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

Earth and Space Science

Jingyi Chen¹  Taylor Sullivan²  Andrew D. Parsekian²  Roger J. Michaelides³  Howard A. Zebker⁴  Xingyu Xu⁵  Lin Liu⁵  Richard H. Chen⁶  Kevin Schaefer⁷  Mahta Moghaddam⁸  Yuhuan Zhao⁸ 

[1] Department of Aerospace Engineering and Engineering Mechanics University of Texas Austin TX USA;Department of Geology and Geophysics University of Wyoming Laramie WY USA;Department of Geophysics Colorado School of Mines Golden CO USA;Department of Geophysics Stanford University Stanford CA USA;Earth System Science Programme Faculty of Science The Chinese University of Hong Kong Hong Kong China;Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA;National Snow and Ice Data Center Cooperative Institute for Research in Environmental Sciences University of Colorado at Boulder Boulder CO USA;Viterbi School of Engineering University of Southern California Los Angeles CA USA;

关键词: InSAR;    UAVSAR;    synthetic aperture radar;    permafrost;    active layer thickness;    Arctic and boreal;   

DOI  :  10.1029/2020EA001630

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown