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Monitoring highway stability in permafrost regions with X-band temporary scatterers stacking InSAR

Lookup NU author(s): Dr Keren Dai, Professor Zhenhong Li

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Interferograms with short wavelength (e.g., X-band) are usually prone to temporal decorrelation in permafrost regions, leading to the unavailability of sufficient high-coherence interferograms for performing conventional time series InSAR analysis. This paper proposes the utilization of temporary scatterers for the stacking InSAR method, thus enabling extraction of subsidence in a permafrost region with limited SAR images and limited high-coherence interferograms. Such method is termed as the temporary scatterers stacking InSAR (TSS-InSAR). Taking the Gonghe-Yushu highway (about 30 km), part of G214 National Highway in Qinghai province (in a permafrost region), as a case study, this TSS-InSAR approach was demonstrated in detail and implemented. With 10 TerraSAR-X images acquired during the period from May 2015 to August 2015, the subsidence along this highway was extracted. In this case the lack of a consistent number of SAR acquisitions limits the possibility to perform other conventional time series InSAR analysis. The results show that the middle part of this highway is in the thermokarst and seasonal frozen soil area, and its accumulated subsidence reach up to 10 cm in 110 days. The thawing phenomena is still the main reason for the instability of highway. The results demonstrate that the TSS-InSAR method can effectively extract the subsidence information in a challenging scenario with limited X-band SAR images and limited high-coherence interferograms, where other time series InSAR-based techniques cannot be applied in a simple way.


Publication metadata

Author(s): Dai K, Liu G, Li Z, Ma D, Wang X, Zhang B, Tang J, Li G

Publication type: Article

Publication status: Published

Journal: Sensors

Year: 2018

Volume: 18

Issue: 6

Online publication date: 08/06/2018

Acceptance date: 05/06/2018

Date deposited: 26/06/2018

ISSN (electronic): 1424-8220

Publisher: MDPI AG

URL: https://doi.org/10.3390/s18061876

DOI: 10.3390/s18061876


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Funding

Funder referenceFunder name
15ZA0059
2016T002-E
15ZA0060
2014-K6-010
41474003
41771402
2017YFB0502704
E21608
SKLGED2018-5-3-E

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