Systematic preparation and processing of interferometric synthetic aperture radar data for monitoring linear transportation infrastructure

Peter Oliver; Claire Samson; Shawn Kenny

doi:10.1117/1.JRS.13.024504

15 April 2019 Systematic preparation and processing of interferometric synthetic aperture radar data for monitoring linear transportation infrastructure

Peter Oliver, Claire Samson, Shawn Kenny

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 13, Issue 2, 024504 (April 2019). https://doi.org/10.1117/1.JRS.13.024504

Abstract

We propose a methodology for the systematic preparation and processing of interferometric synthetic aperture radar (InSAR) data for monitoring linear transportation infrastructure subject to geohazards. The methodology is applied to two RADARSAT-2 Spotlight synthetic aperture radar datasets, and three case studies in Cornwall, Eastern Ontario, Canada, are examined. An InSAR processing sequence was established and 19 SLA24 and 15 SLA74 images were used to create time-series deformation maps spanning from March 2015 to September 2016. The noise floors were ±1.5 and ±1.0 cm, for the SLA24 and SLA74 datasets, respectively. Phase unwrapping errors, atmospheric path delay, and the limited number of images were identified as the largest contributors to measurement uncertainty, which was of the same order as the ground deformation field. To improve coherence and utility of the radar images for monitoring the effects of geohazards on infrastructure, it is recommended that imagery acquisitions consider the use of small incidence angles with moderate image resolution and 6- to 12-day revisit periods.

Citation Download Citation

Peter Oliver, Claire Samson, and Shawn Kenny "Systematic preparation and processing of interferometric synthetic aperture radar data for monitoring linear transportation infrastructure," Journal of Applied Remote Sensing 13(2), 024504 (15 April 2019). https://doi.org/10.1117/1.JRS.13.024504

Received: 26 June 2018; Accepted: 22 March 2019; Published: 15 April 2019

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