Discrimination between young sea ice types from single look SAR image texture

Abstract

This study addresses the modeling of synthetic aperture radar (SAR) image texture for sea ice targets in the Labrador marginal ice zone (MIZ). The image texture of distributed scatterers contains a substantial component relating to the imaging system as well as information about the target itself. Theory shows that the image autocorrelation function (ACF) may be analyzed to separate system contributions from scene contributions under certain conditions. The main theses of the study are: (i) SAR intensity images of sea ice are spatially non-Gaussian; and (ii) the predominant types and forms of MIZ sea ice may be discriminated based upon ACF model parameters. Data for the experiment was collected during the Labrador Ice Margin Experiment (LIMEX) during the spring of 1989. The primary data set is synthetic aperture radar imagery collected by the Canada Centre for Remote Sensing from an airborne platform The image data are at two frequencies (5.3 and 9.25 GHz) and four polarisations (HH, HV, VH, and W). Ancilliary data include RC-10 mapping camera photographs and extensive surface measurements. Experimental results indicate that the model provides an excellent fit to the measured ACFs. The image texture was found to be a strong function of the form of the sea ice as well as its type. For a given type, the various forms could be discriminated with a single SAR channels. For full discrimination of all types and forms, a two-channel combination was necessary: X/sub HV/+C/sub HH/ or X/sub HV/+C/sub HV/. >