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	Author	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Title	17th ISCRAM Conference Proceedings			Type	Conference Volume
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings � 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1-1193
	Keywords
	Abstract	The 17th annual conference on Information Systems for Crisis Response and Management (ISCRAM 2020) was scheduled to be held in Blacksburg, Virginia from May 24th-27th, 2020. Unfortunately, due to the widespread impacts of the COVID-19 pandemic, the conference organizers and the ISCRAM Board decided to postpone the conference until May 2021. Even though we could not hold the conference as originally planned, all papers accepted for presentation at ISCRAM 2020 are published in the conference proceedings presented here, and the authors of these papers will have the opportunity to present their papers at the 2021 conference. The 2021 conference will once again be hosted at Virginia Tech in Blacksburg, Virginia, and it will take place during the week of May 23rd, 2021. The theme of ISCRAM 2020 is �Bringing Disaster Resilience into Focus.� These proceedings seek to highlight resilience in Crisis and Emergency Management and to stimulate discussions that enable the design of crisis and emergency management systems that contribute to more resilient organizations and communities. We are pleased to present the accepted papers for ISCRAM 2020, which consist of excellent contributions on a wide range of topics.
	Address
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-92	ISBN	2411-3478	Medium
	Track	Proceedings	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes				Approved	yes
	Call Number				Serial	2307
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	Author	Ben Ortiz; Laura Kahn; Marc Bosch; Philip Bogden; Viveca Pavon-Harr; Onur Savas; Ian McCulloh
	Title	Improving Community Resiliency and Emergency Response With Artificial Intelligence			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	35-41
	Keywords	Emergency Management, Semantic Segmentation, Inland Flood Modeling, Route Optimization.
	Abstract	New crisis response and management approaches that incorporate the latest information technologies are essential in all phases of emergency preparedness and response, including the planning, response, recovery, and assessment phases. Accurate and timely information is as crucial as is rapid and coherent coordination among the responding organizations. We are working towards a multi-pronged emergency response tool that provide stakeholders timely access to comprehensive, relevant, and reliable information. The faster emergency personnel are able to analyze, disseminate and act on key information, the more effective and timelier their response will be and the greater the benefit to affected populations. Our tool consists of encoding multiple layers of open source geospatial data including flood risk location, road network strength, inundation maps that proxy inland flooding and computer vision semantic segmentation for estimating flooded areas and damaged infrastructure. These data layers are combined and used as input data for machine learning algorithms such as finding the best evacuation routes before, during and after an emergency or providing a list of available lodging for first responders in an impacted area for first. Even though our system could be used in a number of use cases where people are forced from one location to another, we demonstrate the feasibility of our system for the use case of Hurricane Florence in Lumberton, a town of 21,000 inhabitants that is 79 miles northwest of Wilmington, North Carolina.
	Address	Accenture Federal Services; Accenture Federal Services; Accenture Federal Services; Accenture Federal Services; Accenture Federal Services; Accenture Federal Services
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-4	ISBN	2411-3390	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Laura.kahn@accenturefederal.com			Approved	no
	Call Number				Serial	2205
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	Author	Stefan Schauer; Stefan Rass; Sandra König; Klaus Steinnocher; Thomas Schaberreiter; Gerald Quirchmayr
	Title	Cross-Domain Risk Analysis to Strengthen City Resilience: the ODYSSEUS Approach			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	652-662
	Keywords	Risk Management; Cross-Domain Networks; Interdependencies; Stochastic Model; City Resilience; Critical Infrastructures
	Abstract	In this article, we want to present the concept for a risk management approach to assess the condition of critical infrastructure networks within metropolitan areas, their interdependencies among each other and the potential cascading effects. In contrast to existing solutions, this concept aims at providing a holistic view on the variety of interconnected networks within a city and the complex dependencies among them. Therefore, stochastic models and simulations are integrated into risk management to improve the assessment of cascading effects and support decision makers in crisis situations. This holistic view will allow risk managers at the city administration as well as emergency organizations to understand the full consequences of an incident and plan mitigation actions accordingly. Additionally, the approach will help to further strengthen the resilience of the entire city as well as the individual critical infrastructures in crisis situations.
	Address	AIT Austrian Institute of Technology; Alpen-Adria Universit\"at Klagenfurt; AIT Austrian Institute of Technology;AIT Austrian Institute of Technology;University of Vienna; University of Vienna
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-60	ISBN	2411-3446	Medium
	Track	Resilience in Critical Infrastructures	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	stefan.schauer@ait.ac.at			Approved	no
	Call Number				Serial	2261
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	Author	Henry Agsten
	Title	Effects of Smartphone-Based Alerting on Reducing Arrival Times for Volunteer Fire Departments			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	990-994
	Keywords	Volunteer Fire Departments; Time Reduction; Inefficiencies; Smartphone Application
	Abstract	This practitioner paper describes the efforts of a volunteer fire department in Germany to reduce the time to arrive at a place of emergency. It presents the former situation, identifies reasons for delays and highlights the volunteers' first years in utilizing an existing smartphone application for alert and response as a mean to optimize their times of arrival. The paper finally evaluates the effects of the application's usage.
	Address	Alarm Dispatcher Systems GmbH,Dresden, Germany
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-89	ISBN	2411-3475	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	ha@alarm-dispatcher.de			Approved	no
	Call Number				Serial	2290
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	Author	Matti Wiegmann; Jens Kersten; Friederike Klan; Martin Potthast; Benno Stein
	Title	Analysis of Detection Models for Disaster-Related Tweets			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	872-880
	Keywords	Tweet Filtering; Crisis Management; Evaluation Framework
	Abstract	Social media is perceived as a rich resource for disaster management and relief efforts, but the high class imbalance between disaster-related and non-disaster-related messages challenges a reliable detection. We analyze and compare the effectiveness of three state-of-the-art machine learning models for detecting disaster-related tweets. In this regard we introduce the Disaster Tweet Corpus~2020, an extended compilation of existing resources, which comprises a total of 123,166 tweets from 46~disasters covering 9~disaster types. Our findings from a large experiments series include: detection models work equally well over a broad range of disaster types when being trained for the respective type, a domain transfer across disaster types leads to unacceptable performance drops, or, similarly, type-agnostic classification models behave more robust at a lower effectiveness level. Altogether, the average misclassification rate of~3,8\% on performance-optimized detection models indicates effective classification knowledge but comes at the price of insufficient generalizability.
	Address	Bauhaus-Universit\“at Weimar German Aerospace Center (DLR); German Aerospace Center (DLR); German Aerospace Center (DLR); Leipzig University; Bauhaus-Universit\”at Weimar
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-77	ISBN	2411-3463	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	matti.wiegmann@uni-weimar.de			Approved	no
	Call Number				Serial	2278
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	Author	Yannic Schulte; Miriam Klein; Marcus Wiens; Frank Fiedrich
	Title	Spontaneous Volunteers Across National Borders: An Agent-Based Comparison			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	327-336
	Keywords	Spontaneous Volunteers, Cross-Border, Borderland, Agent-Based Modelling, Disaster Management.
	Abstract	In today's globalized world and with the extensive use of social media, there is a high connectivity of people across countries, which can be a helpful potential in disaster response. In a coordinated manner, spontaneous volunteers from neighbouring nations can provide high manpower and resources to a disaster affected area. In this article, we discuss why the consideration of spontaneous volunteers is relevant in a cross-border context in order to improve disaster resilience for borderlands. Furthermore, we introduce a baseline agent-based model to simulate cooperation procedures for the involvement of spontaneous volunteers to the official crisis response in a borderland and discuss important issues that need to be addressed in future considerations.
	Address	Bergische Universität Wuppertal; Karlsruhe Institute of Technology; Karlsruhe Institute of Technology; Bergische Universität Wuppertal
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-32	ISBN	2411-3418	Medium
	Track	Cross-Border Resilience	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	yschulte@uni-wuppertal.de			Approved	no
	Call Number				Serial	2233
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	Author	Jean-Paul Monet; Pierre Schaller; Sergio Pirone; Marc Castellnou Ribau; Stéphane Poyau; Marc Dumas
	Title	Civil Protection in Europe: Towards a Unified Command System? Lessons Learned, Studies and Ideas About Change Management			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	315-325
	Keywords	Crisis Management, Incident, Command and Control System, Interoperability, European Union.
	Abstract	After the summer 2017 deadly wildfires in Portugal, President Juncker of the European Commission asked for “a stronger European Union (EU)”, clearly targeting civil protection management. This wish found achievement in the March 2019 guidance to establish a reserve of EU response capacities called “rescEU”, integrated into the jurisdictional basis of EU civil protection. However, the authors regret the ambition of this plan has not been fulfilled. Due to some very “European constraints” this “new deal” has introduced only small changes in terms of resources and knowledge management. In each of the past several years, climate change has brought new examples of fatal natural disasters: wildfires in Sweden, and Greece, and flash floods in Spain and France. Because of this continuous rise in disasters, and based on some lessons learned, the authors stress that it's now time to shape a project to improve European Civil Protection. The idea is to move from the already good modular system of the EU Civil Protection Mechanism to an integrated, robust, and unique European Command System, which clearly must be fully interoperable with other existing mechanisms (US ICS, UNOCHA...).
	Address	Bouches-du-Rhône Fire department; National French Fire Academy (Ensosp); Corpo forestal Piemonte, Italy; Pau Costa foundation, Spain; Landes Fire department; Bouches-du-Rhône Fire department
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-31	ISBN	2411-3417	Medium
	Track	Command & Control Studies	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	jpmonet@sdis13.fr			Approved	no
	Call Number				Serial	2232
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	Author	Kristine Steen-Tveit; Jaziar Radianti; Bjørn Erik Munkvold
	Title	SMS-based real-time data collection for evaluation of situational awareness and common operational picture: lessons learned from a field exercise			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	276-284
	Keywords	Real-time Data Collection, Emergency Exercises, Situational Awareness, Common Operational Picture.
	Abstract	Managing complex multi-agency emergency operations requires that the key actors have a holistic, correct and dynamic situational awareness (SA) and that the involved actors establish a common operational picture (COP). Establishing SA and COP are key objectives in many multi-agency exercises, however, reported research shows limitations in existing methods and approaches for collecting the data required for evaluating this. By being able to capture near real-time information during different phases of the exercise we will be better positioned to identify what works well and what does not work in the process of establishing SA and COP. Our paper presents an example of real-time data collection using SMS during a multi-agency field exercise. Overall, the results support the idea of this as an effective method for collecting real-time data for analyzing the formation of SA and a COP among actors in emergency management.
	Address	Centre for Integrated Emergency Management (CIEM), University of Agder, Norway; University of Agder, Norway; University of Agder, Norway
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-27	ISBN	2411-3413	Medium
	Track	Command & Control Studies	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	kristine.steen-tveit@uia.no			Approved	no
	Call Number				Serial	2228
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	Author	Kristine Steen-Tveit
	Title	Identifying Information Requirements for Improving the Common Operational Picture in Multi-Agency Operations			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	252-263
	Keywords	Situational Awareness, Common Operational Picture, Information Sharing, Common Information Requirements, Multi-Agency Emergency Operations.
	Abstract	While there exists a considerable body of literature on the importance of a common operational picture (COP) in multi-agency emergency operations, the COP concept itself still lacks a univocal definition. Despite the lack of consensus regarding the mechanisms underlying the COP, the literature implies a level of consistency in the focus on sharing critical information. Based on interviews with Norwegian emergency management stakeholders, this study investigates common information requirements for emergency management services and presents an example of a framework for structuring the sharing of critical information and building a COP. Termed 'the window report', this framework is used among emergency stakeholders in Norway and Sweden. The study identified eight common information requirement categories for managing extreme weather scenarios. With a focus on common information needs and a process for structured information sharing, future strategic emergency management planning might take a more holistic perspective on cross-sectoral operations than in current practice.
	Address	Centre for Integrated Emergency Management, University of Agder
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-25	ISBN	2411-3411	Medium
	Track	Command & Control Studies	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	kristine.steen-tveit@uia.no			Approved	no
	Call Number				Serial	2226
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	Author	Anastasia Moumtzidou; Marios Bakratsas; Stelios Andreadis; Anastasios Karakostas; Ilias Gialampoukidis; Stefanos Vrochidis; Ioannis Kompatsiaris
	Title	Flood detection with Sentinel-2 satellite images in crisis management systems			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1049-1059
	Keywords	Floods, Change Detection, Bi-temporal Analysis, Sentinel-2, Deep Neural Networks.
	Abstract	The increasing amount of falling rain may cause several problems especially in urban areas, which drainage system can often not handle this large amount in a short time. Confirming a flooded scene in a timely manner can help the authorities to take further actions to counter the crisis event or to get prepared for future relevant incidents. This paper studies the detection of flood events comparing two successive in time Sentinel-2 images, a method that can be extended for detecting floods in a time-series. For the flood detection, fine-tuned pre-trained Deep Convolutional Neural Networks are used, testing as input different sets of three water sensitive satellite bands. The proposed approach is evaluated against different change detection baseline methods, based on remote sensing. Experiments showed that the proposed method with the augmentation technique applied, improved significantly the performance of the neural network, resulting to an F-Score of 62% compared to 22% of the traditional remote sensing techniques. The proposed method supports the crisis management authority to better estimate and evaluate the flood impact.
	Address	Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece;
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-95	ISBN	2411-3481	Medium
	Track	Using Artificial Intelligence to exploit Satellite Data in Risk and Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	moumtzid@iti.gr			Approved	no
	Call Number				Serial	2296
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	Author	Lise Ann St. Denis; Amanda Lee Hughes; Jeremy Diaz; Kylen Solvik; Maxwell B. Joseph; Jennifer K. Balch
	Title	'What I Need to Know is What I Don't Know!': Filtering Disaster Twitter Data for Information from Local Individuals			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	730-743
	Keywords	Crisis Informatics, Social Media, Emergency Management, Situational Awareness.
	Abstract	We report on the design, development, and evaluation of a user labeling framework for social media monitoring by emergency responders. By labeling Twitter user accounts based on behavior and content, this novel approach identifies tweets from accounts belonging to Individuals generating Personalized content and captures information that might otherwise be missed. We evaluate the framework using training data from the 2018 Camp, Woolsey, and Hill fires. Approximately 30% of the Individual-Personalized tweets contain first-hand information, providing a rich stream of content for social media monitoring. Because it can quickly eliminate most redundant tweets, this framework could be a critical first step in an end-to-end information extraction pipeline. It may also generalize more easily for new disaster events since it relies on general user account attributes rather than tweet content. We conclude with next steps for refining and evaluating our framework in near real-time during a disaster response.
	Address	CIRES, Earth Lab, University of Colorado, Boulder; Crisis Informatics Lab Brigham Young University; Institute for Computational and Data Sciences, Department of Geography, Penn State University; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder; CIRES, Earth Lab, University of Colorado, Boulder; CIRES, Earth Lab, Department of Geography, University of Colorado, Boulder
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-66	ISBN	2411-3452	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Lise.St.Denis@Colorado.edu			Approved	no
	Call Number				Serial	2267
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	Author	Josep Cobarsí; Laura Calvet
	Title	Community resilience instruments: Chances of improvement through customization and integration?			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	381-388
	Keywords	Community Resilience, Measurement Instruments, Disaster Risk Reduction, Stakeholders, Data.
	Abstract	Resilience is understood as the ability of a system, community or society exposed to hazards to resist, absorb, accommodate, adapt to, transform and recover from the effects of a hazard in a timely and efficient manner. So far, dozens of measurement instruments have been developed to measure community resilience to disasters, considering each one different types of hazards (general, natural, climate, man-made, etc.) and communities (general, urban, rural, etc.). However, none of these instruments has been widely adopted yet. In this context, we discuss important gaps for resilience research and practice. Then, we propose a conceptual framework to review community resilience instruments, so to enhance their improvement through two facets (or dimensions) we propose of customization and integration. This framework is characterized by the following properties for community resilience instruments: encapsulation, intelligibility, geographical focus, hazard range focus, connectivity, adaptability to dynamic conditions, datification, and stakeholders' involvement. We look forward to apply this framework to review a purposive sample of community resilience instruments regarding natural disasters.
	Address	Computer Science, Multimedia and Telecommunication Studies. Universitat Oberta de Catalunya. Barcelona (Spain); Computer Science, Multimedia and Telecommunication Studies. Universitat Oberta de Catalunya. Barcelona (Spain)
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-36	ISBN	2411-3422	Medium
	Track	Data and Resilience: Opportunities and Challenges	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	jcobarsi@uoc.edu			Approved	no
	Call Number				Serial	2237
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	Author	Artur Ricardo Bizon; Luciana P. de Araújo Kohler; Adilson Luiz Nicoletti; Fernanda Dal Bosco; Murilo Schramm da Silva; Thales Bohn Pessatti
	Title	Integration statistical systems for land cover mapping in Southern Brazil			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	498-505
	Keywords	Random Forest, Logistic Regression, Classifier, Google Earth Engine, Remote Sensing.
	Abstract	The remote sensing is a way to optimize the process of land cover classification allowing that this process will be by high definition images of satellite. For the research it was used the Google Earth Engine with JavaScript programming language to classify the images, identifying the areas with forest or reforest. It was identified that classifiers Random Forest and Logistic Regression have a high performance in classify the images. From them it was developed functions to process automatically of new images with purpose of classify them in relation to land cover.
	Address	Departamento de Engenharia Florestal -- Universidade Regional de Blumenau; Departamento de Engenharia Florestal -- Universidade Regional de Blumenau; Departamento de Engenharia Florestal -- Universidade Regional de Blumenau;Departamento de Engenharia Florestal -- Universidade Regional de Blumenau; Departamento de Engenharia Florestal -- Universidade Regional de Blumenau; Departamento de Engenharia Florestal -- Universidade Regional de Blumenau
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-47	ISBN	2411-3433	Medium
	Track	Geospatial Technologies and Geographic Information Science for Crisis Management (GIS)	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	abizon@furb.br			Approved	no
	Call Number				Serial	2248
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	Author	Kamol Roy; MD Ashraf Ahmed; Samiul Hasan; Arif Mohaimin Sadri, P.D.
	Title	Dynamics of Crisis Communications in Social Media: Spatio-temporal and Text-based Comparative Analyses of Twitter Data from Hurricanes Irma and Michael			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	812-824
	Keywords	Social Media, Dynamic Topic Modeling, Irma, Michael, Disaster Management.
	Abstract	Social media platforms play critical roles in information dissemination, communication and co-ordination during different phases of natural disasters as it is crucial to know the type of crisis information being disseminated and user concerns. Large-scale Twitter data from hurricanes Irma (Sept. 2017) and Michael (Oct. 2018) are used here to understand the topic dynamics over time by applying the Dynamic Topic Model, followed by a comparative analyses of the differences in such dynamics for these two hurricane scenarios. We performed a spatio-temporal analyses of user activities with reference to the hurricane center location and wind speed. The findings of spatio-temporal analyses show that differences in hurricane path and the affected regions influence user participation and social media activity. Besides, topic dynamics reveals that situational awareness, disruptions, relief action are among the patterns common for both hurricanes; unlike topics such as hurricane evacuation and political situation that are scenario dependent.
	Address	Department of CECE University of Central Florida; Department of CECE University of Central Florida; Department of CECE University of Central Florida; Department of MDCM Florida International University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-72	ISBN	2411-3458	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	roy.kamol@knights.ucf.edu			Approved	no
	Call Number				Serial	2273
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	Author	Erik Prytz; Anna-Maria Grönbäck; Krisjanis Steins; Craig Goolsby; Tobias Andersson Granberg; Carl-Oscar Jonson
	Title	Evaluating the Effect of Bleeding Control Kit Locations for a Mass Casualty Incident Using Discrete Event Simulation			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	167-178
	Keywords	Simulation, Mass Casualty Incident, Tourniquet, Stop the Bleed, Bleeding Control Kit Placement.
	Abstract	The purpose of this study was to develop a simulation model to evaluate bleeding control kit location strategies for a mass casualty incident scenario. Specifically, the event simulated was an explosion at a large sports arena. The model included a representation of the arena itself, simulated crowd movements following the detonation of an improvised explosive device, injuries and treatments, and different ways for immediate responders to help injured patients using tourniquets. The simulation model gave logically consistent results in the validation scenarios and the simulation outcomes were in line with the expected outcomes. The results of the different tourniquet location scenarios indicated that decentralized placement (more than one location) is better, easy access is important (between rather than at emergency exits) and that an increased number of available tourniquets will result in an increased number of survivors.
	Address	Department of Computer and Information Science, Linköping University; Linköping University; Department of Science and Technology, Linköping University; Uniformed Services University of the Health Sciences; Department of Science and Technology, Linköping University; Center for Disaster Medicine and Traumatology, and Department of Biomedical and Clinical Sciences, Linköping University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-16	ISBN	2411-3402	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Erik.prytz@liu.se			Approved	no
	Call Number				Serial	2217
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	Author	Henrique Romano Correia; Ivison da Costa Rubim; Angelica F.S. Dias; Juliana B.S. França; Marcos R.S. Borges
	Title	Drones to the Rescue: A Support Solution for Emergency Response			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	904-913
	Keywords	Emergency, Information System, Collaborative Systems, Decision-making Drones.
	Abstract	Emergency is a threatening condition that requires urgent action, an effective response and within an emergency scenario there may be risks for responders, as well as for those affected. Response time is crucial for affected individuals and environments to be addressed on their needs. In this context, the goal of this work is to support the agents involved in the emergency response, through an application-supported collaborative solution using drones. This solution aims to collect information from the worked emergency scenario, so that, through the collaboration of specialists, there is a greater support for the decision-making made by the responsible agents within this scenario, causing it to occur in a shorter time, thus speeding up the response to the emergency. In this work, the aim was to validate with experts from the Rio de Janeiro Firefighters, who already work with drones, by evaluating the utility of the solution in real scenarios.
	Address	Department of Computer Science – Universidade Federal do Rio de Janeiro, Brazil; Post-graduation Program in Informatics (PPGI) – Universidade Federal do Rio de Janeiro, Brazil; Post-graduation Program in Informatics (PPGI) – Universidade Federal do Rio de Janeiro, Brazil; Department of Computer Science – Federal Rural University of Rio de Janeiro, Brazil; Post-graduation Program in Informatics (PPGI) – Universidade Federal do Rio de Janeiro, Brazil, TECNUN, University of Navarra, Donostia, San Sebastián, Spain
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-80	ISBN	2411-3466	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	henriquercorreia@gmail.com			Approved	no
	Call Number				Serial	2281
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	Author	Xukun Li; Doina Caragea
	Title	Improving Disaster-related Tweet Classification with a Multimodal Approach			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	893-902
	Keywords	Multimodal Model; Tweet Classification; Deep Learning
	Abstract	Social media data analysis is important for disaster management. Lots of prior studies have focused on classifying a tweet based on its text or based on its images, independently, even if the tweet contains both text and images. Under the assumptions that text and images may contain complementary information, it is of interest to construct classifiers that make use of both modalities of the tweet. Towards this goal, we propose a multimodal classification model which aggregates text and image information. Our study aims to provide insights into the benefits obtained by combining text and images, and to understand what type of modality is more informative with respect to disaster tweet classification. Experimental results show that both text and image classification can be improved by the multimodal approach.
	Address	Department of Computer Science, Kansas State University; Department of Computer Science, Kansas State University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-79	ISBN	2411-3465	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	xukun@ksu.edu			Approved	no
	Call Number				Serial	2280
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	Author	Liuqing Li; Edward A. Fox
	Title	Disaster Response Patterns across Different User Groups on Twitter: A Case Study during Hurricane Dorian			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	838-848
	Keywords	Hurricane, Response, Pattern, User Classification, Twitter
	Abstract	We conducted a case study analysis of disaster response patterns across different user groups during Hurricane Dorian in 2019. We built a tweet collection about the hurricane, covering a two week period. We divided Twitter users into two groups: brand/organization or individual. We found a significant difference in response patterns between the groups. Brand users increasingly participated as the disaster unfolded, and they posted more tweets than individual users on average. Regarding emotions, brand users posted more tweets with joy and surprise, while individual users posted more tweets with sadness. Fear was a common emotion between the two groups. Further, both groups used different types of hashtags and words in their tweets. Some distinct patterns were also discovered in their concerns on specific topics. These results suggest the value of further exploration with more tweet collections, considering the behavior of different user groups during disasters.
	Address	Department of Computer Science, Virginia Tech; Department of Computer Science, Virginia Tech;
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-74	ISBN	2411-3460	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	liuqing@vt.edu			Approved	no
	Call Number				Serial	2275
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	Author	Cheng Wang; Benjamin Bowes; Arash Tavakoli; Stephen Adams; Jonathan Goodall; Peter Beling
	Title	Smart Stormwater Control Systems: A Reinforcement Learning Approach			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	2-13
	Keywords	Reinforcement Learning, Stormwater, Flooding Control.
	Abstract	Flooding poses a significant and growing risk for many urban areas. Stormwater systems are typically used to control flooding, but are traditionally passive (i.e. have no controllable components). However, if stormwater systems are retrofitted with valves and pumps, policies for controlling them in real-time could be implemented to enhance system performance over a wider range of conditions than originally designed for. In this paper, we propose an autonomous, reinforcement learning (RL) based, stormwater control system that aims to minimize flooding during storms. With this approach, an optimal control policy can be learned by letting an RL agent interact with the system in response to received reward signals. In comparison with a set of static control rules, RL shows superior performance on a wide range of artificial storm events. This demonstrates RL's ability to learn control actions based on observation and interaction, a key benefit for dynamic and ever-changing urban areas.
	Address	Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-1	ISBN	2411-3387	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	cw8xk@virginia.edu			Approved	no
	Call Number				Serial	2202
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	Author	Samer Chehade; Nada Matta; Jean-Baptiste Pothin; Remi Cogranne
	Title	Ontology-Based Approach for Designing User Interfaces: Application for Rescue Actors			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	54-65
	Keywords	Interactions, Modelling, Ontologies, Rescue Operations, User Interface Design.
	Abstract	Nowadays, rescue actors still lack backing to exchange information effectively and ensure a common operational picture. Several studies report a low adoption of communication systems in rescue operations as well as a negative position of actors to such systems. The real needs of stakeholders, simply put, are not satisfied by the offered systems. Observing this circumstance through a user-centred design focal point, we notice that such issues ordinarily originate from inadequate design techniques. For this reason, we aim to implement Rescue MODES, a communication system oriented to support awareness amongst French actors in rescue operations based on their needs. In this paper, we propose an approach and introduce a platform that allows final users to design system interfaces in a customised way. This approach is based on an application ontology and an interaction model.
	Address	Department of Research and Development, DataHertz, Troyes, France; Institut Charles Delaunay, TechCICO, Université de Technologie de Troyes, Troyes, France; Department of Research and Development, DataHertz, Troyes, France; Institut Charles Delaunay, M2S, Université de Technologie de Troyes, Troyes, France
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-6	ISBN	2411-3392	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Samer.chehade@datahertz.fr			Approved	no
	Call Number				Serial	2207
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	Author	Lixiong Chen; Monika Buscher; Yang Hu
	Title	Crowding Out the Crowd:The Transformation of Network Disaster Communication Patterns on Weibo			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	472-489
	Keywords	Weibo, Transformation, Crowding Out, Crisis Communication, Mobilities.
	Abstract	There is a surge in people turning to social media in disasters in China. In the 2010 Yushu earthquake, 5,979 Weibos were posted. Almost 10 years on, in the 2019 Yibin earthquake it was 17,495. This study presents a Social Network Analysis of the dynamics of this growth, taking the six major Chinese earthquakes of this decade as a case study. By constructing relationship matrices, the research reveals a transformation of networked crisis communication patterns on Weibo. We show how communication relationships between verified organisational users, government agencies, verified individual users (such as celebrities) and unverified ordinary users have changed, and we observe that government agencies are 'crowding out the crowd' of other users. We consider key aspects and the ethical complexities of this phenomenon.
	Address	Department of Sociology Lancaster University; Department of Sociology Lancaster University; Department of Sociology Lancaster University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-45	ISBN	2411-3431	Medium
	Track	Ethical, Legal, and Social Issues	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	c.lixiong@lancaster.ac.uk			Approved	no
	Call Number				Serial	2246
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	Author	Mehdi Ben Lazreg; Usman Anjum; Vladimir Zadorozhny; Morten Goodwin
	Title	Semantic Decay Filter for Event Detection			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	14-26
	Keywords	String Metric, Event Detection, Crisis Management.
	Abstract	Peaks in a time series of social media posts can be used to identify events. Using peaks in the number of posts and keyword bursts has become the go-to method for event detection from social media. However, those methods suffer from the random peaks in posts attributed to the regular daily use of social media. This paper proposes a novel approach to remedy that problem by introducing a semantic decay filter (SDF). The filter's role is to eliminate the random peaks and preserve the peak related to an event. The filter combines two relevant features, namely the number of posts and the decay in the number of similar tweets in an event-related peak. We tested the filter on three different data sets corresponding to three events: the STEM school shooting, London bridge attacks, and Virginia beach attacks. We show that, for all the events, the filter can eliminate random peaks and preserve the event-related peaks.
	Address	Dept. of Information and Communication Technology, University of Agder,Grimstad, Norway; Dept. of Informatics and Networked Systems, University of Pittsburgh, Pittsburgh, USA; Dept. of Informatics and Networked Systems, University of Pittsburgh, Pittsburgh, USA; Dept. of Information and Communication Technology, University of Agder,Grimstad, Norway
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-2	ISBN	2411-3388	Medium
	Track	AI Systems for Crisis and Risks	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	mehdi.ben.lazreg@uia.no			Approved	no
	Call Number				Serial	2203
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	Author	Valerio Lorini; Javier Rando; Diego Saez-Trumper; Carlos Castillo
	Title	Uneven Coverage of Natural Disasters in Wikipedia: The Case of Floods			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	688-703
	Keywords	Social Media, News Values, Wikipedia, Natural Disasters, Floods.
	Abstract	The usage of non-authoritative data for disaster management provides timely information that might not be available through other means. Wikipedia, a collaboratively-produced encyclopedia, includes in-depth information about many natural disasters, and its editors are particularly good at adding information in real-time as a crisis unfolds. In this study, we focus on the most comprehensive version of Wikipedia, the English one. Wikipedia offers good coverage of disasters, particularly those having a large number of fatalities. However, by performing automatic content analysis at a global scale, we also show how the coverage of floods in Wikipedia is skewed towards rich, English-speaking countries, in particular the US and Canada. We also note how coverage of floods in countries with the lowest income is substantially lower than the coverage of floods in middle-income countries. These results have implications for analysts and systems using Wikipedia as an information source about disasters.
	Address	European Commission, Joint Research Centre (JRC), Ispra, Italy Universitat Pompeu Fabra, Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain; Wikimedia Foundation; Universitat Pompeu Fabra, Barcelona, Spain
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-63	ISBN	2411-3449	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	valerio.lorini@ec.europa.eu			Approved	no
	Call Number				Serial	2264
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	Author	Flavio Dusse; Renato Novais; Manoel Mendonça
	Title	A Visual Analytics Based Model for Crisis Management Decision-Making			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	157-166
	Keywords	Crisis Management, Decision-Making, Visual Analytics, Model.
	Abstract	Crisis Management (CM) refers to the ability to deal with crisis tasks in different phases and iterations. People working in a crisis are generally under pressure to make the right decision at the right time. They must process large amounts of data and assimilate the received information in an intuitive way. Visual Analytics (VA) is potentially useful to analyze and understand the huge amount of data in several areas including in a crisis. We propose a model based on VA to support decision-making in CM. The aim of the model is to help visualization designers to create effective VA interfaces, to help crisis managers to make quick and assertive decisions with them. In previous studies, we carried out a survey protocol with a multi-method approach to collect data on crisis related decision-making and analyze all these data qualitatively with formal techniques during the large events held in Brazil in recent years. In this work, we used our previous findings to develop the proposed model. We validated it using the focus group technique. With the new findings, we identified relevant insights on the use of VA for crisis management. We hope that, with these continuous cycles of validation and improvement, the agencies that manage crises might use our model as a reference for building more effective IT decision-making infrastructures based on VA.
	Address	Federal University of Bahia; Federal Institute of Bahia; Federal University of Bahia
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-15	ISBN	2411-3401	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	dussebr@dcc.ufba.br			Approved	no
	Call Number				Serial	2216
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	Author	Milad Baghersad; Christopher W. Zobel; Ravi Behara
	Title	Evaluation of Local Government Performance after Disasters			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	210-217
	Keywords	311 Services, Disaster, Municipal Departments, Resilience.
	Abstract	Monitoring and evaluation can help organizations involved in disasters learn from their responses to prior events and improve their performance over time. Using a data set of non-emergency service requests in New York City (NYC), this paper provides a method to evaluate and compare the performance of local governments in terms of service request response times after different disaster events. In particular, the proposed method can be used to compare such performance across divisions or boroughs in a city. To illustrate this, we evaluate the performance in five of NYC's boroughs: the Bronx, Brooklyn, Manhattan, Queens, and Staten Island, across seven major natural disaster events from 2010 to 2012. Our analyses show that Queens and Brooklyn demonstrate better performance than the other boroughs in almost all of the seven events under consideration.
	Address	Florida Atlantic University; Virginia Tech; Florida Atlantic University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-20	ISBN	2411-3406	Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	mbaghersad@fau.edu			Approved	no
	Call Number				Serial	2221
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