Issues
Areas
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TRL Level
SRL Level
The Albanian coastline has been declining in recent years due to coastal erosion and uncontrolled...
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.
Developed by Institute of Environmental Engineering, Kaunas University of Technology
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.
See more information about this level and the TRL and SRL levels.
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.
Limitations/conditions under which this innovation does not work or is less effective
First of all, this model requires a proxy indicator. For tested case study, a proxy indicator was modeled using a cellular automata-based software called “Metronamica” (a commercial product), however there might be possibilities to use alternative models to model a required proxy indicator. Case study was done for Greater Hamburg, Germany. For other case studies, additional research should be done (i.e. available datasets, future urban development scenarios, population’s projections etc.)
Added value
This innovation is a first such future population’s vulnerability to natural disasters model which uses not only a future climate, but also future social and urban landscape data. This is not a projection, but more as an exploration tool which helps local decision makers to see how different urban development patterns would affect city differently and what local areas could have a greater effect by future 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.
Developed by Institute of Environmental Engineering, Kaunas University of Technology
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.
The main components of the system have been tested separately, and an initial integration exercise has been conducted.
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.
Limitations/conditions under which this innovation does not work or is less effective
First of all, this model requires a proxy indicator. For tested case study, a proxy indicator was modeled using a cellular automata-based software called “Metronamica” (a commercial product), however there might be possibilities to use alternative models to model a required proxy indicator. Case study was done for Greater Hamburg, Germany. For other case studies, additional research should be done (i.e. available datasets, future urban development scenarios, population’s projections etc.)
Added value
This innovation is a first such future population’s vulnerability to natural disasters model which uses not only a future climate, but also future social and urban landscape data. This is not a projection, but more as an exploration tool which helps local decision makers to see how different urban development patterns would affect city differently and what local areas could have a greater effect by future heat waves.
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