Combining Amsr-E And Quikscat Image Data To Improve Sea Ice Classification

The benefits of augmenting AMSR-E image data with QuikSCAT image data for supervised sea ice classification in the Western Arctic region are investigated. Experiments compared the performance of a maximum likelihood classifier when used with the AMSR-E only data set against the combined data and examined the preferred number of features to use as well as the reliability: v of training data over time. Adding QuikSCAT often improves classifier accuracy in a statistically significant manner and never decreased it significantly when enough,features are used. Combining these data sets beneficial sea ice mapping. Using all available features is recommended and training data from a specific date remains reliable within 30 days.