Permafrost Dynamics Observatory—Part I: Postprocessing and Calibration Methods of UAVSAR L‐Band InSAR Data for Seasonal Subsidence Estimation

• Main Authors: Roger J. Michaelides, Richard H. Chen, Yuhuan Zhao, Kevin Schaefer, Andrew D. Parsekian, Taylor Sullivan, Mahta Moghaddam, Howard A. Zebker, Lin Liu, Xingyu Xu, Jingyi Chen
• Format: Article
• Language: English
• Published: American Geophysical Union (AGU) 2021-07-01
• Series: Earth and Space Science
• Subjects: InSAR; UAVSAR; synthetic aperture radar; permafrost; active layer thickness; Arctic and boreal
• Online Access: https://doi.org/10.1029/2020EA001630

Abstract 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.