Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Seismic Vulnerability of the Italian Roadway Bridge Stock

This study focuses on the seismic vulnerability evaluation of the Italian roadway bridge stock, within the framework of a Civil Protection sponsored project. A comprehensive database of existing bridges (17,000 bridges with different level of knowledge) was implemented. At the core of the study stands a procedure for automatically carrying out state-of-the-art analytical evaluation of fragility curves for two performance levels – damage and collapse – on an individual bridge basis. A webGIS was developed to handle data and results. The main outputs are maps of bridge seismic risk (from the fragilities and the hazard maps) at the national level and real-time scenario damage-probability maps (from the fragilities and the scenario shake maps). In the latter case the webGIS also performs network analysis to identify routes to be followed by rescue teams. Consistency of the fragility derivation over the entire bridge stock is regarded as a major advantage of the adopted approach

"Last-Mile" preparation for a potential disaster

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

Managing Climatic Risks to Combat Land Degradation and Enhance Food security: Key Information Needs

This paper discusses the key information needs to reduce the negative impacts of weather variability and climate change on land degradation and food security, and identifies the opportunities and barriers between the information and services needed. It suggests that vulnerability assessments based on a livelihood concept that includes climate information and key socio-economic variables can overcome the narrow focus of common one-dimensional vulnerability studies. Both current and future climatic risks can be managed better if there is appropriate policy and institutional support together with technological interventions to address the complexities of multiple risks that agriculture has to face. This would require effective partnerships among agencies dealing with meteorological and hydrological services, agricultural research, land degradation and food security issues. In addition a state-of-the-art infrastructure to measure, record, store and disseminate data on weather variables, and access to weather and seasonal climate forecasts at desired spatial and temporal scales would be needed

Urban seismic risk index for Medellín, Colombia, based on probabilistic loss and casualties estimations

The final publication is available at Springer via http://dx.doi.org/10.1007/s11069-015-2056-4Medellín is the second largest city of Colombia with more than 2 million inhabitants according to the latest census and with more than 240,000 public and private buildings. It is located on an intermediate seismic hazard area according to the seismic zonation of Colombia although no destructive earthquakes have occurred having as a consequence low seismic risk awareness among its inhabitants. Using the results of a fully probabilistic risk assessment of the city with a building by building resolution level and considering the dynamic soil response, average annual losses by sectors as well as casualties and other direct effects are obtained and aggregated at county level. Using the holistic evaluation module of the multi-hazard risk assessment CAPRA platform, EvHo, a comprehensive assessment that considered the social fragility and lack or resilience at county level is performed making use of a set of indicators with the objective of capturing the aggravating conditions of the initial physical impact. The urban seismic risk index, USRi, is obtained at county level which is useful to communicate risk to decision-makers and stakeholders besides making easy identifying potential zones that can be problematic in terms of several dimensions of the vulnerability. This case study is an example of how a multidisciplinary research on disaster risk reduction helps to show how risk analysis can be of high relevance for decision-making processes in disaster risk management.Peer ReviewedPostprint (author's final draft

Estimating Impact and Frequency of Risks to Safety and Mission Critical Systems Using CVSS

Many safety and mission critical systems depend on the correct and secure operation of both supportive and core software systems. E.g., both the safety of personnel and the effective execution of core missions on an oil platform depend on the correct recording storing, transfer and interpretation of data, such as that for the Logging While Drilling (LWD) and Measurement While Drilling (MWD) subsystems. Here, data is recorded on site, packaged and then transferred to an on-shore operational centre. Today, the data is transferred on dedicated communication channels to ensure a secure and safe transfer, free from deliberately and accidental faults. However, as the cost control is ever more important some of the transfer will be over remotely accessible infrastructure in the future. Thus, communication will be prone to known security vulnerabilities exploitable by outsiders. This paper presents a model that estimates risk level of known vulnerabilities as a combination of frequency and impact estimates derived from the Common Vulnerability Scoring System (CVSS). The model is implemented as a Bayesian Belief Network (BBN)