Modeling future population's vulnerability to heat waves
Existing future vulnerability to natural disasters assessments is often limited accounting for projected changes in future climate. However, not only is climate changing, but also populations (aging, social welfare, migration, etc). and urban environments are (increase of green areas, development of high rise buildings etc.). Therefore all these three aspects should be considered when assessing future population's vulnerability.
This innovation uses a Cellular Automata-based model "Metronamica" to model a proxy indicator - urban landscape at micro (building block)-scale. Based on a number of different urban development scenarios, an allocation of urban landscape cells is used to model future social and landscape data (indicators). In the end indicators are weigthed and combined into an vulnerability index which shows which locations might be most vulnerable in the future and where decision makers should take specific action.
Technology validated in relevant environment.
Fidelity of breadboard technology increases significantly. The basic technological components are integrated with reasonably realistic supporting elements so they can be tested in a simulated environment. Examples include “high-fidelity” laboratory integration of components.
Fidelity of breadboard technology increases significantly. The basic technological components are integrated with reasonably realistic supporting elements so they can be tested in a simulated environment. Examples include “high-fidelity” laboratory integration of components.
Model produced a vulnerability index for four urban development scenarios (business as usual, concentration (compact city), urban sprawl and de-central concentration) for Greater Hamburg case study on basis of 250 x 250 meters cells. Index showed a number of critical locations which might have high population's vulnerability to heat waves. Main reasons among high vulnerability was a high percentage of older population, higher percentage of welfare recipients and longer distances to hospitals.
How does it work?
This model was tested in Hamburg case study and used a proxy indicator (Urban Population's Vulnerability Zones (UPVZ)) as a basis for other indicators. UPVZ was modeled by Metronamica (cellular automata-based model). To model UPVZ there was a need to calibrate (which took most of the time) a model. Then based on experts' evaluation four different urban development scenarios were modeled and used to develop four different UPVZ allocations. Next task was to disaggregate 2000 census data by different UPVZ classes and added an assumption that this data will not change over a time. Finally data was modeled based on UPVZ allocations and was compiled into an index which showed potential population's vulnerability to heat waves in Greater Hamburg.
By logging in you can access to more detailed information on the innovation