Submission #8

Submission information
Submitted by Anonymous
Thursday, March 17, 2011 - 07:56
98.165.228.36
Serge Rey
Srey@asu.edu
Monitoring Social Vulnerability to Natural Hazards
For long-term emergency management, it is important to monitor the spatial distributions of vulnerable populations exposed to natural hazards and establish place-based plans for responding to and recovering from disaster events. A group of regional planners would like to estimate social vulnerability for the U.S. area and examine how its spatial distributions have changed over time. They particularly want to identify which places have experienced a continuous increase or decrease in their vulnerability.
Planners, decision-makers, analysts
- Planners access a web-mapping interface of the CyberGIS Gateway where they can estimate and visualize social vulnerability and its temporal changes.
- Analysts may want to access back-end vulnerability analysis tools through web services in order to feed the analysis results into other analysis tools.
- Decision-makers may not directly visit the CyberGIS Gateway. They instead use external web applications that show only vulnerability maps generated by the CyberGIS Gateway.
- Database necessary for estimating social vulnerability indices (e.g., historical census data)
- Computational tools to estimate the indices and their spatial autocorrelation (e.g., global and local indicators of spatial autocorrelation)
- Computational tools to estimate the trend of temporal changes of the indices at each spatial observation
- Online mapping services and applications to generate and render vulnerability maps
1. The planners access the web-mapping interface and request vulnerability estimation for a specific time period.
2. The interface shows choropleth or density maps of the estimated vulnerability index for each time point.
3. The planners use map animation or other advanced interaction tools to examine the spatial patterns of the estimated index. They might see some clustering patterns during the map interactions. In such case, they test whether or not the observed spatial clustering is statistically significant.
4. The planners now estimate the trends in the temporal changes of the index for each observation.
5. The interface generates a map of observations at each of which the index has significantly increased.
6. During the above analysis, the planners select a few important maps and feed them into a web application that relevant decision-makers often use.
7. Some analysts may have other source data for the vulnerability estimation but cannot share it through the CyberGIS Gateway. In such case, they use the additional web services interface to estimate the vulnerability index for their own data.
- The planners obtained vulnerability maps and identified the areas with increasing or decreasing vulnerability.
- The planners obtained vulnerability maps but could not identify any areas that have experienced consistent changes in their vulnerability.
- The planners failed to obtain vulnerability maps.