| Title | Satellite interferometry for regional assessment of landslide hazard to pipelines in northeastern British Columbia, Canada |
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| Author | Samsonov, S ;
Blais-Stevens, A |
| Source | International Journal of Applied Earth Observation and Geoinformation vol. 118, 103273, 2023 p. 1-13, https://doi.org/10.1016/j.jag.2023.103273
 Open Access |
| Image |  |
| Year | 2023 |
| Alt Series | Natural Resources Canada, Contribution Series 20220090 |
| Publisher | Elsevier |
| Document | serial |
| Lang. | English |
| Media | paper; digital; on-line |
| File format | pdf; html |
| Province | British Columbia |
| NTS | 84D; 84E; 84L; 84M; 94A; 94B; 94C; 94D; 94E; 94F; 94G; 94H; 94I; 94J; 94K; 94L; 94M; 94N; 94O; 94P |
| Lat/Long WENS | -126.3333 -119.0000 59.1667 56.5000 |
| Subjects | Transport; Science and Technology; regional geology; fossil fuels; pipelines; deformation; landslides; synthetic aperture radar surveys (SAR) |
| Illustrations | location maps; tables; diagrams; charts; satellite imagery |
| Program | Canada Centre for Remote Sensing People Support and Leadership |
| Released | 2023 03 24 |
| Abstract | 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. |
| Summary | (Plain Language Summary, not published)
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 already 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. In this study, we compare deformation
maps, as proxies of landslide hazard, 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 located in proximity to slow-moving
landslides. We conclude that readily available Sentinel-1 data can produce high-quality deformation maps capable of detecting slow-moving landslides. In the study area, we observe hundreds of slow-moving landslides. We then focus on two small regions
where landslide activity in the proximity to the pipelines is particularly significant. |
| GEOSCAN ID | 330133 |
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