Linking Regional Winter Sea Ice Thickness and Surface Roughness to Spring Melt Pond Fraction on Landfast Arctic Sea Ice
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data and Pre-Processing
2.3. Object Based, Hybrid and Grid-Cell Image Analysis
3. Results
3.1. Victoria Strait Thickness, Roughness and fp Distributions in 2015
3.2. Relationship between Thickness and fp
3.3. Relationship between Roughness and fp
3.4. Relationship between Smoothed Surface Roughness and fp
3.5. Relationship between Thickness and Roughness
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Parameter | Instrument | Measurement Approach | Platform | Acquisition Dates | Description |
---|---|---|---|---|---|
Snow plus Ice Thickness | EM-bird | Electromagnetic induction and laser altimeter | Airborne | 19 April 2015 | Spatial resolution: 6.0 m Swath width: ~120 m Accuracy: 0.15 m |
Ice Surface Roughness | Riegel Laser Measurement System Q120 | 2D laser scanner | Airborne | 19 April 2015 | Spatial resolution: 1.2 m Swath width: 105 m Accuracy: 0.025 m |
Melt Pond Fraction (fp) | GeoEye-1 | Multispectral (VIS/NIR) | Satellite | 22 June 2015 23 June 2015 25 June 2015 | Spatial resolution: Panchromatic (0.5 m), Multispectral (2.0 m) Spectral resolution: RGBNIR |
Objects | RADARSAT-2 | C-band frequency SAR | Satellite | 23 April 2015 25 April 2015 | 23 April 2015 Pixel Spacing (azimuth × range): 5.1 × 4.7 m Incidence angle: 40.2°–41.6° Polarization: Fine Quad 25 April 2015 Pixel spacing (azimuth × range): 4.9 × 4.7 m Incidence angle: 22.3°–24.2° Polarization: Fine Quad |
FYI | MYI | FYI | MYI | FYI | MYI | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Fine | Med | Fine | Med | Coarse | Fine | Med | Fine | Med | Coarse | 120 m | 240 m | 120 m | 240 m | ||||
Min | Objects | −0.66 | −0.61 | −0.37 | −0.33 | −0.31 | Hybrid | −0.64 | −0.67 | −0.32 | −0.27 | −0.31 | Grid-cell | −0.61 | −0.65 | −0.30 | −0.11 |
Max | −0.51 | −0.67 | −0.45 | −0.33 | −0.29 | −0.40 | −0.73 | −0.43 | −0.42 | −0.40 | −0.72 | −0.75 | −0.46 | −0.38 | |||
Mean | −0.72 | −0.75 | −0.59 | −0.54 | −0.56 | −0.68 | −0.85 | −0.55 | −0.56 | −0.59 | −0.71 | −0.75 | −0.47 | −0.41 | |||
Med | −0.75 | −0.71 | −0.60 | −0.56 | −0.58 | −0.74 | −0.81 | −0.59 | −0.60 | −0.64 | −0.69 | −0.75 | −0.45 | −0.44 | |||
SD | −0.38 | −0.65 | −0.36 | −0.25 | −0.25 | −0.31 | −0.72 | −0.32 | −0.32 | −0.34 | −0.60 | −0.69 | −0.47 | −0.38 |
FYI | MYI | FYI | MYI | FYI | MYI | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Fine | Med | Fine | Med | Coarse | Fine | Med | Fine | Med | Coarse | 120 m | 240 m | 120 m | 240 m | ||||
Min | Objects | −0.34 | −0.32 | 0.30 | 0.21 | 0.16 | Hybrid | −0.35 | −0.31 | 0.25 | 0.27 | 0.19 | Grid-cell | −0.25 | −0.26 | −0.05 | −0.01 |
Max | −0.29 | −0.57 | 0.01 | 0.05 | 0.07 | −0.20 | −0.53 | 0.02 | 0.04 | 0.01 | −0.40 | −0.55 | −0.10 | −0.12 | |||
Mean | −0.32 | −0.53 | 0.02 | 0.03 | −0.02 | −0.25 | −0.52 | 0.04 | 0.09 | 0.00 | −0.35 | −0.42 | −0.09 | −0.11 | |||
Med | −0.22 | −0.41 | −0.03 | 0.00 | −0.07 | −0.14 | −0.36 | 0.03 | 0.06 | −0.03 | −0.30 | −0.37 | −0.07 | −0.11 | |||
SD | −0.35 | −0.59 | −0.07 | −0.03 | −0.02 | −0.29 | −0.63 | 0.00 | −0.01 | −0.06 | −0.39 | −0.54 | −0.10 | −0.17 |
FYI | MYI | FYI | MYI | FYI | MYI | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Fine | Med | Fine | Med | Coarse | Fine | Med | Fine | Med | Coarse | 120 m | 240 m | 120 m | 240 m | ||||
Min | Objects | −0.81 | −0.80 | −0.31 | −0.35 | −0.34 | Hybrid | −0.77 | −0.84 | −0.34 | −0.29 | −0.25 | Grid-cell | −0.72 | −0.77 | −0.20 | −0.23 |
Max | −0.79 | −0.81 | −0.27 | −0.26 | −0.21 | −0.72 | −0.80 | −0.24 | −0.19 | −0.09 | −0.72 | −0.77 | −0.19 | −0.22 | |||
Mean | −0.80 | −0.81 | −0.29 | −0.29 | −0.27 | −0.75 | −0.83 | −0.28 | −0.23 | −0.17 | −0.72 | −0.77 | −0.19 | −0.22 | |||
Med | −0.80 | −0.81 | −0.29 | −0.29 | −0.26 | −0.75 | −0.82 | −0.26 | −0.22 | −0.16 | −0.72 | −0.77 | −0.19 | −0.22 | |||
SD | −0.14 | −0.34 | 0.06 | 0.24 | 0.28 | −0.04 | −0.23 | 0.17 | 0.19 | 0.26 | −0.45 | −0.55 | 0.08 | 0.01 |
FYI | MYI | FYI | MYI | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Fine | Med | Fine | Med | Coarse | 120 m | 240 m | 120 m | 240 m | |||
Min | Objects | 0.39 | 0.36 | 0.07 | 0.21 | 0.27 | Grid-cell | 0.30 | 0.34 | 0.01 | 0.23 |
Max | 0.56 | 0.65 | 0.41 | 0.54 | 0.57 | 0.44 | 0.53 | 0.11 | 0.13 | ||
Mean | 0.36 | 0.49 | 0.20 | 0.20 | 0.23 | 0.41 | 0.44 | 0.07 | 0.07 | ||
Med | 0.18 | 0.26 | 0.12 | 0.06 | 0.03 | 0.34 | 0.38 | 0.04 | 0.13 | ||
SD | 0.52 | 0.68 | 0.40 | 0.47 | 0.47 | 0.35 | 0.45 | 0.05 | 0.07 |
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Nasonova, S.; Scharien, R.K.; Haas, C.; Howell, S.E.L. Linking Regional Winter Sea Ice Thickness and Surface Roughness to Spring Melt Pond Fraction on Landfast Arctic Sea Ice. Remote Sens. 2018, 10, 37. https://doi.org/10.3390/rs10010037
Nasonova S, Scharien RK, Haas C, Howell SEL. Linking Regional Winter Sea Ice Thickness and Surface Roughness to Spring Melt Pond Fraction on Landfast Arctic Sea Ice. Remote Sensing. 2018; 10(1):37. https://doi.org/10.3390/rs10010037
Chicago/Turabian StyleNasonova, Sasha, Randall K. Scharien, Christian Haas, and Stephen E. L. Howell. 2018. "Linking Regional Winter Sea Ice Thickness and Surface Roughness to Spring Melt Pond Fraction on Landfast Arctic Sea Ice" Remote Sensing 10, no. 1: 37. https://doi.org/10.3390/rs10010037
APA StyleNasonova, S., Scharien, R. K., Haas, C., & Howell, S. E. L. (2018). Linking Regional Winter Sea Ice Thickness and Surface Roughness to Spring Melt Pond Fraction on Landfast Arctic Sea Ice. Remote Sensing, 10(1), 37. https://doi.org/10.3390/rs10010037