Detection and discrimination of icebergs and ships using satellite altimetry

Recent research has confirmed that satellite altimetry can be used for detecting icebergs. In an effort to validate the altimetry-based approach, this study used 105 samples of icebergs contained in both satellite altimeter data and ENVISAT-ASAR scenes for the Weddell Sea area. The probability of detecting icebergs larger than 150 m waterline-length was 47%. The problem of discriminating ships and icebergs based on altimeter measurements was addressed using an ensemble of automated classifiers. A total of ten features were defined from the altimetry signal to be used as predictor variables in supervised classification. The classifier ensemble comprised discriminant functions, k-nearest neighbor, neural networks, support vector machines, and decision tree analysis. Several algorithms successfully classified objects as ships or icebergs with an accuracy exceeding 85%.