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Coherent SAR methods for monitoring dry-snow covered terrain

Thesis type
(Thesis) Ph.D.
Date created
2022-02-16
Authors/Contributors
Abstract
Coherent synthetic aperture radar (SAR) based terrain monitoring relies on effective image focusing, compensation of interferometric phase biases and mitigation of decorrelation effects. The observation of dry-snow-covered terrain is affected by microwave interaction with the snow and this poses a challenge for terrain mapping applications in terms of the effect of the snow on target focusing, signal phase bias and decorrelation. However, these effects also provide an opportunity to map snow properties. As such, dry-snow presents a dual problem for coherent SAR applications: the joint mitigation of the effects of snow to allow unbiased observation of the terrain under the snow and measurement of the snow layer itself. This thesis introduces novel methods to address three aspects of this dual problem: (i) image formation – the defocusing and phase biasing effects of dry-snow are considered including how these can be corrected and exploited to estimate snow water equivalent (SWE) from a single SAR channel; (ii) interferometric phase bias – the limitations of SAR interferometry (InSAR) based SWE change mapping are addressed by exploiting the effect that terrain slope has on the dry-snow InSAR phase contribution; and (iii) temporal decorrelation – an adaptation of phase-linking methods is introduced to better enable multi-temporal InSAR for the case of seasonal snow covered terrain which suffers sever cross-season decorrelation effects. In each case, an analytical model for the respective method is presented, the use of the method is demonstrated with simulated data while method performance is validated with real SAR datasets, either from the SFU Airborne SAR System or the RADARSAT-2 satellite. Together, these contributions represent a significant advancement in enabling wide-scale and persistent coherent SAR monitoring of snow-covered terrains.
Document
Identifier
etd21844
Copyright statement
Copyright is held by the author(s).
Permissions
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: Rabus, Bernhard
Thesis advisor: Vaughan, Rodney
Language
English
Member of collection
Download file Size
input_data\22410\etd21844.pdf 16.06 MB

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