Assessing the spaceborne 183.31-GHz radiometric channel geolocation using high-altitude lakes, ice shelves, and SAR imagery

• Published in: IEEE Transactions on Geoscience and Remote Sensing
• Main Authors: Papa M., Mattioli V., Avbelj J., Marzano F. S.
• Other Authors: Papa, M., Mattioli, V., Avbelj, J., Marzano, F. S.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2021
• Subjects: image geolocation error; spaceborne millimeter-wave radiometer; surface landmark; synthetic aperture radar (SAR) imagery; Antarc*; Antarctic; Ice Shelves
• Online Access: http://hdl.handle.net/11573/1555397; https://doi.org/10.1109/TGRS.2020.3024677

The goal of this work is to perform the geolocation error assessment of the channel imagery at 183.31 GHz of the Special Sensor Microwave Imager/Sounder (SSMIS). The frequency around 183.31 GHz still represents the highest channel frequency of current spaceborne microwave and millimeter-wave radiometers. The latter will be extended to frequencies up to 664 GHz, as in the case of EUMETSAT Ice Cloud Imager (ICI). This use of submillimeter observations unfortunately prevents a straightforward geolocation error assessment using landmark-based techniques. We used SSMIS data at 183.31 GHz as a submillimeter proxy to identify the most suitable targets for geolocation error validation in very dry atmospheric conditions, as suggested by radiative transfer modeling. Using a yearly SSMIS data set, three candidates' landmark targets are selected: 1) high-altitude lakes and high-latitude bays using a coastline reference database and 2) Antarctic ice shelves using coastlines derived from Sentinel-1 Synthetic Aperture Radar (SAR) imagery. Data processing is carried out by using spatial cross correlation methods in the spatial frequency domain and performing a numerical sensitivity analysis to contour displacement. Cloud masking, based on a fuzzy-logic approach, is applied to automatically selected clear-air days. The results show that the average geolocation error is about 6.2 km for mountainous lakes and sea bays and 5.4 km for ice shelves, with a standard deviation of about 2.7 and 2.0 km, respectively. The results are in line with SSMIS previous estimates, whereas annual clear-air days are about 10% for mountainous lakes and sea bays and 18% for ice shelves.