Early ICESat-2 on-orbit Geolocation Validation Using Ground-Based Corner Cube Retro-Reflectors
The Ice, Cloud and Land Elevation Satellite-2 (ICESat-2), an Earth-observing laser altimetry mission, is currently providing global elevation measurements. Geolocation validation confirms the altimeter’s ability to accurately position the measurement on the surface of the Earth and provides insight...
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ftmdpi:oai:mdpi.com:/2072-4292/12/21/3653/ 2023-08-20T04:00:57+02:00 Early ICESat-2 on-orbit Geolocation Validation Using Ground-Based Corner Cube Retro-Reflectors Lori Magruder Kelly Brunt Michael Alonzo agris 2020-11-07 application/pdf https://doi.org/10.3390/rs12213653 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs12213653 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 21; Pages: 3653 ICESat-2 ATLAS geolocation laser altimetry Text 2020 ftmdpi https://doi.org/10.3390/rs12213653 2023-08-01T00:25:30Z The Ice, Cloud and Land Elevation Satellite-2 (ICESat-2), an Earth-observing laser altimetry mission, is currently providing global elevation measurements. Geolocation validation confirms the altimeter’s ability to accurately position the measurement on the surface of the Earth and provides insight into the fidelity of the geolocation determination process. Surfaces well characterized by independent methods are well suited to provide a measure of the ICESat-2 geolocation accuracy through statistical comparison. This study compares airborne lidar data with the ICESat-2 along-track geolocated photon data product to determine the horizontal geolocation accuracy by minimizing the vertical residuals between datasets. At the same location arrays of corner cube retro-reflectors (CCRs) provide unique signal signatures back to the satellite from their known positions to give a deterministic solution of the laser footprint diameter and the geolocation accuracy for those cases where two or more CCRs were illuminated within one ICESat-2 transect. This passive method for diameter recovery and geolocation accuracy assessment is implemented at two locations: White Sands Missile Range (WSMR) in New Mexico and along the 88°S latitude line in Antarctica. This early on-orbit study provides results as a proof of concept for this passive validation technique. For the cases studied the diameter value ranged from 10.6 to 12 m. The variability is attributed to the statistical nature of photon-counting lidar technology and potentially, variations in the atmospheric conditions that impact signal transmission. The geolocation accuracy results from the CCR technique and airborne lidar comparisons are within the mission requirement of 6.5 m. Text Antarc* Antarctica MDPI Open Access Publishing Remote Sensing 12 21 3653 |
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Open Polar |
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MDPI Open Access Publishing |
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ftmdpi |
language |
English |
topic |
ICESat-2 ATLAS geolocation laser altimetry |
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ICESat-2 ATLAS geolocation laser altimetry Lori Magruder Kelly Brunt Michael Alonzo Early ICESat-2 on-orbit Geolocation Validation Using Ground-Based Corner Cube Retro-Reflectors |
topic_facet |
ICESat-2 ATLAS geolocation laser altimetry |
description |
The Ice, Cloud and Land Elevation Satellite-2 (ICESat-2), an Earth-observing laser altimetry mission, is currently providing global elevation measurements. Geolocation validation confirms the altimeter’s ability to accurately position the measurement on the surface of the Earth and provides insight into the fidelity of the geolocation determination process. Surfaces well characterized by independent methods are well suited to provide a measure of the ICESat-2 geolocation accuracy through statistical comparison. This study compares airborne lidar data with the ICESat-2 along-track geolocated photon data product to determine the horizontal geolocation accuracy by minimizing the vertical residuals between datasets. At the same location arrays of corner cube retro-reflectors (CCRs) provide unique signal signatures back to the satellite from their known positions to give a deterministic solution of the laser footprint diameter and the geolocation accuracy for those cases where two or more CCRs were illuminated within one ICESat-2 transect. This passive method for diameter recovery and geolocation accuracy assessment is implemented at two locations: White Sands Missile Range (WSMR) in New Mexico and along the 88°S latitude line in Antarctica. This early on-orbit study provides results as a proof of concept for this passive validation technique. For the cases studied the diameter value ranged from 10.6 to 12 m. The variability is attributed to the statistical nature of photon-counting lidar technology and potentially, variations in the atmospheric conditions that impact signal transmission. The geolocation accuracy results from the CCR technique and airborne lidar comparisons are within the mission requirement of 6.5 m. |
format |
Text |
author |
Lori Magruder Kelly Brunt Michael Alonzo |
author_facet |
Lori Magruder Kelly Brunt Michael Alonzo |
author_sort |
Lori Magruder |
title |
Early ICESat-2 on-orbit Geolocation Validation Using Ground-Based Corner Cube Retro-Reflectors |
title_short |
Early ICESat-2 on-orbit Geolocation Validation Using Ground-Based Corner Cube Retro-Reflectors |
title_full |
Early ICESat-2 on-orbit Geolocation Validation Using Ground-Based Corner Cube Retro-Reflectors |
title_fullStr |
Early ICESat-2 on-orbit Geolocation Validation Using Ground-Based Corner Cube Retro-Reflectors |
title_full_unstemmed |
Early ICESat-2 on-orbit Geolocation Validation Using Ground-Based Corner Cube Retro-Reflectors |
title_sort |
early icesat-2 on-orbit geolocation validation using ground-based corner cube retro-reflectors |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2020 |
url |
https://doi.org/10.3390/rs12213653 |
op_coverage |
agris |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_source |
Remote Sensing; Volume 12; Issue 21; Pages: 3653 |
op_relation |
https://dx.doi.org/10.3390/rs12213653 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs12213653 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
21 |
container_start_page |
3653 |
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1774721576380399616 |