Retrieval of Melt Ponds on Arctic Multiyear Sea Ice in Summer from TerraSAR-X Dual-Polarization Data Using Machine Learning Approaches: A Case Study in the Chukchi Sea with Mid-Incidence Angle Data
Abstract
:1. Introduction
2. Materials
2.1. Airborne SAR Survey Data
2.2. TerraSAR-X Dual-Polarization Data
2.3. Sea Ice Conditions
3. Methodology
3.1. Construction of the Reference Dataset
3.2. Polarimetric Parameters
3.3. Machine Learning Approaches for Melt Pond Retrieval
4. Results and Discussion
4.1. Polarimetric Signatures
4.2. Performance of Melt Pond Detection Model Using Polarimetric Parameters
Reference | Open Water | Sea Ice | Melt Pond | Sum | User’s Accuracy |
---|---|---|---|---|---|
Classified as | |||||
Open water | 1865 | 79 | 1197 | 3141 | 59.38% |
Sea ice | 54 | 2152 | 349 | 2555 | 84.23% |
Melt pond | 558 | 246 | 931 | 1735 | 53.66% |
Sum | 2477 | 2477 | 2477 | 7431 | |
Producer’s accuracy | 75.29% | 86.88% | 37.59% | ||
Overall accuracy | 66.59% | ||||
Kappa coefficient | 49.88% |
Reference | Open Water | Sea Ice | Melt Pond | Sum | User’s Accuracy |
---|---|---|---|---|---|
Classified as | |||||
Open water | 1955 | 50 | 1175 | 3180 | 61.48% |
Sea ice | 27 | 2222 | 286 | 2535 | 87.65% |
Melt pond | 495 | 205 | 1016 | 1716 | 59.21% |
Sum | 2477 | 2477 | 2477 | 7431 | |
Producer’s accuracy | 78.93% | 89.71% | 41.02% | ||
Overall accuracy | 69.88% | ||||
Kappa coefficient | 54.82% |
4.3. Performance of the Melt Pond Detection Model Considering the Texture Features of the Polarimetric Parameters
Reference | Open Water | Sea Ice | Melt Pond | Sum | User’s Accuracy |
---|---|---|---|---|---|
Classified as | |||||
Open water | 2333 | 14 | 210 | 2557 | 91.24% |
Sea ice | 15 | 2175 | 434 | 2624 | 82.89% |
Melt pond | 129 | 288 | 1833 | 2250 | 81.47% |
Sum | 2477 | 2477 | 2477 | 7431 | |
Producer’s accuracy | 94.19% | 87.81% | 74.0% | ||
Overall accuracy | 85.33% | ||||
Kappa coefficient | 78.0% |
Reference | Open Water | Sea Ice | Melt Pond | Sum | User’s Accuracy |
---|---|---|---|---|---|
Classified as | |||||
Open water | 2366 | 7 | 125 | 2498 | 94.72% |
Sea ice | 5 | 2280 | 304 | 2589 | 88.06% |
Melt pond | 106 | 190 | 2048 | 2344 | 87.37% |
Sum | 2477 | 2477 | 2477 | 7431 | |
Producer’s accuracy | 95.52% | 92.04% | 82.68% | ||
Overall accuracy | 90.08% | ||||
Kappa coefficient | 85.12% |
4.4. Retrieved Melt Pond Statistics
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Han, H.; Im, J.; Kim, M.; Sim, S.; Kim, J.; Kim, D.-j.; Kang, S.-H. Retrieval of Melt Ponds on Arctic Multiyear Sea Ice in Summer from TerraSAR-X Dual-Polarization Data Using Machine Learning Approaches: A Case Study in the Chukchi Sea with Mid-Incidence Angle Data. Remote Sens. 2016, 8, 57. https://doi.org/10.3390/rs8010057
Han H, Im J, Kim M, Sim S, Kim J, Kim D-j, Kang S-H. Retrieval of Melt Ponds on Arctic Multiyear Sea Ice in Summer from TerraSAR-X Dual-Polarization Data Using Machine Learning Approaches: A Case Study in the Chukchi Sea with Mid-Incidence Angle Data. Remote Sensing. 2016; 8(1):57. https://doi.org/10.3390/rs8010057
Chicago/Turabian StyleHan, Hyangsun, Jungho Im, Miae Kim, Seongmun Sim, Jinwoo Kim, Duk-jin Kim, and Sung-Ho Kang. 2016. "Retrieval of Melt Ponds on Arctic Multiyear Sea Ice in Summer from TerraSAR-X Dual-Polarization Data Using Machine Learning Approaches: A Case Study in the Chukchi Sea with Mid-Incidence Angle Data" Remote Sensing 8, no. 1: 57. https://doi.org/10.3390/rs8010057