4.7 Article

Satellite interferometry for regional assessment of landslide hazard to pipelines in northeastern British Columbia, Canada

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ELSEVIER
DOI: 10.1016/j.jag.2023.103273

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Transportation infrastructure; Pipelines; Ground deformation; Synthetic aperture radar; DInSAR; RADARSAT-2; Sentinel-1; MSBAS; Landslide; British Columbia; Canada

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Pipelines are crucial for transportation infrastructure as they provide a safe and efficient means of transporting oil and gas. Landslide hazards to pipelines can be reduced by using remote sensing techniques, such as radar interferometry, to detect ground deformation. This study shows that readily available Sentinel-1 data can produce high-quality deformation maps capable of detecting slow-moving landslides.
Pipelines are a critical component of transportation infrastructure. They offer the safest and most efficient way to transport large volumes of oil and natural gas from development areas to refineries and consumers. Landslides can damage pipelines resulting in a spill of a toxic substance. However, landslide hazards to pipelines and other infrastructure can be significantly reduced, if the location of landslides is known and the appropriate mitigation measures are taken in advance. Traditional, ground-based methods for mapping areas susceptible to landslides can be expensive and limited. Radar interferometry is a remote sensing technique that measures ground deformation from two Synthetic Aperture Radar (SAR) images. Time series of ground deformation computed from repeatedly acquired SAR data allows us to detect slow-moving, deep-seated landslides over a large area with high spatial resolution and precision. European Space Agency's Sentinel-1 satellite systematically collects SAR data worldwide, and large datasets have been collected since approximately 2016-2017. A combination of improved availability of SAR data, inexpensive processing power and advanced processing techniques designed for large datasets provides an opportunity to map ground deformation on a regional scale. The study's objective is to compare deformation maps, as proxies for landslide identification, computed from commercial RADARSAT-2 data and freely available Sentinel-1 data over a region in northeast British Columbia, Canada, with an extensive network of pipelines. It is concluded that readily available Sentinel-1 data can produce high-quality deformation maps capable of detecting slow-moving landslides. In the study area, hundreds of slow-moving landslides are mapped using hotspot analysis based on Getis-Ord Gi* statistics, and two small regions where landslide activity near the pipelines is particularly significant are studied in detail. Field observations also revealed that slope deformation features formed in the surface sediments consist of colluvium derived from a mix of glaciolacustrine, till and fine-grained sedimentary bedrock.

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