Permafrost Dynamics Observatory—Part I: Postprocessing and Calibration Methods of UAVSAR L‐Band InSAR Data for Seasonal Subsidence Estimation
| Autor: | Kevin Schaefer, Lin Liu, R. J. Michaelides, Taylor D. Sullivan, Richard H. Chen, Jingyi Chen, Mahta Moghaddam, Yuhuan Zhao, Andrew D. Parsekian, Xingyu Xu, Howard A. Zebker |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Informatics
010504 meteorology & atmospheric sciences Earthquake Source Observations Arctic and boreal Astronomy 0211 other engineering and technologies 02 engineering and technology Permafrost Biogeosciences 01 natural sciences Remote Sensing InSAR Planetary Sciences: Solar System Objects Ionospheric Physics Observatory Interferometric synthetic aperture radar Permafrost Cryosphere and High‐latitude Processes Seismology Earthquake Interaction Forecasting and Prediction active layer thickness QE1-996.5 Exploration Geophysics Gravity Methods Ocean Predictability and Prediction Geology Asteroids Seismic Cycle Related Deformations Results from 10 Years of UAVSAR Observations Tectonic Deformation Oceanography: General Policy Time Variable Gravity Comets: Dust Tails and Trails Estimation and Forecasting Seismicity and Tectonics Planetary Sciences: Comets and Small Bodies Space Weather Cryosphere Mathematical Geophysics Probabilistic Forecasting Research Article synthetic aperture radar Synthetic aperture radar L band Satellite Geodesy: Results QB1-991 Environmental Science (miscellaneous) Active Layer Radio Science Cryobiology Earthquake Dynamics Calibration Comets Magnetospheric Physics Geodesy and Gravity Ionosphere Monitoring Forecasting Prediction UAVSAR 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing Gravity anomalies and Earth structure Continental Crust Policy Sciences Active layer Interferometry Arctic 13. Climate action General Earth and Planetary Sciences Other Subduction Zones Hydrology Transient Deformation Prediction Natural Hazards Forecasting permafrost |
| Zdroj: | Earth and Space Science, Vol 8, Iss 7, Pp n/a-n/a (2021) Earth and Space Science (Hoboken, N.j.) |
| ISSN: | 2333-5084 |
| Popis: | Interferometric synthetic aperture radar (InSAR) has been used to quantify a range of surface and near surface physical properties in permafrost landscapes. Most previous InSAR studies have utilized spaceborne InSAR platforms, but InSAR datasets over permafrost landscapes collected from airborne platforms have been steadily growing in recent years. Most existing algorithms dedicated toward retrieval of permafrost physical properties were originally developed for spaceborne InSAR platforms. In this study, which is the first in a two part series, we introduce a series of calibration techniques developed to apply a novel joint retrieval algorithm for permafrost active layer thickness retrieval to an airborne InSAR dataset acquired in 2017 by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar over Alaska and Western Canada. We demonstrate how InSAR measurement uncertainties are mitigated by these calibration methods and quantify remaining measurement uncertainties with a novel method of modeling interferometric phase uncertainty using a Gaussian mixture model. Finally, we discuss the impact of native SAR resolution on InSAR measurements, the limitation of using few interferograms per retrieval, and the implications of our findings for cross‐comparison of airborne and spaceborne InSAR datasets acquired over Arctic regions underlain by permafrost. Key Points We develop and present several calibration and postprocessing methods for seasonal subsidence estimation from interferometric synthetic aperture radar deformationNovel methods for phase referencing and uncertainty quantification due to nonergodicity within the multilook window are proposedResidual sources of uncertainty in active layer thickness estimation are discussed and quantified |
| Databáze: | OpenAIRE |
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