Using Spatial Regression as a Tool for Permafrost Hazard Assessment: A Case Study of the Hudson Bay Railway ...
The Hudson Bay Railway (HBR) has faced increasing instability and rising maintenance costs due to permafrost thaw, a process accelerated by climate change over the past three decades. Geotechnical investigations have identified the Herchmer Subdivision as the most severely impacted area, with histor...
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| Format: | Article in Journal/Newspaper |
| Language: | English |
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Graduate Studies
2025
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| Online Access: | https://dx.doi.org/10.11575/prism/48570 https://ucalgary.scholaris.ca/handle/1880/120980 |
| Summary: | The Hudson Bay Railway (HBR) has faced increasing instability and rising maintenance costs due to permafrost thaw, a process accelerated by climate change over the past three decades. Geotechnical investigations have identified the Herchmer Subdivision as the most severely impacted area, with historical and contemporary data revealing that previously stable ground is becoming unstable and that the permafrost boundary is shifting northward. As permafrost degradation continues, there is a pressing need for accurate predictions of thaw-related hazards to support infrastructure resilience and maintenance planning along the HBR. To address this challenge, we employed Multiscale Geographically Weighted Regression (MGWR) to identify the key variables contributing to sinkhole formation along the railway. This spatial modeling tool enables the assessment of multiple climatic and ecological factors influencing permafrost degradation while determining their statistical significance. In our MGWR model, ... |
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