |||||||||||||
Unclassified | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | |
G | 100.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 7.95 | 100.00 |
P | 0.00 | 100.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 12.61 | 100.00 |
HD | 0.00 | 0.00 | 100.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.18 | 0.00 | 9.27 | 89.89 |
WG | 0.00 | 0.00 | 0.00 | 100.00 | 0.65 | 0.00 | 0.00 | 0.00 | 0.00 | 2.12 | 0.00 | 6.60 | 98.40 |
Ka | 0.00 | 0.00 | 0.00 | 0.00 | 99.35 | 0.00 | 0.00 | 0.00 | 0.00 | 0.23 | 0.00 | 4.33 | 100.00 |
Sa | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 100.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 3.26 | 100.00 |
Ma | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 98.92 | 0.00 | 0.00 | 0.00 | 0.00 | 5.10 | 100.00 |
Sq | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 100.00 | 0.00 | 0.00 | 0.00 | 10.28 | 98.49 |
Ex | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 1.08 | 0.00 | 100.00 | 0.00 | 0.00 | 3.68 | 100.00 |
TQ | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 97.46 | 0.00 | 29.37 | 99.40 |
V | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 100.00 | 7.56 | 100.00 |
Total | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | |
Producer’s accuracy | 100.00 | 100.00 | 100.00 | 99.35 | 100.00 | 98.92 | 100.00 | 100.00 | 97.46 | 100.00 | 100.00 | ||
Overall accuracy = 99.15%; Kappa coefficient = 0.99 | |||||||||||||
(b) Confusion matrix of SAM algorithm | |||||||||||||
Unclassified | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 2.21 | 0.17 | |
G | 95.28 | 2.31 | 1.06 | 2.11 | 0.00 | 0.43 | 1.89 | 0.00 | 8.05 | 0.00 | 0.00 | 8.49 | 89.20 |
P | 3.32 | 97.69 | 0.00 | 0.00 | 0.00 | 0.00 | 0.27 | 0.00 | 1.53 | 0.00 | 0.00 | 12.65 | 97.37 |
HD | 0.17 | 0.00 | 64.40 | 0.47 | 11.00 | 5.11 | 5.12 | 0.00 | 0.00 | 0.05 | 0.37 | 6.92 | 59.71 |
WG | 0.00 | 0.00 | 0.15 | 77.05 | 11.33 | 0.00 | 0.00 | 13.51 | 0.00 | 3.96 | 0.00 | 7.65 | 44.66 |
Ka | 0.00 | 0.00 | 2.87 | 6.09 | 59.55 | 6.81 | 0.27 | 2.84 | 0.00 | 6.55 | 0.55 | 5.72 | 41.21 |
Sa | 0.35 | 0.00 | 5.13 | 3.75 | 8.74 | 66.81 | 4.85 | 11.08 | 16.09 | 0.00 | 0.55 | 5.29 | 65.15 |
Ma | 0.52 | 0.00 | 19.00 | 0.00 | 0.00 | 0.85 | 81.13 | 0.00 | 11.49 | 0.00 | 0.00 | 6.42 | 65.75 |
Sq | 0.00 | 0.00 | 0.30 | 5.62 | 8.41 | 2.98 | 0.00 | 64.59 | 0.38 | 6.18 | 10.11 | 10.10 | 65.46 |
Ex | 0.35 | 0.00 | 0.15 | 0.00 | 0.00 | 17.02 | 6.47 | 2.57 | 62.45 | 0.00 | 0.00 | 3.46 | 93.92 |
TQ | 0.00 | 0.00 | 6.94 | 4.92 | 0.97 | 0.00 | 0.00 | 5.41 | 0.00 | 83.26 | 1.29 | 26.71 | 85.74 |
V | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 84.93 | 6.42 | 100.00 |
Total | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | |
Producer’s accuracy | 95.28 | 97.69 | 77.05 | 59.55 | 66.81 | 81.13 | 64.59 | 62.45 | 83.26 | 64.40 | 84.93 | ||
Overall accuracy = 79.71%; Kappa coefficient = 0.76 | |||||||||||||
(c) Confusion matrix of SID algorithm | |||||||||||||
Unclassified | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | |
G | 94.06 | 1.32 | 0.15 | 0.00 | 0.00 | 0.00 | 2.16 | 0.81 | 12.64 | 0.00 | 0.00 | 8.31 | 89.97 |
P | 1.92 | 98.68 | 0.00 | 0.00 | 0.00 | 0.00 | 0.27 | 0.00 | 2.30 | 0.00 | 0.00 | 12.70 | 98.03 |
HD | 0.00 | 0.00 | 62.14 | 0.47 | 10.36 | 12.77 | 0.54 | 0.14 | 0.00 | 0.00 | 0.18 | 6.67 | 58.23 |
WG | 0.00 | 0.00 | 0.00 | 75.41 | 19.74 | 0.00 | 0.00 | 5.81 | 0.00 | 5.86 | 0.00 | 7.68 | 34.33 |
Ka | 0.00 | 0.00 | 0.30 | 13.58 | 59.55 | 0.00 | 0.00 | 10.68 | 0.00 | 9.50 | 1.29 | 7.45 | 33.47 |
Sa | 0.35 | 0.00 | 19.31 | 7.49 | 5.18 | 71.91 | 2.96 | 15.41 | 9.96 | 0.00 | 1.29 | 7.01 | 76.67 |
Ma | 0.00 | 0.00 | 8.45 | 0.00 | 0.00 | 2.13 | 86.79 | 0.00 | 14.18 | 0.00 | 0.00 | 5.83 | 84.57 |
Sq | 0.00 | 0.00 | 0.30 | 1.41 | 4.85 | 3.83 | 0.00 | 62.97 | 0.00 | 0.18 | 9.01 | 7.65 | 62.60 |
Ex | 3.67 | 0.00 | 2.41 | 0.00 | 0.00 | 9.36 | 7.28 | 1.08 | 60.92 | 0.00 | 0.18 | 3.53 | 95.82 |
TQ | 0.00 | 0.00 | 6.94 | 1.64 | 0.32 | 0.00 | 0.00 | 3.11 | 0.00 | 84.46 | 0.55 | 26.56 | 85.83 |
V | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 87.50 | 6.61 | 100.00 |
Total | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | |
Producer’s accuracy | 94.06 | 98.68 | 75.41 | 59.55 | 71.91 | 86.79 | 62.97 | 60.92 | 84.46 | 62.14 | 87.50 | ||
Overall accuracy = 80.23%; Kappa coefficient = 0.77 |
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Rajendran, S.; Nasir, S.; El-Ghali, M.A.K.; Alzebdah, K.; Salim Al-Rajhi, A.; Al-Battashi, M. Spectral Signature Characterization and Remote Mapping of Oman Exotic Limestones for Industrial Rock Resource Assessment. Geosciences 2018, 8, 145. https://doi.org/10.3390/geosciences8040145
Rajendran S, Nasir S, El-Ghali MAK, Alzebdah K, Salim Al-Rajhi A, Al-Battashi M. Spectral Signature Characterization and Remote Mapping of Oman Exotic Limestones for Industrial Rock Resource Assessment. Geosciences. 2018; 8(4):145. https://doi.org/10.3390/geosciences8040145
Chicago/Turabian StyleRajendran, Sankaran, Sobhi Nasir, Mohammed A. K. El-Ghali, Khaled Alzebdah, Ali Salim Al-Rajhi, and Mohammed Al-Battashi. 2018. "Spectral Signature Characterization and Remote Mapping of Oman Exotic Limestones for Industrial Rock Resource Assessment" Geosciences 8, no. 4: 145. https://doi.org/10.3390/geosciences8040145
APA StyleRajendran, S., Nasir, S., El-Ghali, M. A. K., Alzebdah, K., Salim Al-Rajhi, A., & Al-Battashi, M. (2018). Spectral Signature Characterization and Remote Mapping of Oman Exotic Limestones for Industrial Rock Resource Assessment. Geosciences, 8(4), 145. https://doi.org/10.3390/geosciences8040145