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#landslides

2 posts2 participants0 posts today
Public
Anita Graser 🇪🇺🇺🇦🇬🇪

Thrilled to share our latest publication "Visualizing uncertainties in landslide susceptibility modelling using bivariate mapping" nhess.copernicus.org/articles/

What’s inside:
✅ A new way to jointly visualize susceptibility & uncertainty in landslide prediction
✅ Practical, open-source tools for implementation in R and QGIS

Loved the interdisciplinarity of this project

nhess.copernicus.orgBrief communication: Visualizing uncertainties in landslide susceptibility modelling using bivariate mappingAbstract. Effectively communicating uncertainties inherent to statistical models is a challenging yet crucial aspect of the modelling process. This is particularly important in applied research, where output is used and interpreted by scientists and decision-makers alike. In disaster risk reduction, susceptibility maps for natural hazards are vital for spatial planning and risk assessment. We present a novel type of landslide susceptibility map that jointly visualizes the estimated susceptibility and the corresponding prediction uncertainty, using an example from a mountainous region in Carinthia, Austria. We also provide implementation guidelines to create such maps using popular free and open-source software packages.
#DisasterRiskReduction#Landslides#QGIS
Public
Dr. Eric J. Fielding, PhD

NASA Radar Imagery Reveals Details About Los Angeles-Area Landslides. Landslides on Palos Verdes peninsula have been moving rapidly in last two years. NASA airborne radar called UAVSAR flies on piloted NASA planes and measures displacements of the ground surface using InSAR analysis. We requested flights in three directions to map motion of landslides on the Palos Verdes peninsula next to Los Angeles. #NASA #NASA_JPL #InSAR #radar #landslides

jpl.nasa.gov/news/nasa-radar-i

NASA Jet Propulsion Laboratory (JPL)NASA Radar Imagery Reveals Details About Los Angeles-Area LandslidesAnalysis of data from NASA radar aboard an airplane shows that the decades-old active landslide area on the Palos Verdes Peninsula has expanded.
Public
Anita Graser 🇪🇺🇺🇦🇬🇪

I really enjoyed the interdisciplinary collaboration sparked by the gAia project on predicting #landslides, resulting in our recent #preprint:

📝 "Visualizing uncertainties in landslide susceptibility modeling using bivariate mapping"

nhess.copernicus.org/preprints

nhess.copernicus.orgBrief communication: Visualizing uncertainties in landslide susceptibility modeling using bivariate mappingAbstract. Effectively communicating uncertainties inherent to statistical models is a challenging yet crucial aspect of the modeling process. This is particularly important in applied research, where output is used and interpreted by scientists and decision makers alike. In disaster risk reduction, susceptibility maps for natural hazards are vital for spatial planning and risk assessment. We present a novel type of landslide susceptibility map that jointly visualizes the estimated susceptibility and the corresponding prediction uncertainty, using an example from a mountainous region in Carinthia, Austria. We also provide implementation guidelines to create such maps using popular free and open-source software packages.
#QGIS#RStats#GIScience
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