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	Author	Haiyan Hao; Yan Wang
	Title	Hurricane Damage Assessment with Multi-, Crowd-Sourced Image Data: A Case Study of Hurricane Irma in the City of Miami			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	825-837
	Keywords	Computer Vision, Damage Assessment, Disaster Management, Insurance Claims, Social Networking Platforms.
	Abstract	The massive crowdsourced data generated on social networking platforms (e.g. Twitter and Flickr) provide free, real-time data for damage assessment (DA) even during catastrophes. Recent studies leveraging crowdsourced data for DA mainly focused on analyzing textual formats. Crowdsourced images can provide rich and objective information about damage conditions, however, are rarely researched for DA purposes. The highly-varied content and loosely-defined damage forms make it difficult to process and analyze the crowdsourced images. To address this problem, we propose a data-driven DA method based on multi-, crowd-sourced images, which includes five machine learning classifiers organized in a hierarchical structure. The method is validated with a case study investigating the damage condition of the City of Miami caused by Hurricane Irma. The outcome is then compared with a metric derived from NFIP insurance claims data. The proposed method offers a resource for rapid DA that supplements conventional DA methods.
	Address	University of Florida; University of Florida
	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	978-1-949373-27-73	ISBN	2411-3459	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	hhao@ufl.edu			Approved	no
	Call Number				Serial	2274
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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	Rob Grace
	Title	Hyperlocal Toponym Usage in Storm-Related Social Media			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	849-859
	Keywords	Volunteered Geographic Information, Twitter, Information Behavior, Crisis Informatics, Emergency Management.
	Abstract	Crisis responders need to locate events reported in social media messages that typically lack geographic metadata such as geotags. Toponyms, places names referenced in messages, provide another source of geographic information, however, the availability and granularity of toponyms in crisis social media remain poorly understood. This study examines toponym usage and granularity across six categories of crisis-related information posted on Twitter during a severe storm. Findings show users often include geographic information in messages describing local and remote storm events but do so rarely when discussing other topics, more often use toponyms than geotags when describing local events, and tend to include fine-grained toponyms in reports of infrastructure damage and service disruption and course-grained toponyms in other kinds of storm-related messages. These findings present requirements for hyperlocal geoparsing techniques and suggest that social media monitoring presents more immediate affordances for course-grained damage assessment than fine-grained situational awareness during a crisis.
	Address	Texas Tech 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	978-1-949373-27-75	ISBN	2411-3461	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	rob.grace@ttu.edu			Approved	no
	Call Number				Serial	2276
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	Author	Anna Kruspe
	Title	Detecting Novelty in Social Media Messages During Emerging Crisis Events			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	860-871
	Keywords	Social media; Clustering; Novelty; Embeddings
	Abstract	Social media can be a highly valuable source of information during disasters. A crisis' development over time is of particular interest here, as social media messages can convey unfolding events in near-real time. Previous approaches for the automatic detection of information in such messages have focused on a static analysis, not taking temporal changes and already-known information into account. In this paper, we present a novel method for detecting new topics in incoming Twitter messages (tweets) conditional upon previously found related tweets. We do this by first extracting latent representations of each tweet using pre-trained sentence embedding models. Then, Infinite Mixture modeling is used to dynamically cluster these embeddings anew with each incoming tweet. Once a cluster reaches a minimum number of members, it is considered to be a new topic. We validate our approach on the TREC Incident Streams 2019A data set.
	Address	German Aerospace Center (DLR), Jena, 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	978-1-949373-27-76	ISBN	2411-3462	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	anna.kruspe@dlr.de			Approved	no
	Call Number				Serial	2277
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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	Nasik Muhammad Nafi; Avishek Bose; Sarthak Khanal; Doina Caragea; William H. Hsu
	Title	Abstractive Text Summarization of Disaster-Related Documents			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	881-892
	Keywords	Disaster Reporting; Text Summarization; Information Extraction; Reinforcement Learning; Evaluation Metrics
	Abstract	Abstractive summarization is intended to capture key information from the full text of documents. In the application domain of disaster and crisis event reporting, key information includes disaster effects, cause, and severity. While some researches regarding information extraction in the disaster domain have focused on keyphrase extraction from short disaster-related texts like tweets, there is hardly any work that attempts abstractive summarization of long disaster-related documents. Following the recent success of Reinforcement Learning (RL) in other domains, we leverage an RL-based state-of-the-art approach in abstractive summarization to summarize disaster-related documents. RL enables an agent to find an optimal policy by maximizing some reward. We design a novel hybrid reward metric for the disaster domain by combining \underline{Vec}tor Similarity and \underline{Lex}icon Matching (\textit{VecLex}) to maximize the relevance of the abstract to the source document while focusing on disaster-related keywords. We evaluate the model on a disaster-related subset of a CNN/Daily Mail dataset consisting of 104,913 documents. The results show that our approach produces more informative summaries and achieves higher \textit{VecLex} scores compared to the baseline.
	Address	Kansas State University; Kansas State University; Kansas State University; Kansas State University; 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	978-1-949373-27-78	ISBN	2411-3464	Medium
	Track	Social Media for Disaster Response and Resilie	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	nnafi@ksu.edu			Approved	no
	Call Number				Serial	2279
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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	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	Edward J. Glantz; Frank E. Ritter; Don Gilbreath; Sarah J. Stager; Alexandra Anton; Rahul Emani
	Title	UAV Use in Disaster 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	914-921
	Keywords	Disaster Response, Emergency Management, Drone, Unmanned Aircraft System (UAS), Unmanned Aerial Vehicle (UAV).
	Abstract	Unmanned aerial vehicles (UAV) provide multiple opportunities to first responders and disaster managers, especially as they continue to improve in affordability as well as capabilities. This paper provides a brief review of how UAV capabilities have been used in disaster management, examples of current use within disaster management, as well as adoption considerations. Example disaster domains include fires, tornadoes, flooding, building and dam collapses, crowd monitoring, search and rescue, and post disaster monitoring of critical infrastructures. This review can increase awareness and issues when considering UAVs by those challenged with the management of crisis and disaster events.
	Address	The Pennsylvania State University; The Pennsylvania State University; The Pennsylvania State University; The Pennsylvania State University; The Pennsylvania State University; The Pennsylvania 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	978-1-949373-27-81	ISBN	2411-3467	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	edward.glantz@psu.edu			Approved	no
	Call Number				Serial	2282
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	Author	Benjamin Barth; Govinda Chaithanya Kabbinahithilu; Alexandros Bartzas; Spyros Pantazis; Tomaso deCola
	Title	A Content Oriented Information Sharing System for Disaster 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	922-927
	Keywords	Information Sharing, Preparation, Response, Content Oriented.
	Abstract	In response to natural and man-made hazards multiple organisations usually are involved in a very complex situation. On the other hand, extreme weather situations due to the climate change create hazards in areas which were considered safe before. In order to improve the capabilities of involved organisations in responding and preparing for disaster events, the availability of an efficient information sharing approach is a key enabler. To this end, we propose a communication system based on a content oriented architecture tailored to disaster management. It includes a catalogue that is offering web services for publishing and subscribing of disaster information and for further collaboration amongst agencies and first responders. Moreover, the considered approach also allows for full content access control and enables a flexible system. The paper shows the current status of the system design. Next steps will include the implementation and evaluation of the approach.
	Address	German Aerospace Center (DLR); German Aerospace Center (DLR); Space Hellas S.A.; Space Hellas S.A.; German Aerospace Center (DLR)
	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	978-1-949373-27-82	ISBN	2411-3468	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Benjamin.Barth@dlr.de			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2283
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	Author	Debora Robles Perez; Manuel Esteve Domingo; Israel Perez Llopis; Federico J. Carvajal Rodrigo
	Title	System and Architecture of an Adapted Situation Awareness Tool for First Responders			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	928-936
	Keywords	Critical Infrastructure Protection; First Responder; Command and Control; Autonomous Vehicles; Resilience
	Abstract	First responders (FRs) in Europe are currently facing large natural and man-made disasters (e.g. wild fire, terrorist attacks, industrial incidents, big floods, gas leaks etc.), that put their own lives and those of thousands of others at risk. Adapted situation awareneSS tools and taIlored training curricula for increaSing capabiliTies and enhANcing the proteCtion of first respondErs (ASSISTANCE) is an ongoing European H2020 project which main objective is to increase FRs Situation Awareness (SA) for helping and protecting different kinds of FRs' organizations that work together in large scale disasters mitigation. ASSISTANCE will enhance the SA of the FRs organisations during their mitigation activities through the integration of new paradigms, tools and technologies (e.g. drones/robots equipped with a range of sensors, robust communications capabilities, etc.) with the main objective of increasing both their protection and their efficiency.
	Address	Universitat Politècnica de València; Universitat Politècnica de València; Universitat Politècnica de València; Universitat Politècnica de València
	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	978-1-949373-27-83	ISBN	2411-3469	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	derobpe@upvnet.upv.es			Approved	no
	Call Number				Serial	2284
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	Author	Konstantinos Konstantoudakis; Georgios Albanis; Emmanouil Christakis; Nikolaos Zioulis; Anastasios Dimou; Dimitrios Zarpalas; Petros Daras
	Title	Single-Handed Gesture UAV Control for First Responders – A Usability and Performance User Study			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	937-951
	Keywords	First Responders; UAV; Gesture Recognition; User Study
	Abstract	Unmanned aerial vehicles (UAVs) have increased in popularity in recent years and are now involved in many activities, professional and otherwise. First responders, those teams and individuals who are the first to respond in crisis situations, have been using UAVs to assist them in locating victims and identifying hazards without endangering human personnel needlessly. However, professional UAV controllers tend to be heavy and cumbersome, requiring both hands to operate. First responders, on the other hand, often need to carry other important equipment and need to keep their hands free during a mission. This work considers enabling first responders to control UAVs with single-handed gestures, freeing their other hand and reducing their encumbrance. Two sets of gesture UAV controls are presented and implemented in a simulated environment, and a two-part user study is conducted: the first part assesses the comfort of each gesture and their intuitive association with basic flight control concepts; and the second evaluates two different modes of gesture control in a population of users including both genders, and first responders as well as members of the general populace. The results, consisting of both objective and subjective measurements, are discussed, hindrances and problems are identified, and directions of future work and research are mapped out.
	Address	Visual Computing Lab (VCL), Information Technologies Institute (ITI), Centre for Research and Technology – Hellas (CERTH), Thessaloniki, Greece; Visual Computing Lab (VCL), Information Technologies Institute (ITI), Centre for Research and Technology – Hellas (CERTH), Thessaloniki, Greece;Visual Computing Lab (VCL), Information Technologies Institute (ITI), Centre for Research and Technology – Hellas (CERTH), Thessaloniki, Greece;Visual Computing Lab (VCL), Information Technologies Institute (ITI), Centre for Research and Technology – Hellas (CERTH), Thessaloniki, Greece;Visual Computing Lab (VCL), Information Technologies Institute (ITI), Centre for Research and Technology – Hellas (CERTH), Thessaloniki, Greece;Visual Computing Lab (VCL), Information Technologies Institute (ITI), Centre for Research and Technology – Hellas (CERTH), Thessaloniki, Greece;Visual Computing Lab (VCL), Information Technologies Institute (ITI), Centre for Research and Technology – Hellas (CERTH), 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	978-1-949373-27-84	ISBN	2411-3470	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	k.konstantoudakis@iti.gr			Approved	no
	Call Number				Serial	2285
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	Author	Tobias Andersson Granberg; Carl-Oscar Jonson; Erik Prytz; Krisjanis Steins; Martin Waldemarsson
	Title	Sensor Requirements for Logistics Analysis of Emergency Incident Sites			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	952-960
	Keywords	Sensors; Emergency Response Planning; Tracking; Team Interaction
	Abstract	Using sensors to collect data at emergency incident sites can facilitate analysis of the logistic operations. This can be used to improve planning and preparedness for new operations. Furthermore, real-time information from the sensors can serve as operational decision support. In this work in progress, we investigate the requirements on the sensors, and on the sensor data, to facilitate such an analysis. Through observations of exercises, the potential of using sensors for data collection is explored, and the requirements are considered. The results show that the potential benefits are significant, especially for tracking patients, and understanding the interaction between the response actors. However, the sensors need to be quite advanced in order to capture the necessary data.
	Address	Linköping University, Department of Science and Technology; Linköping University, Center for Disaster Medicine and Traumatology, and Department of Biomedical and Clinical Sciences; Linköping University, Department of Computer and Information Science; Linköping University, Department of Science and Technology; Linköping University, Department of Science and Technology
	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	978-1-949373-27-85	ISBN	2411-3471	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	tobias.andersson.granberg@liu.se			Approved	no
	Call Number				Serial	2286
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	Author	Michael Holzhüter; Ulrich Meissen
	Title	A Decentralized Reference Architecture for Interconnected Systems in Emergency 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	961-972
	Keywords	Civil Protection; Emergency Management; Interoperability; Interconnected Collaboration; Resilient Architecture
	Abstract	Optimal communication and information exchange are key elements for handling complex crises or disaster situations. With the increasing number of heterogeneous ICT systems, also raises the importance of adequate support for interconnectivity and information logistics between stakeholders to thoroughly gather information and to make quick but precise decisions. The main purpose of the information exchange is then to manage the crisis as quickly as possible, to provide full information to protect first responders' health and safety, to optimally dispatch resources, and to ensure coordination between different relief forces. Based on an end user survey with a particular focus on first responders, this paper introduces an evolutionary architecture to enable information exchange in crises situation or disasters. The aim is to provide a decentralized approach among heterogeneous ICT-systems which abstracts from the underlying communication technologies and heterogeneity of connected systems and fulfills the functional and non-functional requirements from end users.
	Address	Hochschule für Technik und Wirtschaft Berlin; Fraunhofer-Institut für Offene Kommunikationssysteme; Hochschule für Technik und Wirtschaft Berlin; Fraunhofer-Institut für Offene Kommunikationssysteme
	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	978-1-949373-27-86	ISBN	2411-3472	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	michael.holzhueter@fokus.fraunhofer.de			Approved	no
	Call Number				Serial	2287
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	Author	Ryan K. Williams; Nicole Abaid; James McClure; Nathan Lau; Larkin Heintzman; Amanda Hashimoto; Tianzi Wang; Chinmaya Patnayak; Akshay Kumar
	Title	Collaborative Multi-Robot Multi-Human Teams in Search and Rescue			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	973-983
	Keywords	Search \& Rescue; Autonomy; Lost-Person Modeling; GIS; Visualization
	Abstract	Robots such as unmanned aerial vehicles (UAVs) deployed for search and rescue (SAR) can explore areas where human searchers cannot easily go and gather information on scales that can transform SAR strategy. Multi-UAV teams therefore have the potential to transform SAR by augmenting the capabilities of human teams and providing information that would otherwise be inaccessible. Our research aims to develop new theory and technologies for field deploying autonomous UAVs and managing multi-UAV teams working in concert with multi-human teams for SAR. Specifically, in this paper we summarize our work in progress towards these goals, including: (1) a multi-UAV search path planner that adapts to human behavior; (2) an in-field distributed computing prototype that supports multi-UAV computation and communication; (3) behavioral modeling that yields spatially localized predictions of lost person location; and (4) an interface between human searchers and UAVs that facilitates human-UAV interaction over a wide range of autonomy.
	Address	Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech; 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	978-1-949373-27-87	ISBN	2411-3473	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	rywilli1@vt.edu			Approved	no
	Call Number				Serial	2288
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	Author	Spyros Chrysanthopoulos; Theofanis Kapetanakis; Giannis Chaidemenos; Stelios Vernardos; Harris Georgiou; Claudio Rossi
	Title	Emergency Response in Recent Urban/Suburban Disaster Events in Attica: Technology Gaps, Limitations and Lessons Learned			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	984-989
	Keywords	First Responders, Search and Rescue, Flash Flood, Urban Wildfire, Urban Operations.
	Abstract	Emergency response operations in large-scale urban/suburban disaster events is often addressed by the standard protocols and international guidelines for collapsed buildings, heavy debris, etc. However, a wide range of First Responder (FR) operations need to address various other contexts, work environments and hazards. In this paper, two real disaster events are explored as use cases for such urban/suburban FR operations, namely a flash flood and a wildfire, both in Attica, Greece (2017-2018). Based on our team's experience from these mobilizations and active participation in both these events as FR actor in the field, we present the challenges, the complexity of such multi-aspect disaster events, the limitations of emergency response, the technology gaps of the FR teams, as well as the lessons learned during these deployments. Finally, we make some notes on future prospects and possible advancements in tools and technologies that would greatly enhance the operational safety and readiness of the FR teams in such events.
	Address	Hellenic Rescue Team of Attica (HRTA); Hellenic Rescue Team of Attica (HRTA); Hellenic Rescue Team of Attica (HRTA); Hellenic Rescue Team of Attica (HRTA); Hellenic Rescue Team of Attica (HRTA); LINKS Foundation
	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	978-1-949373-27-88	ISBN	2411-3474	Medium
	Track	Technologies for First Responders	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	harris@xgeorgio.info			Approved	no
	Call Number				Serial	2289
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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	Jonas Höchst; Lars Baumgartner; Franz Kuntke; Alvar Penning; Artur Sterz; Bernd Freisleben
	Title	LoRa-based Device-to-Device Smartphone Communication for Crisis Scenarios			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	996-1011
	Keywords	LoRa, Disaster Communication, Device-To-Device Communication.
	Abstract	In this paper, we present an approach to facilitate long-range device-to-device communication via smartphones in crisis scenarios. Through a custom firmware for low-cost LoRa capable micro-controller boards, called rf95modem, common devices for end users can be enabled to use LoRa through a Bluetooth, Wi-Fi, or serial connection. We present two applications utilizing the flexibility provided by the proposed firmware. First, we introduce a novel device-to-device LoRa chat application that works a) on the two major mobile platforms Android and iOS and b) on traditional computers like notebooks using a console-based interface. Second, we demonstrate how other infrastructure-less technology can benefit from our approach by integrating it into the DTN7 delay-tolerant networking software. The firmware, the device-to-device chat application, the integration into DTN7, as well as the experimental evaluation code fragments are available under permissive open-source licenses.
	Address	University of Marbur, Germany Technical University of Darmstadt, Germany; Technical University of Darmstadt, Germany; Technical University of Darmstadt, Germany; University of Marburg, Germany; University of Marburg, Germany Technical University of Darmstadt, Germany; University of Marburg, Germany Technical University of Darmstadt, 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	978-1-949373-27-90	ISBN	2411-3476	Medium
	Track	Usability and Universal Design of ICT for Emergency Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	hoechst@informatik.uni-marburg.de			Approved	no
	Call Number				Serial	2291
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	Author	Pouyan Fotouhi Tehrani; Niklas von Kalckreuth; Selma Lamprecht
	Title	Toward an Integrative Model of Trust for Digital Emergency Communication			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	1012-1021
	Keywords	Trust; Emergency Management; Digital Communication; Modeling
	Abstract	Digital technologies have become an integral enabler of communication during various phases of emergency management (EM). A crucial prerequisite of effective communication between authorities and the public during EM is the establishment of adequate mutual trust. Trust, however, is an elusive concept which is not easily translatable into technical settings. In this paper we propose an integrative model of trust in digital communication and show how such model can be advantageous in assessing and improving trust relations in context of EM. Our interdisciplinary model, which is based on findings from psychology, sociology and computer sciences provides an abstraction which not only seizes both subjective and objective as well as personal and non-personal, \eg institutional or cultural, aspects of trust but at the same time is concrete enough to be applicable to real-life scenarios.
	Address	Weizenbaum Institute, Fraunhofer FOKUS; Weizenbaum Institute, Humboldt University Berlin; Weizenbaum Institute, Fraunhofer FOKUS
	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	978-1-949373-27-91	ISBN	2411-3477	Medium
	Track	Usability and Universal Design of ICT for Emergency Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	pouyan.fotouhi.tehrani@fokus.fraunhofer.de			Approved	no
	Call Number				Serial	2292
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	Author	Abhish Khanal; Deepak Chand; Prakash Chaudhary; Subash Timilsina; Sanjeeb Prasad Panday; Aman Shakya; Rom Kant Pandey
	Title	Search Disaster Victims using Sound Source Localization			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	1022-1030
	Keywords	Sound Source Localization (SSL); Omni-Directional Drive; Disaster Victim; Generalized Cross Correlation Phase Transform (GCC-PHAT)
	Abstract	Sound Source Localization (SSL) are used to estimate the position of sound sources. Various methods have been used for detecting sound and its localization. This paper presents a system for stationary sound source localization by cubical microphone array consisting of eight microphones placed on four vertical adjacent faces which is mounted on three wheel omni-directional drive for the inspection and monitoring of the disaster victims in disaster areas. The proposed method localizes sound source on a 3D space by grid search method using Generalized Cross Correlation Phase Transform (GCC-PHAT) which is robust when operating in real life scenario where there is lack of visibility. The computed azimuth and elevation angle of victimized human voice are fed to embedded omni-directional drive system which navigates the vehicle automatically towards the stationary sound source.
	Address	Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Sanothimi Campus, Tribhuvan 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	978-1-949373-27-92	ISBN	2411-3478	Medium
	Track	Usability and Universal Design of ICT for Emergency Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	072bex402@ioe.edu.np			Approved	no
	Call Number				Serial	2293
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	Author	Harrison Cole
	Title	Accessible Mitigation Planning: Tactile Hazard Map Design and Evaluation			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	1031-1037
	Keywords	Cartography; Accessibility; Disability; Tactile; Mitigation Planning
	Abstract	While creating a community hazard mitigation plan (HMP) has become recognized as a key component of successful disaster management, significant portions of the process are often inaccessible to people with vision disabilities. Maps in particular are often large, visually dense documents that are printed on two-dimensional paper, or distributed via PDF with no alternate text. For people with profound low vision or who are blind, alternative media is required. The research discussed here proposes that tactile maps may present an accessible and cost-effective medium for representing geospatial data relevant to the hazard mitigation planning process. Using flood insurance rate maps (FIRMs) distributed by the Federal Emergency Management Agency (FEMA) as a starting point, this paper proposes an evaluatory framework for transcribing conventional maps into tactile documents, as well as characterizing users' experiences using them for mitigation planning, directions for future research and generalizing the process for applications in other domains.
	Address	The Pennsylvania 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	978-1-949373-27-93	ISBN	2411-3479	Medium
	Track	Usability and Universal Design of ICT for Emergency Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	harrisoncole@psu.edu			Approved	no
	Call Number				Serial	2294
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	Author	Terje Gjøsæter; Jaziar Radianti; Weiqin Chen
	Title	Towards Situational Disability-aware Universally Designed Information Support Systems for Enhanced Situational Awareness			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	1038-1047
	Keywords	Situational Awareness; Situational Disabilities; Universal Design; Decision Making; Process Model
	Abstract	This paper takes on the challenge of designing situational awareness information systems that take into account not only the prevalence of so-called demons of situational awareness, but also situational disabilities that will typically occur in a disaster situation, both in the control room and in the field among the general public as well as first responders. It further outlines how a situational awareness information system process model can be adapted and used as a basis for designing situational awareness information support systems that address these issues with the help of Universal Design principles.
	Address	Oslo Metropolitan University; University of Agder; Oslo Metropolitan 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	978-1-949373-27-94	ISBN	2411-3480	Medium
	Track	Usability and Universal Design of ICT for Emergency Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	tergjo@oslomet.no			Approved	no
	Call Number				Serial	2295
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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	Alessandro Farasin; Luca Colomba; Giulio Palomba; Giovanni Nini
	Title	Supervised Burned Areas Delineation by Means of Sentinel-2 Imagery and Convolutional Neural Networks			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	1060-1071
	Keywords	Burned Area Delineation, Sentinel-2, U-Net, CuMedVision1, Convolutional Neural Network, Deep Learning, Supervised Learning, Pixel-wise Segmentation.
	Abstract	Wildfire events are increasingly threatening our lands, cities, and lives. To contrast this phenomenon and to limit its damages, governments around the globe are trying to find proper counter-measures, identifying prevention and monitoring as two key factors to reduce wildfires impact worldwide. In this work, we propose two deep convolutional neural networks to automatically detect and delineate burned areas from satellite acquisitions, assessing their performances at scale using validated maps of burned areas of historical wildfires. We demonstrate that the proposed networks substantially improve the burned area delineation accuracy over conventional methods.
	Address	Politecnico di Torino – DAUIN dept., and LINKS Foundation – DSISA dept.; Politecnico di Torino – DAUIN dept.; LINKS Foundation – DSISA dept.; LINKS Foundation – DSISA dept.
	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	978-1-949373-27-96	ISBN	2411-3482	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	alessandro.farasin@polito.it			Approved	no
	Call Number				Serial	2297
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	Author	Giulio Palomba; Alessandro Farasin; Claudio Rossi
	Title	Sentinel-1 Flood Delineation with Supervised Machine Learning			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	1072-1083
	Keywords	Floods, Mapping, Deep Learning, Copernicus EMS, Sentinel-1, SAR.
	Abstract	Floods are one of the major natural hazards in terms of affected people and economic damages. The increasing and often uncontrolled urban sprawl together with climate change effects will make future floods more frequent and impacting. An accurate flood mapping is of paramount importance in order to update hazard and risk maps and to plan prevention measures. In this paper, we propose the use of a supervised machine learning approach for flood delineation from satellite data. We train and evaluate the proposed algorithm using Sentinel-1 acquisition and certified flood delineation maps produced by the Copernicus Emergency Management Service across different geographical regions in Europe, achieving increased performances against previously proposed supervised machine learning approaches for flood mapping.
	Address	LINKS Foundation – DSISA dept.; Politecnico di Torino – DAUIN dept. and LINKS Foundation – DSISA dept.; LINKS Foundation – DSISA dept.
	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	978-1-949373-27-97	ISBN	2411-3483	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	giulio.palomba@linksfoundation.com			Approved	no
	Call Number				Serial	2298
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