Probabilistic River Water Mapping from Landsat-8 Using the Support Vector Machine Method
Abstract
:1. Introduction
2. Study Area and Data
2.1. Study Area
2.2. Data
3. Methods
3.1. FMask Algorithm
3.2. Feature Set Construction
3.3. Posterior Probability Support Vector Machine (SVM)
3.4. Water Mapping Using Traditional Water Index Methods
3.5. Accuracy Assessment
3.5.1. Accuracy Assessment on Posterior Probability Images
3.5.2. Accuracy Assessment on Binary Water Maps
4. Result and Discussion
4.1. Posterior Probability Results
4.2. Histogram-Based Thresholding
4.3. Binary Water Maps
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Site | Path/Row of Landsat-8 Image | Date of Landsat-8 Image | Date of Sentinel-2 Image |
---|---|---|---|
Zhengyixia | 134/32 | 2019-3-23 | 2019-3-22 |
Shuangtabu | 136/32 | 2019-3-21 | 2019-3-18 |
Yingluoxia | 134/33 | 2019-3-23 | 2019-3-22 |
Name | Wavelength (μm) | Description |
---|---|---|
U-BLUE | 0.435–0.451 | Band 1 (ultra blue) surface reflectance |
BLUE | 0.452–0.512 | Band 2 (blue) surface reflectance |
GREEN | 0.533–0.590 | Band 3 (green) surface reflectance |
RED | 0.636–0.673 | Band 4 (red) surface reflectance |
NIR | 0.851–0.879 | Band 5 (near infrared) surface reflectance |
SWIR1 | 1.566–1.651 | Band 6 (shortwave infrared 1) surface reflectance |
SWIR2 | 2.107–2.294 | Band 7 (shortwave infrared 2) surface reflectance |
Method | Overall Accuracy | Commission Error | Omission Error | Kappa | Critical Success Index (CSI) |
---|---|---|---|---|---|
PPSVM | 98.3% | 0.9% | 0.6% | 0.877 | 0.795 |
mNDWI | 98.2% | 1.0% | 0.7% | 0.868 | 0.781 |
NDWI | 97.7% | 1.1% | 1.2% | 0.824 | 0.723 |
Method | Overall Accuracy | Commission Error | Omission Error | Kappa | Critical Success Index (CSI) |
---|---|---|---|---|---|
PPSVM | 98.9% | 0.6% | 0.5% | 0.719 | 0.574 |
mNDWI | 99.1% | 0.5% | 0.3% | 0.784 | 0.650 |
NDWI | 97.6% | 1.5% | 0.9% | 0.465 | 0.321 |
Method | Overall Accuracy | Commission Error | Omission Error | Kappa | Critical Success Index (CSI) |
---|---|---|---|---|---|
PPSVM | 98.8% | 0.6% | 0.6% | 0.822 | 0.707 |
mNDWI | 98.6% | 0.7% | 0.7% | 0.804 | 0.682 |
NDWI | 98.9% | 0.5% | 0.6% | 0.839 | 0.730 |
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Liu, Q.; Huang, C.; Shi, Z.; Zhang, S. Probabilistic River Water Mapping from Landsat-8 Using the Support Vector Machine Method. Remote Sens. 2020, 12, 1374. https://doi.org/10.3390/rs12091374
Liu Q, Huang C, Shi Z, Zhang S. Probabilistic River Water Mapping from Landsat-8 Using the Support Vector Machine Method. Remote Sensing. 2020; 12(9):1374. https://doi.org/10.3390/rs12091374
Chicago/Turabian StyleLiu, Qihang, Chang Huang, Zhuolin Shi, and Shiqiang Zhang. 2020. "Probabilistic River Water Mapping from Landsat-8 Using the Support Vector Machine Method" Remote Sensing 12, no. 9: 1374. https://doi.org/10.3390/rs12091374
APA StyleLiu, Q., Huang, C., Shi, Z., & Zhang, S. (2020). Probabilistic River Water Mapping from Landsat-8 Using the Support Vector Machine Method. Remote Sensing, 12(9), 1374. https://doi.org/10.3390/rs12091374