Object-Based Arctic Sea Ice Ridge Detection From High-Spatial-Resolution Imagery

Xin Miao, Missouri State University
Hongjie Xie
Stephen F. Ackley
Songfeng Zheng, Missouri State University


High-spatial-resolution aerial photographs can provide detailed distribution of sea ice features. However, very few studies have ever considered shadows on the photographs for sea ice detection. In this letter, sea ice shadows, retrieved from 163 selected aerial photographs acquired on July 26, 2010, in a marginal-ice-zone area near Barrow, Alaska, utilizing an object-based classification scheme, are used to estimate the sea ice ridge attributes through local solar illumination geometry. The photograph-averaged ridge frequency (354.6-8908.7 km -2 ), length (1.22-10.33 m), and height (0.15-1.29 m) are obtained from the 163 photographs using batch processing. This letter provides an important batch processing method for ridge detection and ridge attribute retrieval from the high-resolution imagery of sea ice.