@inproceedings {512, title = {Large scale dynamic estimation of ocean surface temperature}, booktitle = {IEEE Geoscience and Remote Sensing Symposium}, year = {1999}, abstract = {

This paper addresses the dynamic estimation of the ocean surface temperature based on data from the Along-Track Scanning Radiometer (ATSR) for large (512 times;512) fields. For such huge problems, the conventional dynamic estimation tool (the Kalman filter) is not directly applicable, instead, we develop a recursive estimation algorithm that emulates the Kalman filter. Our approach uses a multiscale estimation algorithm for the update step, and makes simplifying assumptions about the surface dynamics leading to a computationally efficient prediction step

}, keywords = {Along-Track Scanning Radiometer data, ATSR data, geophysical signal processing, image processing, Kalman filter, Kalman filters, large scale dynamic estimation, multiscale estimation algorithm, ocean surface temperature, oceanographic techniques, prediction step, prediction theory, radiometry, recursive estimation, recursive estimation algorithm, recursive filters, update step}, doi = {http://dx.doi.org/10.1109/IGARSS.1999.772108}, author = {P Fieguth and F M. Khellah and M J. Murray and M R. Allen} } @inproceedings {474, title = {Hierarchical methods for global-scale estimation problems}, booktitle = {IEEE Canadian Conference on Electrical and Computer Engineering}, year = {1998}, address = {Waterloo, Canada}, abstract = {

There is a substantial signal-processing challenge associated with large-scale (especially global-scale) remote-sensing problems: solving the statistical inverse problem (i.e. deducing the properties of the sensed field from measurements) by brute force, that is by covariance matrix inversion, is completely impractical for fields involving millions of pixels. This paper reports on the ongoing development of an alternative technique, in which the statistical problem is modeled on a multiscale tree, applied to estimating sea-surface temperature (SST) based on infrared radiance observations from the along-track scanning radiometers (ATSRs)

}, keywords = {along-track scanning radiometers, covariance matrix inversion, geophysical signal processing, global-scale estimation problems, hierarchical methods, image processing, infrared radiance observations, inverse problems, measurements, multiscale tree, oceanographic techniques, parameter estimation, radiometry, Remote Sensing, remote-sensing, sea-surface temperature, sensed field, signal-processing, statistical analysis, statistical inverse problem, statistical problem, tree data structures}, doi = {http://dx.doi.org/10.1109/CCECE.1998.682707}, author = {P Fieguth and M R. Allen and M J. Murray} } @inproceedings {462, title = {Passive microwave imagery of a tropical storm near 118 GHz thermal and precipitation structure}, booktitle = {IGARSS {\textquoteright}94}, year = {1994}, abstract = {

An imaging microwave radiometer with eight double-sideband channels centered on the 118.75-GHz (1-)oxygen resonance was flown on a NASA ER-2 high altitude aircraft over a tropical cyclone in the Coral Sea, east of Australia. An eyewall of strong convection and a warm core within the eye are clearly visible. Brightness temperatures observed within the eye are approximately 10K warmer than those observed in clear air 100 km away. This warming extends somewhat beyond the eyewall in the highest (most opaque) channel. Two passes three hours apart may reveal a slight weakening of the convective activity. This flight provides the first known calibrated high-resolution 18.75 GHz imagery of a tropical storm. Temperature profiles and cloud-top altitudes may be inferred from the data

}, keywords = {118 GHz, 118.75 GHz, AD 1993 02 07, airborne remote sensing, atmosphere, atmospheric techniques, atmospheric temperature, brightness temperature, Coral Sea, double-sideband channels, EHF mm wave millimetric radiometry, eyewall, measurement technique, meteorology, microwave image, millimetre wave measurement, passive microwave imagery, precipitation structure, radiometry, rain, Remote Sensing, storm, storms, strong convection, tropical cyclone, tropical storm, warm core}, doi = {http://dx.doi.org/10.1109/IGARSS.1994.399760}, author = {M J. Schwartz and J W. Barrett and P Fieguth and P W. Rosenkranz and M S. Spina and D H. Staelin} }