On the dimensionality of multiparameter microwave image data from thin sea ice in the Labrador Sea

Abstract

Thin ice is typically defined as comprising the World Meteorological Organization's young and new ice categories, referring to sea ice that is less than 0.3 m thick. This ice type is an extremely important factor in both the thermodynamic and dynamic properties of both polar and marginal ice covers. In the LIMEX'89 experiment, spatially and temporally registered multipolarization data from 5.3 and 9.25 GHz SARs and from 37 and 90 GHz imaging radiometers were acquired over a region containing a wide range of new ice growth stages in the Labrador ice pack. The temperatures at the data acquisition time were -10 and correspond to ice growth conditions. In this paper, the dimensionality of the multifrequency, multipolarization active and passive data set is examined to determine the complementarity of the sensor parameters and sensor types for thin ice measurements. Principal component analysis is used to provide estimates of the information content of individual measurement channels and their combinations. Various measurement subspaces are examined. Criteria for channel redundance are proposed and tested and the classification potential of the multidimensional measurement set is tested for thin ice growth stages that are known to present classification difficulties for microwave sensors. Given six nominally independent SAR measurement channels, the information space dimension of this subspace is shown to be greater than five. The four radiometer channels are shown to have information space dimension two and are redundant in frequency. The combined, ten element, SAR/radiometer measurement space was shown to have information space dimension eight under the criteria used when the scattering polarization ratios are included.