Abstract: This paper describes how enthusiasts from the radio-amateur and red-cross communities developed and applied position tracking to search and rescue services in Norway. This was based on the APRS standard which has been used by radio-amateurs for some time.
The document describes how radio-amateurs designed a tracking device which was robust and simple to use along with a web-based online service, a map server, to display positions along with other geographical information on electronic maps. The software for the tracker and the map server is free and open source. This system has been used in a number of search and rescue missions in Norway since 2009, to support decisions making in the command and control centre.

Abstract: As a future member of the European Union (EU), Croatia has decided to implement EU Directive 2002/59/EC of the European Parliament and of the Council binding all EU member states to define places of refuge for ships in need of assistance off their coasts, or to develop techniques for providing assistance to such ships. Consequently, the Ministry of the Sea, Tourism, Transport and Development of the Republic of Croatia has initiated a project for developing an effective Decision Support System (DSS) for defining the places of refuge for ships in distress at sea. Such a system would include a model based upon GIS and different operational research models, which would eventually result in establishing an integral DSS. Starting points for analysis are shipping corridors, and 380 potential locations for places of refuge designated in the official navigational pilot book. Multicriteria analysis, with GIS-generated input data, would be used to establish worthiness of a place of refuge for each ship category, taking into account kinds of accident. Tables of available intervention resources would be made, as well as analysis of their availability in respect of response time, and quantitative and qualitative sufficiency.

Abstract: During large scale crisis response operations there is an acute and continuous need to efficiently and quickly allocate a dynamically changing supply of resources. In this paper we are proposing a system, which uses polls to seamlessly discover, request, collect and aggregate information from engaged resource providers using the web or mobile devices. At the same time we aim to integrate information from sources such as sensors deployed on incident sites, publicly available open data, corporate legacy systems or documents stored on remote locations. The overall process of such Poll Sourcing also encompasses reservation and order of suitable resources. We provide a validation scenario concerning reservation of hospital beds during a mass casualty incident.

Abstract: Social media platforms, like Twitter, are increasingly used by billions of people internationally to share information. As such, these platforms contain vast volumes of real-time multimedia content about the world, which could be invaluable for a range of tasks such as incident tracking, damage estimation during disasters, insurance risk estimation, and more. By mining this real-time data, there are substantial economic benefits, as well as opportunities to save lives. Currently, the COVID-19 pandemic is attacking societies at an unprecedented speed and scale, forming an important use-case for social media analysis. However, the amount of information during such crisis events is vast and information normally exists in unstructured and multiple formats, making manual analysis very time consuming. Hence, in this paper, we examine how to extract valuable information from tweets related to COVID-19 automatically. For 12 geographical locations, we experiment with supervised approaches for labelling tweets into 7 crisis categories, as well as investigated automatic priority estimation, using both classical and deep learned approaches. Through evaluation using the TREC-IS 2020 COVID-19 datasets, we demonstrated that effective automatic labelling for this task is possible with an average of 61% F1 performance across crisis categories, while also analysing key factors that affect model performance and model generalizability across locations.

Abstract: Previous research claimed that organizational stress, due to task complexity and time pressure, leads to considerably negative effects on the decision-making performance of individuals and organizations. At the same time, intellectual capital (IC), in providing intangible internal and external organizational assets has a positive effect on organizational decision-making performance. This paper develops a structural equation model to analyze the relationships among IC, task complexity, time pressure and decision-making performance. Empirical data are collected from 374 participants, who are from universities, institutes, enterprises, government, with different occupations and expertise. We present two conclusions. First, IC consisting of internal capital, human capital and external capital leads to a reduced complexity of tasks and reduced time pressure and hence reduced organizational stress. Second, reduced organizational stress results in higher levels of performance for organizational decision-making.

Abstract: The emotional qualities of a report play an important role in the evaluation of eye witness reports in crisis centers. Human operators in the crisis center can use the amount of anxiety and stress detected in a spoken report to rapidly estimate the possible impact and urgency of a report and the appropriate response to the reporter. This paper presents ongoing work in automated multi-modal emotion sensing of crisis reports in order to reduce the cognitive load on human operators. Our approach is based on the work procedures adopted by the crisis response center Rijnmond environmental agency (DCMR) and assumes a spoken dialogue between a reporter and a crisis control center. We use an emotion model based on conceptual graphs that is continually evaluated while the dialogue continues. We show how the model can be applied to interpret crisis report in a fictional toxic gas dispersion scenario.

Abstract: Community-based disaster response is gaining attention in the United States because of major problems with domestic disaster recovery over the last decade. A social network analysis approach is used to illustrate how community-academic partnerships offer one way to leverage information about existing, mediated relationships with the community through trusted actors. These partnerships offer a platform that can be used to provide entré into communities that are often closed to outsiders, while also allowing greater access to community embedded physical assets and human resources, thus facilitated more culturally appropriate crisis response. Using existing, publically available information about funded community-academic partnerships in Wisconsin, USA, we show how social network analysis of these meta-organizations may provide critical information about both community vulnerabilities in disaster and assist in rapidly identifying these community resources in the aftermath of a crisis event that may provide utility for boundary spanning crisis information systems.

Abstract: This study attempted to evaluate the utility of the Incident Command System (ICS) in varying disaster contexts. ICS is mandated in the United States and practitioners assert that it is an effective organizing system for emergency management. However, researchers contend that the utility of ICS is conflated with inter-team familiarity gained during ICS exercises. A military team-in-the-loop simulator was customized to represent the problems, resources, and command structures found in civilian led disaster management teams. A modified single case design drawn from behavioral psychology was used to explore possible casual relationships between changes team heterogeneity and performance. The design also allowed for the evaluation of improvisation on performance. Further, psychological factors that may underpin improvisation were explored. In addition to some preliminary empirical findings, the successes and difficulties in adapting the DDD simulator are briefly discussed as part of an effort to achieved greater interdisciplinary integration.

Abstract: Crises range from global catastrophes to personal disasters. However, systematic inquiry on crises rarely employs a comparative approach to examine commonalities between these seemingly very different events. We argue here that individual psychosocial disasters can inform a broader discussion on crises. Our approach applies general crisis theory to a smartphone based psychosocial support system for US military veterans. We engaged in a process designed to explore how veteran peer-to-peer mentorship can be augmented with IS support to display potential early warning signs as first step toward preventative intervention for high risk behaviors. To gain a better understanding of how military veterans might benefit from such a system, this article focuses on a community collaborative design process. The co-design process used the Small Stories method, allowing important cultural characteristics of to emerge, illuminating considerations in IS design with military veterans, and highlighting how humans think about crisis events at the individual level.

Abstract: Face mask scarcity in the United States hindered early infection control efforts during the COVID-19 pandemic. Areas with a history of racial segregation and poverty experienced differential COVID-19 death and morbidity rates. Supplying masks equitably and rapidly became an urgent public health priority. A partnership between a local manufacturer with available polypropylene fabric and the Medical College of Wisconsin, which had the capability to assemble and distribute masks, was formed in April, 2020. An improvised logistics framework allowed for rapid distribution more than 250,000 masks, and later facilitated hand-off to other organizations to distribute over 3 million masks. Using an action research framework three phases of the effort are considered, 1) initial deliveries to community clinics, 2) equitable distribution to community agencies while under “safer at home” orders, and 3) depot deliveries and transfer of logistics management as larger agencies recovered. A multi-actor view was used to interrogate the information needs of faculty and staff remotely directing distribution, medical student volunteers delivering masks, and the manufacturer monitorng overall inventory. Logistics information was managed using Google Sheets augmented with a small SQLite component. A phenomenological view, toggling back and forth from the “socio” to the “technical” provides detailed insight into the strengths and limitations of digital solutions for humanitarian logistics, highlighting where paper-based processes remain more efficient. This case study suggests that rather than building bespoke logistics software, supporting relief efforts with non-traditional responders may benefit from extensible components that augment widely used digital tools.

Abstract: As a result of climate change and global weather patterns, large forest fires are becoming more frequent in different parts of the world. The focus of the presented work is on creation of a complex coordination and communication framework for a swarm of drones specially tailored for use in preventing and monitoring of forest fires. The presented algorithm has been testing and evaluating using a computer simulation. The testing and validation in relevant environment is scheduled during a pilot demonstration exercise with real personnel and equipment, which will take place in Slovakia on April 2023. The presented work is a part of the SILVANUS EU H2020 project, whose objective is the creation of a climate resilient forest management platform for forest fire prevention and suppression. SILVANUS draws on environmental, technical, and social science experts to support regional and national authorities responsible for forest fire management in their respective countries.

Abstract: Ghana's capital, the Greater Accra Metropolitan Area (GAMA) is most vulnerable to flooding due to its high population density. This paper proposes the fusion of satellite imagery, social media, and geospatial data to derive near real-time (NRT) flood maps to understand human activity during a disaster and the extent of infrastructure damage. To that end, the paper presents an automatic thresholding technique for NRT flood mapping using Sentinel-1 images where four different speckle filters are compared using the VV, VH and VV/VH polarization to determine the best polarization(s) for delineating flood extents. The VV and VH bands together on Perona-Malik filtered images achieved the highest accuracy with an F1-score of 81.6%. Moreover, all tweet text and images were found to be located in flooded regions or in very close proximity to a flooded region, thus allowing crisis responders to better understand vulnerable communities and what humanitarian action is required.

Abstract: The use of ecosystems for EcoDRR is a beneficial and a viable option for community stakeholders. For example, ecosystems can mitigate the effects of hazards experienced in anthropogenic communities. Ecosystem services are the underlying reason for this benefit. EcoDRR is the idea of sustainable management, conservation, and restoration of ecosystems to maximize ecosystem services and reduce disaster risks and impacts. The use of geospatial technologies to monitor large-scale ecosystems are often subject to Geographic Information Capacity (GIC), or the ability of ecosystem stakeholders to utilize all existing geographic information, resources, and capacities to monitor ecosystem services. Though these tools are useful, currently there is not a tool that specifically quantifies ecosystem services in the context of DRR. The main contribution of this paper is a conceptual framework intended to quantify ecosystem services in the context of EcoDRR.