Geolocating Low-Earth-Orbit satellite data from next-generation millimeter-wave radiometers using natural targets
The main 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 ra...
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Università degli Studi di Roma "La Sapienza"
2021
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ftunivromairis:oai:iris.uniroma1.it:11573/1485754 2024-02-11T09:55:46+01:00 Geolocating Low-Earth-Orbit satellite data from next-generation millimeter-wave radiometers using natural targets PAPA, Mario Papa, Mario MARZANO, FRANK SILVIO 2021-01-29 http://hdl.handle.net/11573/1485754 eng eng Università degli Studi di Roma "La Sapienza" http://hdl.handle.net/11573/1485754 info:eu-repo/semantics/openAccess Microwave radiometer Synthetic Aperture Radar geolocation landmark targets info:eu-repo/semantics/doctoralThesis 2021 ftunivromairis 2024-01-17T18:07:31Z The main 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. This work uses 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 dataset, 3 candidates landmark targets are selected: i) high-altitude lakes and high-latitude bays using a coastline reference database; ii) Antarctic ice shelves and Arctic shorelines using coastlines derived from Sentinel-1 Synthetic Aperture Radar (SAR) imagery; iii) high altitude mountains using digital elevation model as reference. 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. 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, respectively, with a standard deviation of about 2.7 and 2.0 km. 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. The second goal of this work is to investigate ICI channels, focusing on 243 GHz at horizontal polarization (ICI-4). The results of the simulations using radiative transfer model and artificial neural network (ANN) confirm that ICI-4 will be the best candidate to validate the ... Doctoral or Postdoctoral Thesis Antarc* Antarctic Arctic Ice Shelves Sapienza Università di Roma: CINECA IRIS Antarctic Arctic |
institution |
Open Polar |
collection |
Sapienza Università di Roma: CINECA IRIS |
op_collection_id |
ftunivromairis |
language |
English |
topic |
Microwave radiometer Synthetic Aperture Radar geolocation landmark targets |
spellingShingle |
Microwave radiometer Synthetic Aperture Radar geolocation landmark targets PAPA, Mario Geolocating Low-Earth-Orbit satellite data from next-generation millimeter-wave radiometers using natural targets |
topic_facet |
Microwave radiometer Synthetic Aperture Radar geolocation landmark targets |
description |
The main 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. This work uses 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 dataset, 3 candidates landmark targets are selected: i) high-altitude lakes and high-latitude bays using a coastline reference database; ii) Antarctic ice shelves and Arctic shorelines using coastlines derived from Sentinel-1 Synthetic Aperture Radar (SAR) imagery; iii) high altitude mountains using digital elevation model as reference. 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. 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, respectively, with a standard deviation of about 2.7 and 2.0 km. 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. The second goal of this work is to investigate ICI channels, focusing on 243 GHz at horizontal polarization (ICI-4). The results of the simulations using radiative transfer model and artificial neural network (ANN) confirm that ICI-4 will be the best candidate to validate the ... |
author2 |
Papa, Mario MARZANO, FRANK SILVIO |
format |
Doctoral or Postdoctoral Thesis |
author |
PAPA, Mario |
author_facet |
PAPA, Mario |
author_sort |
PAPA, Mario |
title |
Geolocating Low-Earth-Orbit satellite data from next-generation millimeter-wave radiometers using natural targets |
title_short |
Geolocating Low-Earth-Orbit satellite data from next-generation millimeter-wave radiometers using natural targets |
title_full |
Geolocating Low-Earth-Orbit satellite data from next-generation millimeter-wave radiometers using natural targets |
title_fullStr |
Geolocating Low-Earth-Orbit satellite data from next-generation millimeter-wave radiometers using natural targets |
title_full_unstemmed |
Geolocating Low-Earth-Orbit satellite data from next-generation millimeter-wave radiometers using natural targets |
title_sort |
geolocating low-earth-orbit satellite data from next-generation millimeter-wave radiometers using natural targets |
publisher |
Università degli Studi di Roma "La Sapienza" |
publishDate |
2021 |
url |
http://hdl.handle.net/11573/1485754 |
geographic |
Antarctic Arctic |
geographic_facet |
Antarctic Arctic |
genre |
Antarc* Antarctic Arctic Ice Shelves |
genre_facet |
Antarc* Antarctic Arctic Ice Shelves |
op_relation |
http://hdl.handle.net/11573/1485754 |
op_rights |
info:eu-repo/semantics/openAccess |
_version_ |
1790598634935418880 |