Earth Observations and Imagery Science to Assess and Forecast Risk and Resilience of Communities and Infrastructures dur to Climate Change
Earth Observations and Imagery Science to Assess and Forecast Risk and Resilience of Communities and Infrastructures dur to Climate Change
Session ID#: 124041
Session Description:
The availability of large volume of imagery at high spatio-temporal resolutions along with advancements in geospatial and computational sciences have enabled implementation of near real-time analytics and modeling approaches to inform decisions about risk, resilience, response and recovery. Even during the COVID-19 pandemic, earth observation data have been useful in understanding the economic and environmental impacts of the pandemic.
This session invites papers using machine learning, image science, geo-visualization and geo-computation techniques along with imagery and static/dynamic datasets to (i) understand the interaction between extreme events and socio-physical systems, (ii) assess risk and resilience of communities and infrastructures, (iii) economic and environmental impacts of extreme events and public health disasters, (iv) visualize and communicate risk to a heterogenous audience to help with preparedness and decision-making activities.
Co-Sponsor(s):
- ASPRS: American Society for Photogrammetry and Remote Sensing -
- EGU: European Geosciences Union -
- WCRP: World Climate Research Programme -
Index Terms:
0240 Public health [GEOHEALTH]
1640 Remote sensing [GLOBAL CHANGE]
1910 Data assimilation, integration and fusion [INFORMATICS]
4327 Resilience [NATURAL HAZARDS]
Primary Convener: Bandana Kar, Oak Ridge National Laboratory, Oak Ridge, TN, United States
Convener: Margaret T Glasscoe, JPL-Caltech, Pasadena, CA, United States
Primary Liaison: ZhiQiang Chen, University of Missouri Kansas City, Kansas City, MO, United States
See more of: Natural Hazards