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

Remote sensing technology for disaster mitigation and regional infrastructure planning in urban area: a review

A Very high intensity of regional development is ubiquitous in urban areas. Therefore, urban development requires a proper spatial development strategy in many facets, especially social aspect and disaster potential. The essence of social aspect lies in the prevailing norms and local wisdom that have long existed and become the basis of community life. Inducing various effects on infrastructure development, disaster potential has to be considered as well. Disaster mitigation measures can start with the use of continually developing remote sensing technology, which provides a basis for preparing sustainable development planning. The realization of these measures in urban areas demands specific adjustment to the environmental conditions. This study aimed to examine the capacity of remote sensing data to support disaster mitigation and infrastructure planning based on energy conservation in urban areas. The results indicate that remote sensing technology can be an option for sustainable development planning in urban areas

Approaches to Disaster Management

Approaches to Disaster Management regards critical disaster management issues. Ten original research reports by international scholars centered on disaster management are organized into three general areas of hazards and disaster management. The first section includes discussions of perspectives on vulnerability and on evolving approaches to mitigation. The second section highlights approaches to improve data use and information management in several distinct applications intended to promote prediction and communication of hazard. The third section regards the management of crises and post-event recovery in the private sector, in the design of urban space and among the victims of disaster. This volume contributes both conceptual and practical commentary to the disaster management literature

Seismic Risk Assessment Tools Workshop

Held in the European Crisis Management Laboratory on 11-12 May 2017, the Workshop brought together on one side the developers of some of the most widely used modern seismic risk assessment tools and on the other a number of Civil Protection authorities from countries of the European Civil Protection Mechanism. The objective was to demonstrate the use and capabilities of the tools, explore the possible use in near-real-time impact assessment and promote their use in risk planning and disaster response. The systems presented in the workshop demonstrated a very high sophistication and increased flexibility in accepting data from a large number of sources and formats. Systems that were initially developed on a national scale can now work on a global level with little effort and the use of global-scale exposure data is almost seamless. An urgent need for more accurate exposure data being openly available was identified, as well as the need of proper use of the fragility curves. Inter-system collaboration and interoperability in some cases to increase ease of use was greatly appreciated and encouraged. All systems participated in a real-time simulation exercise on previously unknown seismic data provided by the JRC; some additional automation might be in order, but in general all systems demostrated a capacity to produce results on a near-real-time basis. The demonstrations were unanimously welcomed as very useful by the participating Civil Protection Authorities, most of which are either using a locally-developed system of moving towards using one of those presented in the workshop.JRC.E.1-Disaster Risk Managemen

The Acceptance of Using Information Technology for Disaster Risk Management: A Systematic Review

The numbers of natural disaster events are continuously affecting human and the world economics. For coping with disaster, several sectors try to develop the frameworks, systems, technologies and so on. However, there are little researches focusing on the usage behavior of Information Technology (IT) for disaster risk management (DRM). Therefore, this study investigates the affecting factors on the intention to use IT for mitigating disaster’s impacts. This study conducted a systematic review with the academic researches during 2011-2018. Two important factors from the Technology Acceptance Model (TAM) and others are used in describing individual behavior. In order to investigate the potential factors, the technology platforms are divided into nine types. According to the findings, computer software such as GIS applications are frequently used for simulation and spatial data analysis. Social media is preferred among the first choices during disaster events in order to communicate about situations and damages. Finally, we found five major potential factors which are Perceived Usefulness (PU), Perceived Ease of Use (PEOU), information accessibility, social influence, and disaster knowledge. Among them, the most essential one of using IT for disaster management is PU, while PEOU and information accessibility are more important in the web platforms

Visual analytics of location-based social networks for decision support

Recent advances in technology have enabled people to add location information to social networks called Location-Based Social Networks (LBSNs) where people share their communication and whereabouts not only in their daily lives, but also during abnormal situations, such as crisis events. However, since the volume of the data exceeds the boundaries of human analytical capabilities, it is almost impossible to perform a straightforward qualitative analysis of the data. The emerging field of visual analytics has been introduced to tackle such challenges by integrating the approaches from statistical data analysis and human computer interaction into highly interactive visual environments. Based on the idea of visual analytics, this research contributes the techniques of knowledge discovery in social media data for providing comprehensive situational awareness. We extract valuable hidden information from the huge volume of unstructured social media data and model the extracted information for visualizing meaningful information along with user-centered interactive interfaces. We develop visual analytics techniques and systems for spatial decision support through coupling modeling of spatiotemporal social media data, with scalable and interactive visual environments. These systems allow analysts to detect and examine abnormal events within social media data by integrating automated analytical techniques and visual methods. We provide comprehensive analysis of public behavior response in disaster events through exploring and examining the spatial and temporal distribution of LBSNs. We also propose a trajectory-based visual analytics of LBSNs for anomalous human movement analysis during crises by incorporating a novel classification technique. Finally, we introduce a visual analytics approach for forecasting the overall flow of human crowds