A neural network algorithm for sea ice edge classification
Abbreviated Journal Title
IEEE Trans. Geosci. Remote Sensing
Geochemistry & Geophysics; Engineering, Electrical & Electronic; Remote; Sensing; Imaging Science & Photographic Technology
The NASA Scatterometer (NSCAT), launched in August 1996, is designed to measure wind vectors over ice-free oceans. To prevent contamination of the wind measurements, by the presence of sea ice, algorithms based on neural network technology have been developed to classify ice-free ocean surfaces. Neural networks trained using polarized alone and polarized plus multi-azimuth ''look'' Ku-band backscatter are described. Algorithm skill in locating the sea ice edge around Antarctica is experimentally evaluated using backscatter data from the Seasat-A Satellite Scatterometer that operated in 1978, Comparisons between the algorithms demonstrate a slight advantage of combined polarization and multi-look over using co-polarized backscatter alone. Classification skill is evaluated by comparisons with surface truth (sea ice maps), subjective ice classification, and independent over lapping scatterometer measurements (consecutive revolutions).
Ieee Transactions on Geoscience and Remote Sensing
Article; Proceedings Paper
"A neural network algorithm for sea ice edge classification" (1997). Faculty Bibliography 1990s. 1828.