Permafrost Dynamics Observatory-Part I: Postprocessing and Calibration Methods of UAVSAR L-Band InSAR Data for...

Area of Science:

• Geophysics
• Remote Sensing
• Permafrost Science

Background:

• Interferometric Synthetic Aperture Radar (InSAR) is crucial for quantifying physical properties in permafrost landscapes.
• Previous studies primarily used spaceborne InSAR, but airborne InSAR datasets are increasingly available for permafrost research.
• Existing algorithms for permafrost property retrieval were developed for spaceborne platforms, necessitating adaptation for airborne data.

Purpose of the Study:

• To introduce calibration techniques for applying a novel joint retrieval algorithm to airborne InSAR data for permafrost active layer thickness retrieval.
• To demonstrate the mitigation of InSAR measurement uncertainties through developed calibration methods.
• To quantify remaining uncertainties using a Gaussian mixture model for interferometric phase uncertainty.

Main Methods:

• Development and application of calibration techniques for airborne InSAR data.
• Implementation of a novel joint retrieval algorithm for active layer thickness.
• Modeling interferometric phase uncertainty using a Gaussian mixture model.
• Analysis of airborne InSAR dataset acquired by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar.

Main Results:

• Calibration methods effectively mitigate InSAR measurement uncertainties.
• A novel method quantifies remaining uncertainties using Gaussian mixture modeling.
• The study highlights the impact of SAR resolution and the limitations of using few interferograms.

Conclusions:

• The developed calibration techniques are essential for accurate active layer thickness retrieval from airborne InSAR data.
• Quantifying uncertainties is critical for reliable permafrost monitoring and research.
• Findings have implications for comparing airborne and spaceborne InSAR datasets in Arctic permafrost regions.