Modeling the Long-Term Variability in the Surfaces of Three Lakes in Morocco with Limited Remote Sensing Image Sources
Abstract
:1. Introduction
2. Data
3. Interpolation Methodology
3.1. The Iterative Ratio Method
- N—joint period length;
- xi, yi—values at reference at missing location.
- NR—calculated normal ratio;
- yk—missing value;
- xk—existing value at a different location.
3.2. Kalman Filter
4. Results
4.1. LaB Case
4.2. LaO Case
4.3. c-LaT Case
5. Discussion
5.1. Discussion on the Interpolation Validation
5.2. Discussion on the Obtained Results
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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R—Interpolation | K—Interpolation | |||||
---|---|---|---|---|---|---|
Forward | Backward | Residual | Forward | Backward | Residual | |
Number of data [n]: | 456 | 456 | 456 | 456 | 456 | 456 |
Minimum: | 0.080 | 0.910 | –9.01 | 0.080 | –1.32 | –5.50 |
Maximum: | 37.3 | 39.2 | 8.95 | 34.2 | 33.0 | 6.08 |
Average: | 22.4 | 22.3 | 0.0633 | 22.4 | 22.4 | –0.0122 |
Standard deviation: | 6.36 | 6.19 | 2.27 | 6.09 | 5.97 | 1.06 |
Median: | 23.6 | 23.0 | 0.00 | 23.7 | 23.6 | 0.00 |
Coefficient of variation [Cv]: | 0.284 | 0.277 | 35.8 | 0.272 | 0.267 | –86.9 |
Skewness coefficient [Cs]: | –1.37 | –1.21 | –0.113 | –1.61 | –1.74 | –0.449 |
Kurtosis coefficient [Ck]: | 5.74 | 5.87 | 6.13 | 6.32 | 6.93 | 10.8 |
R—Interpolation | K—Interpolation | |||||
---|---|---|---|---|---|---|
Forward | Backward | Residual | Forward | Backward | Residual | |
Number of data [n]: | 456 | 456 | 456 | 456 | 456 | 456 |
Minimum: | 7.24 | 8.15 | –4.01 | 7.24 | 9.72 | –2.81 |
Maximum: | 17.5 | 17.6 | 4.64 | 17.5 | 15.7 | 3.18 |
Average: | 13.4 | 13.4 | 0.0331 | 13.4 | 13.4 | –0.00947 |
Standard deviation: | 1.55 | 1.61 | 1.02 | 1.38 | 1.15 | 0.585 |
Median: | 13.8 | 13.6 | 0.00 | 13.7 | 13.7 | 0.00 |
Coefficient of variation [Cv]: | 0.115 | 0.121 | 30.9 | 0.102 | 0.0855 | –61.7 |
Skewness coefficient [Cs]: | –0.915 | –0.528 | 0.177 | –0.939 | –0.910 | –0.562 |
Kurtosis coefficient [Ck]: | 4.34 | 3.44 | 6.24 | 4.78 | 3.49 | 9.60 |
R—Interpolation | K—Interpolation | |||||
---|---|---|---|---|---|---|
Forward | Backward | Residual | Forward | Backward | Residual | |
Number of data [n]: | 456 | 456 | 456 | 456 | 456 | 456 |
Minimum: | 3.88 | 3.59 | –2.05 | 4.05 | 4.50 | –1.21 |
Maximum: | 9.42 | 9.87 | 1.99 | 9.18 | 8.64 | 0.99 |
Average: | 6.20 | 6.21 | –0.0129 | 6.13 | 6.14 | –0.0113 |
Standard deviation: | 1.09 | 1.19 | 0.542 | 0.898 | 0.839 | 0.240 |
Median: | 6.18 | 6.14 | 0.00 | 6.05 | 6.08 | 0.00 |
Coefficient of variation [Cv]: | 0.175 | 0.192 | –42.0 | 0.147 | 0.137 | –21.3 |
Skewness coefficient [Cs]: | 0.218 | 0.295 | –0.374 | 0.226 | 0.289 | –0.728 |
Kurtosis coefficient [Ck]: | 2.56 | 2.67 | 5.90 | 2.52 | 2.36 | 9.58 |
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Haidu, I.; El Orfi, T.; Magyari-Sáska, Z.; Lebaut, S.; El Gachi, M. Modeling the Long-Term Variability in the Surfaces of Three Lakes in Morocco with Limited Remote Sensing Image Sources. Remote Sens. 2024, 16, 3133. https://doi.org/10.3390/rs16173133
Haidu I, El Orfi T, Magyari-Sáska Z, Lebaut S, El Gachi M. Modeling the Long-Term Variability in the Surfaces of Three Lakes in Morocco with Limited Remote Sensing Image Sources. Remote Sensing. 2024; 16(17):3133. https://doi.org/10.3390/rs16173133
Chicago/Turabian StyleHaidu, Ionel, Tarik El Orfi, Zsolt Magyari-Sáska, Sébastien Lebaut, and Mohamed El Gachi. 2024. "Modeling the Long-Term Variability in the Surfaces of Three Lakes in Morocco with Limited Remote Sensing Image Sources" Remote Sensing 16, no. 17: 3133. https://doi.org/10.3390/rs16173133