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Using network science to evaluate landslide hazards on Big Sur Coast, California, USA
Abstract. Landslides, ranging from slips to catastrophic failures, pose significant challenges for prediction. This study employs a physically inspired framework to assess landslide hazard at a regional scale (Big Sur Coast, California). Our approach integrates techniques from the study of complex systems with multivariate statistical analysis to identify areas prone to landslide hazards. We successfully apply a technique originally developed on the 2017 Mud Creek landslide and refine our statistical metrics to characterize landslide hazard within a larger geographical area. Our method is compared against factors such as landslide location, slope, displacement, precipitation, and InSAR coherence using multivariate statistical analysis. Our network analyses, which incorporates spatiotemporal dynamics, perform better as a monitoring technique than traditional methods. This approach has potential for real-time monitoring and evaluating landslide hazard across multiple sites.
Why we have to continue with animal testing for medical research
Letters: Dr Robin Lovell-Badge and Prof Emma Robinson respond to an editorial on using new technologies to reduce the reliance on animal experiments
Shabana Mahmood and my surprise at teenagers’ views on immigration
Letters: Rev Dr Michael Fox responds to an article by Nesrine Malik on the home secretary using her ‘story’ to silence criticism of her policies
Science Notes: Revisiting Viking Age art using microwear analysis
Archaeologists are increasingly revisiting long-held theories about the past and highlighting how these ideas need to be updated in light of evolving eviden ...
North Tyneside GP says debt stress causing mental health issues
GP Dr Kamlesh Sreekissoon says his patients are working multiple jobs to make ends meet.
Scientists mapped the shape of a supernova for the first time ever – and it's not what we expected: Space photo of the week
Astronomers using data from the Very Large Telescope (VLT) have revealed that the initial "breakout" phase of a supernova is elongated, not perfectly spherical.