Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Acquisition and Processing
2.3. Methods
2.3.1. Water Index-Based Approaches
2.3.2. Validation and Method Comparison
3. Results
4. Discussion
4.1. Comparison of Different Water Indices in Water Body Extraction
4.2. Comparison of Different Sensors in Water Body Extraction
4.3. Sensitivities of Sensors and Water Body Mapping Algorithms in Different Water Conditions
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Bands | Landsat 7 ETM+ | Landsat 8 OLI | Sentinel-2 MSI | |||
---|---|---|---|---|---|---|
W 1 (µm) | R 1 (m) | W 1 (µm) | R 1 (m) | W 1 (µm) | R 1 (m) | |
Blue | 0.45–0.52 | 30 | 0.45–0.51 | 30 | 0.46–0.52 | 10 |
Green | 0.52–0.60 | 30 | 0.53–0.59 | 30 | 0.55–0.58 | 10 |
Red | 0.63–0.69 | 30 | 0.64–0.67 | 30 | 0.64–0.67 | 10 |
NIR | 0.76–0.90 | 30 | 0.85–0.88 | 30 | 0.78–0.90 | 10 |
SWIR-1 | 1.55–1.75 | 30 | 1.57–1.65 | 30 | 1.57–1.65 | 20 |
SWIR-2 | 2.08–2.35 | 30 | 2.11–2.29 | 30 | 2.10–2.28 | 20 |
Study Area | Algorithms Based on Index Used | Algorithms | Threshold Rules | OA 1 | Applicable Conditions | References |
---|---|---|---|---|---|---|
North Carolina | TCW | TCW = 0.1509 × Bblue + 0.1973 × Bgreen + 0.3279 × Bred + 0.3406 × BNir − 0.7112 × BSWIR-1 − 0.4572 × BSWIR-2 | TCW > 0 | - | Clear water/The mixture of water and other sediments | [35,36] |
Western Nebraska | NDWI | NDWI = (Bgreen − BNir)/(Bgreen + BNir) | NDWI > 0 | - | Clear water/The mixture of water and soil/vegetation | [37] |
Xiamen | mNDWI | mNDWI = (Bgreen − BSWIR-1)/(Bgreen + BSWIR-1) | mNDWI > 0 | 99.85% | Clear water/Water in urban environments | [38] |
The Missouri Coteau | SNN | Sum457 = BNir + BSWIR-1 + BSWIR-2 ND5723 = [(BSWIR-1 + BSWIR-2) − (Bgreen + Bred)]/[(BSWIR-1 + BSWIR-2) + (Bgreen + Bred)] ND571 = [(BSWIR-1 + BSWIR-2) − Bblue]/[(BSWIR-1 + BSWIR-2) + Bblue] | (Sum457 < 0.188) or (ND5723 < −0.457) or (ND571 < 0.04) or (Sum457 < 0.269 and ND5723 < −0.234 and ND571 < 0.40) | 96% | Clear water/The mixture of water and soil/vegetation | [39] |
Denmark, Switzerland, Ethiopia, South Africa, and New Zealand | AWEIsh | AWEIsh = Bblue + 2.5 × Bgreen − 1.5 × (BNir + BSWIR-1) − 0.25 × BSWIR-2 | AWEIsh > 0 | 93%–98% | Open water body with shadow | [41] |
AWEInsh | AWEInsh = 4 × (Bgreen − BSWIR-1) − (0.25 × BNir + 2.75 × BSWIR-1) | AWEInsh > 0 | Open water body without shadow | |||
Salt Lake, Tahoe Lake, Las Vegas and Lake Mead, and Florida | NDWI plus VI | EVI = 2.5 × (BNir − Bred)/(BNir + 6.0 × Bred − 7.5 × Bblue +1) NDVI = (BNir − Bred)/(BNir + Bred) LSWI = (BNir − BSWIR-1)/(BNir + BSWIR-1) mNDWI = (Bgreen − BSWIR-1)/(Bgreen + BSWIR-1) NDWI = (Bgreen − BNir)/(Bgreen + BNir) | EVI < 0.1 and (NDWI > NDVI or NDWI > EVI) | 92.23%–99.12% | Clear water/flooding | [43] |
mNDWI plus VI | EVI < 0.1 and (mNDWI > NDVI or mNDWI > EVI) | 94.34%–99.58% | ||||
LSWI plus VI | EVI < 0.1 and (LSWI > NDVI or LSWI > EVI) | 93.6%–99.52% |
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Zhou, Y.; Dong, J.; Xiao, X.; Xiao, T.; Yang, Z.; Zhao, G.; Zou, Z.; Qin, Y. Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors. Water 2017, 9, 256. https://doi.org/10.3390/w9040256
Zhou Y, Dong J, Xiao X, Xiao T, Yang Z, Zhao G, Zou Z, Qin Y. Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors. Water. 2017; 9(4):256. https://doi.org/10.3390/w9040256
Chicago/Turabian StyleZhou, Yan, Jinwei Dong, Xiangming Xiao, Tong Xiao, Zhiqi Yang, Guosong Zhao, Zhenhua Zou, and Yuanwei Qin. 2017. "Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors" Water 9, no. 4: 256. https://doi.org/10.3390/w9040256
APA StyleZhou, Y., Dong, J., Xiao, X., Xiao, T., Yang, Z., Zhao, G., Zou, Z., & Qin, Y. (2017). Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors. Water, 9(4), 256. https://doi.org/10.3390/w9040256