SLIDE 1
2101: A Disaster Risk Odyssey Vitor Silva, Global Earthquake Model - - PowerPoint PPT Presentation
2101: A Disaster Risk Odyssey Vitor Silva, Global Earthquake Model - - PowerPoint PPT Presentation
2101: A Disaster Risk Odyssey Vitor Silva, Global Earthquake Model Foundation Hazard Exposure Vulnerability Optical imagery (and derived products such as DEMs) enable the identification of geomorphological signatures of faulting. InSAR
SLIDE 2
SLIDE 3
Optical imagery (and derived products such as DEMs) enable the identification of geomorphological signatures of
- faulting. InSAR technology can also support mapping regions of focused geodetic strain, which could be due to strain
accumulation on a fault (figure provided by Ekbal Hussain)
SLIDE 4
Mapping faults around the city of Santiago, Chile
SLIDE 5
Before 1975 1975 - 1990 1990 - 2010 After 2010
Recently released satellite data provides urban footprints according to the vintage. It can support the development of new exposure datasets, or the improvement of the spatial resolution of existing datasets.
SLIDE 6
Satellite data Crowd sourcing initiatives such as OpenStreetMap will revolutionize disaster risk assessment and management, granted that the level of detail of the structures features can be improved.
SLIDE 7
Hazard Intensity
SLIDE 8
Insufficient empirical data Incomplete analytical models
SLIDE 9
Satellite data tailed data obtained via remote sensing, aerial imagery or drones will allow a better understanding of the spatial distributio
- f damage, and through machine learning, an improvement of the existing vulnerability models.
SLIDE 10
SLIDE 11
Undamaged network Damaged network
SLIDE 12
SLIDE 13
SLIDE 14
1965 1975 1985 1995 2005 2015 2025 2035 2045 2055
$- $20 $40 $60 $80 $100 $120 $140 $160 $180 1973 1984 2000 2011 2025 2050
Millions
W M PC CR OTH ADO Total: 1974-2011 Total: 2025-2050
Prediction of the evolution of seismic risk (economic losses) for Costa Rica
SLIDE 15