Title :
The Potential of the Maximum Cross-Correlation Technique to Estimate Surface Currents From Thermal AVHRR Global Area Coverage Data
Author :
Dransfeld, Steffen ; Larnicol, Gilles ; Le Traon, Pierre-Yves
Author_Institution :
Hamburg Univ.
Abstract :
Having already shown its potential of deriving the vector fields representing the ocean-surface advection from sequential 1.1-km-resolution local area coverage (LAC) Advanced Very High Resolution Radiometer (AVHRR) images, the maximum cross-correlation (MCC) technique here is applied to four 4.4-km-resolution global area coverage (GAC) AVHRR images. The resulting three vector fields are compared to the vector fields obtained from the LAC imagery corresponding to the same satellite passages. To quantify the reduction in accuracy inevitable when applying the method to the lower resolution imagery, the LAC vector fields were assumed to be error free. The deviation of the GAC vectors from the LAC vectors is expressed as percentage errors of the signal variance of meridional u and zonal v velocity components, and they are 16%/30%, respectively, for the best case and 62%/117% and 92%/111% for the other two cases. These results indicate that, in its present state, the GAC data do not allow the MCC technique to extract reliable current-vector information from it
Keywords :
correlation methods; image motion analysis; infrared imaging; ocean temperature; oceanographic techniques; radiometry; remote sensing; Advanced Very High Resolution Radiometer; image motion; infrared imaging; local area coverage AVHRR images; marine technology; maximum cross-correlation technique; meridional velocity; ocean-surface advection; remote sensing; satellite passages; signal variance errors; surface currents; thermal AVHRR global area coverage data; vector fields; zonal velocity; Data mining; Image resolution; Infrared imaging; Instruments; Los Angeles Council; Ocean temperature; Radiometry; Satellite broadcasting; Sea surface; Signal resolution; Image motion; infrared imaging; marine technology; remote sensing;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2006.878439