Abstract: It is frequently conveyed, especially in the media, an idea of “increasing impact of natural hazards” typically attributed to their rising frequency and/or growing vulnerability of populations. However, for certain hazard types, this may be mostly a result of increasing population exposure due to phenomenal global population growth, especially in the most hazardous areas. We investigate temporal changes in potential global population exposure and impacts from earthquakes in the XXth century. Spatial analysis is used to combine historical population distributions with a seismic intensity map. Changes in number of victims were also analyzed, while controlling for the progress in frequency and magnitude of hazard events. There is also a focus on mega-cities and implications of fast urbanization for exposure and risk. Results illustrate the relevance of population growth and exposure for risk assessment and disaster outcome, and underline the need for conducting detailed global mapping of settlements and population distribution.

Abstract: In this paper we present a new approach to enhance information extraction from social media that relies upon the geographical relations between twitter data and flood phenomena. We use specific geographical features like hydrological data and digital elevation models to analyze the spatiotemporal distribution of georeferenced twitter messages. This approach is applied to examine the River Elbe Flood in Germany in June 2013. Although recent research has shown that social media platforms like Twitter can be complementary information sources for achieving situation awareness, previous work is mostly concentrated on the classification and analysis of tweets without resorting to existing data related to the disaster, e.g. catchment borders or sensor data about river levels. Our results show that our approach based on geographical relations can help to manage the high volume and velocity of social media messages and thus can be valuable for both crisis response and preventive flood monitoring.

Abstract: Technological advances in both distributed cooperative work and web-map services have the potential to support distributed and collaborative time-critical decision-making for crisis response. We address this potential through the theoretical perspective of distributed cognition and apply this perspective to development of a geocollaborationenabled web application that supports coordinated crisis management activities. An underlying goal of our overall research program is to understand how distributed cognition operates across groups working to develop both awareness of the geographic situation within which events unfold, and insights about the processes that have lead to that geographic situation over time. In this paper, we present our preliminary research on a web application that addresses these issues. Specifically, the application (key parts of which are implemented) enables online, asynchronous, map-based interaction between actors, thus supporting distributed spatial and temporal cognition, and, more specifically, situational awareness and subsequent action in the context of humanitarian disaster relief efforts.

Abstract: Understanding the characteristics of the spatiotemporal distribution of a population, which varies according to the time of the day and the day of the week (weekday or weekend), is one of the most important issues in the field of urban disaster mitigation planning. However, the existing Person Trip Survey data based on weekdays is not appropriate for estimating the spatiotemporal distribution of population on weekends. In the present study, we proposed a method for converting existing Person Trip Survey data from a weekday base to a weekend base and examined the differences in the spatiotemporal distribution of the population. Using these databases, we attempted to compare the number of deaths due to building collapse estimated for weekdays and weekends for various districts in the Tokyo Metropolitan area.