Risk and vulnerability assessment of urban areas
 Population |
| |
Risk is imaginary, and thus implies uncertainty. Risk management deals with prognoses about future events. In order to be suitably prepared, access to substantial, up-to-date and area-wide information is mandatory. Risk is the interaction of a hazard and the vulnerability of a system. Remote sensing contributes spatial information on both.
On the one hand using a digital elevation model based, various contributions to assess the spatial distribution of potentially endangered areas are possible. The location of urbanized areas has a great influence on their vulnerability and exposure. Orographic information or distance to expected sources of natural hazards allows a first assessment of a spatial pattern of exposure. The utilization of a digital elevation model enables the integration of orographic surface information when assessing high risk zones like flood- or tsunami-prone areas based on height information, or landslide prone slopes derived from the terrain’s steepness.
On the other hand the city model enables to spatially analyse pattern of vulnerability of the potentially affected system. The built-up density distribution reflects the quantity of potentially affected structures. The identification of open spaces, their location and dimension provides information on potentially safe and sheltered areas. In addition the main street network extracted from the land-cover classification supports the assessment of accessibility.
Interdisciplinary value-adding for remote sensing products is realized by the synergistic usage of the derived structural building characteristics from high resolution satellite data and methods of civil engineering. The assessment of the expected damage to buildings in case of an earthquake impact is based on the classification of buildings using physical parameters derived from remote sensing and the so-called capacity-spectrum method from civil engineering. Furthermore, knowledge of the physical structure of urban morphology can be utilized to indirectly derive further parameters crucial for risk management. The basic idea behind inferring the population distribution is based on a correlation between the structural characteristics of the urban environment and its population. In combination with land use knowledge the capabilities of remote sensing enable to calculate dynamic behaviour of urban population.
This precise knowledge allows an analysis of population flows, carrying capacities, localization of spatial and temporal population patterns, catchments areas, necessary supply and disposal units, and an assessment potential to quantify potential emergency measures. In short, the methodologies provide up-to-date data and correctly dimensioned information for decision-makers managing highly dynamic urban areas.