Indian Space Research Organisation's SCATSAT-1 is a continuity mission for Oceansat-2 Scatterometer. The sensor works in Ku-band (13.515 GHz) similar to the one flown on-board Oceansat-2. It provides backscattering coefficient over the globe and wind vector data products over the oceans that are useful for weather forecasting, cyclone detection and tracking services. Besides backscattering coefficient (sigma nought), two other important parameters namely, Gamma nought (obtained from backscattering coefficient) and Brightness temperature (obtained from scatterometer noise measurement) are given as the Level-4 data products archived at the ISRO’s Meteorological & Oceanographic Satellite Data Archival Centre. We used these three parameters both in horizontal and vertical polarizations for the Antarctic region (South Polar) to perform, first, a principal component analysis. Then, we used the first three principal components explaining the largest variability in the data set to perform an unsupervised k-means classification to estimate the regions of sea ice in around Antarctica. The derived sea ice extent through this method is compared with other popular sea ice extent products available elsewhere.
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Antarctic sea ice extent from ISRO's SCATSAT-1 using PCA and k-means classification
Published: 22 March 2018 by MDPI in 2nd International Electronic Conference on Remote Sensing session Applications
Keywords: SCATSAT-1, Antarctic sea ice extent, principal component analysis, k-means classification