HR: 14:55h
AN: NG33B-05    [Abstracts]
TI: Geostatistical Surface Classification
AU: * Williams, S
EM: Scott.Williams@colorado.edu
AF: CIRES, University of Colorado Boulder, Boulder, CO 80309-0449 United States
AU: Herzfeld, U C
EM: herzfeld@iceberg.colorado.edu
AF: CIRES, University of Colorado Boulder, Boulder, CO 80309-0449 United States
AB: Geostatistical surface classification is aimed at distinguishing objects - surface provinces or surface types - objectively and automatically. The basic idea is to calculate spatial structure functions from surface data and extract parameters from those functions that constitute a feature vector. If feature vectors can be designed to capture characteristic properties of surface types, then a classification of surface provinces is possible. Application in a moving-window operation facilitates segmentation of a given study area into surface provinces. Application to time series of surface data provides a means to study morphogenetic processes and changes in environmental conditions. Geostatistical classification provides a number of mathematical challenges and solutions as well as a wide range of applications. The problem of extraction of parameters in an ill-posed noise-to-resolution situation motivates the introduction of vario functions of higher order. Association of surface classes may be performed using deterministic functions or connectionist association. Applications range from a segmentation of marine-geologic provinces to a study of self-organisational processes in an alpine snow pack.
DE: 3045 Seafloor morphology and bottom photography
DE: 3299 General or miscellaneous
DE: 1863 Snow and ice (1827)
SC: Nonlinear Geophysics [NG]
MN: 2004 AGU Fall Meeting