Geostatistical interpolation and classification of remote sensing data from ice surfaces

Abstract

Geostatistical methods for interpolation and extrapolation of irregularly spaced data are kriging methods, a family of methods based on the least-squares optimization principle and usually introduced in a probabilistic framework ('geostatistical estimation'). The difference between kriging and numerical interpolation methods lies in the exploitation of a spatial structure function, the variogram, in the optimization. Usefulness of geostatistical interpolation for glaciological data analysis has been demonstrated a number of times. Application of ordinary kriging to satellite radar altimeter data from Antarctic ice streams yields maps of 3-km resolution that facilitate glaciodynamic investigations. The technique is exemplified here for 1995 ERS-1 data, and the resultant new map of the entire Lambert Glacier/Amery Ice Shelf area including upper Lambert Glacier and other tributaries of (lower) Lambert Glacier (59degrees-79degreesE/68degrees-75degreesS) is presented. While interpolation utilizes the primary information in the data, a geostatistical surface classification method is developed to derive secondary information from elevation and backscatter data. Based on quantitative properties of the variogram, elements of surface structures are used for mapping and segmentation of an area into provinces homogeneous in surface characteristics. A critical issue in the analysis of satellite Synthetic Aperture Radar (SAR) data is the availability of ground truthing to distinguish between intensity variations caused by subscaleresolution geophysical variability and noise, and to determine small-scale sources of variations in backscattering. During the 1993-1995 surge of Bering Glacier, Alaska, GPS-located video data were collected from small aircraft and analyzed systematically with the geostatistical ice surface classification system ICECLASS. The objectives are to ( a ) help understand the relations between ice velocities, surface strain states, and progression of deformation processes during the surge, and ( b ) provide a technique for surface classification based on video data, SAR data, or image data in general.