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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.
‘One size fits all’ does not work in politics
David Cottam says we need to be more tolerant, nonjudgmental and understanding of the cultural backgrounds and stages of development of different nations.
ASTP/ONC to exercise enforcement discretion for health IT developers for certain certification criteria - Florida Hospital News and Healthcare Report
NOVEMBER 26, 2025 – The Assistant Secretary for Technology Policy/Office of the National Coordinator for Health IT announced Nov. 24 that it will exercise temporary enforcement discretion for health IT […]
Western Mass filmmaker to screen debut film ‘Splinter’ at Northampton’s Academy of Music
All proceeds from the screening will be donated to the Center for Human Development in Springfield in a tribute to mental health care professionals.