Combining AMSR-E and QuikSCAT image data to improve sea ice classification

TitleCombining AMSR-E and QuikSCAT image data to improve sea ice classification
Publication TypeConference Paper
Year of Publication2008
AuthorsYu, P., D. A. Clausi, R. De Abreu, and T. Agnew
Conference Name5th Workshop on Pattern Recognition for Remote Sensing
Date Published12/2008
Conference LocationTampa, Florida, USA
KeywordsAMSR-E image data, classifier accuracy, hydrological techniques, image classification, maximum likelihood classifier, maximum likelihood estimation, QuikSCAT image data, sea ice, supervised sea ice classification, terrain mapping, Western Arctic region

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 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 is beneficial for sea ice mapping. Using all available features is recommended and training data from a specific date remains reliable within 30 days.