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This study aims at creating a holistic conceptual approach systematizing the interrelation of (natural) hazards, vulnerability and risk. A general hierarchical risk meta-framework presents potentially affected components of a given system, such as its physical, demographic, social, economic, political or ecological spheres, depending on the particular hazard. Based on this general meta-framework, measurable indicators are specified for the system "urban area" as an example. This framework is used as an outline to identify the capabilities of remote sensing to contribute to the assessment of risk. Various indicators contributing to the outline utilizing diverse remote sensing data and methods are presented. Examples such as built-up density, main infrastructure or population distribution identify the capabilities of remote sensing within the holistic perspective of the framework. It is shown how indexing enables a multilayer analysis of the complex and small-scale urban landscape to take different types of spatial indicators into account to simulate concurrence. The result is an assessment of the spatial distribution of risks within an urban area in the case of an earthquake and its secondary threats, using an inductive method. The results show the principal capabilities of remote sensing to contribute to the identification of physical and demographic aspects of vulnerability, as well as provide indicators for the spatial distribution of natural hazards. Aspects of social, economic or political indicators represent limitations of remote sensing for an assessment complying with the holistic risk framework.

Abstract. This study aims at creating a holistic conceptual approach systematizing the interrelation of (natural) hazards, vulnerability and risk. A general hierarchical risk meta-framework presents potentially affected components of a given system, such as its physical, demographic, social, economic, political or ecological spheres, depending on the particular hazard. Based on this general meta-framework, measurable indicators are specified for the system "urban area" as an example. This framework is used as an outline to identify the capabilities of remote sensing to contribute to the assessment of risk. Various indicators contributing to the outline utilizing diverse remote sensing data and methods are presented. Examples such as built-up density, main infrastructure or population distribution identify the capabilities of remote sensing within the holistic perspective of the framework. It is shown how indexing enables a multilayer analysis of the complex and small-scale urban landscape to take different types of spatial indicators into account to simulate concurrence. The result is an assessment of the spatial distribution of risks within an urban area in the case of an earthquake and its secondary threats, using an inductive method. The results show the principal capabilities of remote sensing to contribute to the identification of physical and demographic aspects of vulnerability, as well as provide indicators for the spatial distribution of natural hazards. Aspects of social, economic or political indicators represent limitations of remote sensing for an assessment complying with the holistic risk framework.

International audience ; This study aims at creating a holistic conceptual approach systematizing the interrelation of (natural) hazards, vulnerability and risk. A general hierarchical risk meta-framework presents potentially affected components of a given system, such as its physical, demographic, social, economic, political or ecological spheres, depending on the particular hazard. Based on this general meta-framework, measurable indicators are specified for the system "urban area" as an example. This framework is used as an outline to identify the capabilities of remote sensing to contribute to the assessment of risk. Various indicators contributing to the outline utilizing diverse remote sensing data and methods are presented. Examples such as built-up density, main infrastructure or population distribution identify the capabilities of remote sensing within the holistic perspective of the framework. It is shown how indexing enables a multilayer analysis of the complex and small-scale urban landscape to take different types of spatial indicators into account to simulate concurrence. The result is an assessment of the spatial distribution of risks within an urban area in the case of an earthquake and its secondary threats, using an inductive method. The results show the principal capabilities of remote sensing to contribute to the identification of physical and demographic aspects of vulnerability, as well as provide indicators for the spatial distribution of natural hazards. Aspects of social, economic or political indicators represent limitations of remote sensing for an assessment complying with the holistic risk framework.

This study aims at creating a holistic conceptual approach systematizing the interrelation of (natural) hazards, vulnerability and risk. A general hierarchical risk meta-framework presents potentially affected components of a given system, such as its physical, demographic, social, economic, political or ecological spheres, depending on the particular hazard. Based on this general meta-framework, measurable indicators are specified for the system "urban area" as an example. This framework is used as an outline to identify the capabilities of remote sensing to contribute to the assessment of risk. Various indicators contributing to the outline utilizing diverse remote sensing data and methods are presented. Examples such as built-up density, main infrastructure or population distribution identify the capabilities of remote sensing within the holistic perspective of the framework. It is shown how indexing enables a multilayer analysis of the complex and small-scale urban landscape to take different types of spatial indicators into account to simulate concurrence. The result is an assessment of the spatial distribution of risks within an urban area in the case of an earthquake and its secondary threats, using an inductive method. The results show the principal capabilities of remote sensing to contribute to the identification of physical and demographic aspects of vulnerability, as well as provide indicators for the spatial distribution of natural hazards. Aspects of social, economic or political indicators represent limitations of remote sensing for an assessment complying with the holistic risk framework.

Abstract. Human immediate response is contextualized into different time compartments reflecting the tsunami early warning chain. Based on the different time compartments the available response time and evacuation time is quantified. The latter incorporates accessibility of safe areas determined by a hazard assessment, as well as environmental and demographic impacts on evacuation speed properties assessed using a Cost Distance Weighting GIS approach. Approximately 4.35 million Indonesians live in tsunami endangered areas on the southern coasts of Sumatra, Java and Bali and have between 20 and 150 min to reach a tsunami-safe area. Most endangered areas feature longer estimated-evacuation times and hence the population possesses a weak immediate response capability leaving them more vulnerable to being directly impacted by a tsunami. At a sub-national scale these hotspots were identified and include: the Mentawai islands off the Sumatra coast, various sub-districts on Sumatra and west and east Java. Based on the presented approach a temporal dynamic estimation of casualties and displacements as a function of available response time is obtained for the entire coastal area. As an example, a worst case tsunami scenario for Kuta (Bali) results in casualties of 25 000 with an optimal response time (direct evacuation when receiving a tsunami warning) and 120 000 for minimal response time (no evacuation). The estimated casualties correspond well to observed/reported values and overall model uncertainty is low with a standard error of 5%. The results obtained allow for prioritization of intervention measures such as early warning chain, evacuation and contingency planning, awareness and preparedness strategies down to a sub-district level and can be used in tsunami early warning decision support.

Abstract. More than 4 million Indonesians live in tsunami-prone areas along the southern and western coasts of Sumatra, Java and Bali. Although a Tsunami Early Warning Center in Jakarta now exists, installed after the devastating 2004 tsunami, it is essential to develop tsunami risk knowledge within the exposed communities as a basis for tsunami disaster management. These communities need to implement risk reduction strategies to mitigate potential consequences. The major aims of this paper are to present a risk assessment methodology which (1) identifies areas of high tsunami risk in terms of potential loss of life, (2) bridges the gaps between research and practical application, and (3) can be implemented at community level. High risk areas have a great need for action to improve people's response capabilities towards a disaster, thus reducing the risk. The methodology developed here is based on a GIS approach and combines hazard probability, hazard intensity, population density and people's response capability to assess the risk. Within the framework of the GITEWS (German-Indonesian Tsunami Early Warning System) project, the methodology was applied to three pilot areas, one of which is southern Bali. Bali's tourism is concentrated for a great part in the communities of Kuta, Legian and Seminyak. Here alone, about 20 000 people live in high and very high tsunami risk areas. The development of risk reduction strategies is therefore of significant interest. A risk map produced for the study area in Bali can be used for local planning activities and the development of risk reduction strategies.

Abstract. In the framework of the German Indonesian Tsunami Early Warning System (GITEWS) the assessment of tsunami risk is an essential part of the overall activities. The scientific and technical approach for the tsunami risk assessment has been developed and the results are implemented in the national Indonesian Tsunami Warning Centre and are provided to the national and regional disaster management and spatial planning institutions in Indonesia. The paper explains the underlying concepts and applied methods and shows some of the results achieved in the GITEWS project (Rudloff et al., 2009). The tsunami risk assessment has been performed at an overview scale at sub-national level covering the coastal areas of southern Sumatra, Java and Bali and also on a detailed scale in three pilot areas. The results are provided as thematic maps and GIS information layers for the national and regional planning institutions. From the analyses key parameters of tsunami risk are derived, which are integrated and stored in the decision support system of the national Indonesian Early Warning Centre. Moreover, technical descriptions and guidelines were elaborated to explain the developed approach, to allow future updates of the results and the further development of the methodologies, and to enable the local authorities to conduct tsunami risk assessment by using their own resources.

Abstract. Extreme natural events, like e.g. tsunamis or earthquakes, regularly lead to catastrophes with dramatic consequences. In recent years natural disasters caused hundreds of thousands of deaths, destruction of infrastructure, disruption of economic activity and loss of billions of dollars worth of property and thus revealed considerable deficits hindering their effective management: Needs for stakeholders, decision-makers as well as for persons concerned include systematic risk identification and evaluation, a way to assess countermeasures, awareness raising and decision support systems to be employed before, during and after crisis situations. The overall goal of this study focuses on interdisciplinary integration of various scientific disciplines to contribute to a tsunami early warning information system. In comparison to most studies our focus is on high-end geometric and thematic analysis to meet the requirements of small-scale, heterogeneous and complex coastal urban systems. Data, methods and results from engineering, remote sensing and social sciences are interlinked and provide comprehensive information for disaster risk assessment, management and reduction. In detail, we combine inundation modeling, urban morphology analysis, population assessment, socio-economic analysis of the population and evacuation modeling. The interdisciplinary results eventually lead to recommendations for mitigation strategies in the fields of spatial planning or coping capacity.