Abstract
Sea ice has an intense impact on the polar environment, ocean circulation, weather and regional climate. Unexpected melting of sea ice, which is considered as one of the climate change effects, has become a potential threat to the Earth’s climate. The regular monitoring of sea ice and its extent has become very important towards understanding of sea ice temporal dynamics. In this study, we present an operational technique of generation of sea ice images and sea ice area (derived from the images) using level-4 data from Indian Scatterometer SCATSAT-1. Using hierarchical classification rules, the threshold-based technique has been developed and applied to generate super-resolution (2.25 km) daily sea ice images over the Antarctic for the years 2017 and 2018. The technique uses four SCATSAT-1 data products, i.e. Gamma0 [Horizontal (H) and Vertical (V)] and Brightness Temperature (H and V) to classify sea ice, open water and other classes. Classification accuracy has been assessed by comparing SCATSAT-1 sea ice images with those obtained from AMSR2 sea ice concentration data. The comparison shows that there is around 96.1% matching of sea ice classification between SCATSAT-1 and AMSR-2 SIC derived sea ice images. Hence, it indicates that the super-resolution data of SCATSAT-1 is well capable of distinguishing sea ice from water.
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Acknowledgements
We would like to thank Director, PDPU and Director, Space Applications Centre (SAC), ISRO for giving the opportunity and providing the data sets. We would also like to thank Deputy Director, EPSA for his inspiration and guidance.
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Upadhyay, K., Tripathi, N., Vachharajani, B. et al. Deriving Sea Ice Images from Super Resolution SCATSAT-1 Data over the Antarctic: Operational Method and Accuracy Assessment. J Indian Soc Remote Sens 49, 2575–2581 (2021). https://doi.org/10.1007/s12524-021-01412-8
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DOI: https://doi.org/10.1007/s12524-021-01412-8