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Author Christoph Aubrecht; Klaus Steinnocher; Hermann Huber
Title DynaPop – Population distribution dynamics as basis for social impact evaluation in crisis management Type Conference Article
Year 2014 Publication ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2014
Volume Issue (up) Pages 314-318
Keywords Information systems; Population distribution; Population dynamics; Risk assessment; Activity patterns; Crisis management; Evacuation planning; Population distribution patterns; Population dynamics models; Population exposure; Spatial disaggregation; Spatio-temporal models; Economic and social effects
Abstract In this paper ongoing developments regarding the conceptual setup and subsequent implementation logic of a seamless spatio-temporal population dynamics model are presented. The DynaPop model aims at serving as basic input for social impact evaluation in crisis management. In addition to providing the starting point for assessing population exposure dynamics, i.e. the location and number of affected people at different stages during an event, knowledge of spatio-temporal population distribution patterns is also considered crucial for a set of other related aspects in disaster risk and crisis management including evacuation planning and casualty assessment. DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation.
Address AIT Austrian Institute of Technology, Energy Department, Austria; AIT Austrian Institute of Technology, Safety and Security Department, Austria
Corporate Author Thesis
Publisher The Pennsylvania State University Place of Publication University Park, PA Editor S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780692211946 Medium
Track Geographic Information Science Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 279
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Author Sérgio Freire; Christoph Aubrecht
Title Assessing spatio-temporal population exposure to tsunami hazard in the Lisbon Metropolitan Area Type Conference Article
Year 2011 Publication 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 Abbreviated Journal ISCRAM 2011
Volume Issue (up) Pages
Keywords Hazards; Information systems; Mapping; Population distribution; Population statistics; Land use and land cover; Lisbon; Metropolitan area; Population exposure; Spatio-temporal; Spatiotemporal distributions; Tsunami hazards; Tsunami inundation; Tsunamis
Abstract The coastal region of Lisbon, Portugal, is potentially subject to tsunami hazard. Mapping and assessing tsunami risk requires giving adequate consideration to the population exposure. In the present work we model and map the spatio-temporal distribution of population in the daily cycle and analyze it with a tsunami hazard map to better assess tsunami risk in the Lisbon Metropolitan Area. New high-resolution daytime and nighttime population distribution surfaces are developed using 'intelligent dasymetric mapping' to combine best-available census data and statistics with land use and land cover data. Mobility statistics are considered for mapping daytime distribution. Finally, the population distribution maps are combined with the Tsunami Inundation Susceptibility map to assess potential human exposure to tsunami in daytime and nighttime periods. Results show that a significant amount of population is potentially at risk, and its numbers increase from nighttime to daytime, especially in the zones of high susceptibility.
Address New University of Lisbon, E-GEO, Geography and Regional Planning Research Center, Portugal; AIT Austrian Institute of Technology, Foresight and Policy Development Department, Austria
Corporate Author Thesis
Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Lisbon Editor M.A. Santos, L. Sousa, E. Portela
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9789724922478 Medium
Track Geographic Information Science Expedition Conference 8th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 511
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Author Sophia B. Liu; Leysia Palen
Title Spatiotemporal mashups: A survey of current tools to inform next generation crisis support Type Conference Article
Year 2009 Publication ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives Abbreviated Journal ISCRAM 2009
Volume Issue (up) Pages
Keywords Information systems; Surveys; Crisis informatics; High-level design; Information and Communication Technologies; Large-scale emergency; Spatio-temporal data; Technology designs; Temporal representations; Web mashups; Design
Abstract Developments in information and communication technology (ICT) have adjusted the opportunities for spatial and temporal representations of data, possibly permitting the simultaneous visualization of how different regions and populations are affected during large-scale emergencies and crises. We surveyed 13 crisis-related mashups to derive some high-level design directions to guide the design and testing of next generation crisis support tools. The current web mashups offer a new way of looking at how crises are spatiotemporally ordered. However, since all technology is constrained by limitations of design choice, examining the limits and possibilities of what current design choices afford can inform attributes of what next generation crisis support tools would require.
Address ConnectivIT Lab, Alliance for Technology, Learning and Society Institute, University of Colorado, Boulder, United States; Department of Computer Science, ConnectivIT Lab, University of Colorado, Boulder, United States
Corporate Author Thesis
Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Gothenburg Editor J. Landgren, S. Jul
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9789163347153 Medium
Track Human-Computer Interaction Expedition Conference 6th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 717
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Author Christopher E. Oxendine; Emily Schnebele; Guido Cervone; Nigel Waters
Title Fusing non-authoritative data to improve situational awareness in emergencies Type Conference Article
Year 2014 Publication ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2014
Volume Issue (up) Pages 762-766
Keywords Damage detection; Earth (planet); Damage assessments; Emergency; Emergency evacuation; Emergency operations; Evacuation; Non-authoritative data; Situational awareness; Spatio-temporal data; Information systems
Abstract In order to coordinate emergency operations and evacuations, it is vital to accurately assess damage to people, property, and the environment. For decades remote sensing has been used to observe the Earth from air, space and ground based sensors. These sensors collect massive amounts of dynamic and geographically distributed spatiotemporal data every day. However, despite the immense quantity of data available, gaps are often present due to the specific limitations of the sensors or their carrier platforms. This article illustrates how nonauthoritative data such as social media, news, tweets, and mobile phone data can be used to fill in these gaps. Two case studies are presented which employ non-authoritative data to fill in the gaps for improved situational awareness during damage assessments and emergency evacuations.
Address Department of Geography and Environmental Engineering, United States Military Academy, United States; Department of Geography and GeoInformation Science, George Mason University, United States; Department of Geography, Penn State University, United States
Corporate Author Thesis
Publisher The Pennsylvania State University Place of Publication University Park, PA Editor S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780692211946 Medium
Track Social Media in Crisis Response and Management Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 825
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Author Sérgio Freire; Aneta Florczyk; Martino Pesaresi
Title New Multi-temporal Global Population Grids ? Application to Volcanism Type Conference Article
Year 2016 Publication ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2016
Volume Issue (up) Pages
Keywords Built up; GHSL; Population Distribution; Dasymetric Mapping; Volcanoes; Spatio-temporal Analysis
Abstract Better and finer global analyses of human exposure and risk of natural disasters require improved geoinformation on population distribution and densities, in particular concerning temporal and spatial resolution and capacity for change assessment. This paper presents the development of new multi-temporal global population grids and illustrates their value in the context of risk analysis by estimating the worldwide distribution of population in relation to recent volcanism. Results indicate that almost 6% of the world?s 2015 population lived within 100 km of a volcano with at least one significant eruption, and more than 12% within 100 km of a Holocene volcano, with human concentrations in this zone increasing since 1990 above the global population change rate. The novel 250-m resolution population grids constitute the new state-of-the-art in terms of global geospatial population data, with the potential to advance modeling and analyses at all stages of the emergency management cycle.
Address
Corporate Author Thesis
Publisher Federal University of Rio de Janeiro Place of Publication Rio de Janeiro, Brasil Editor A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3433 ISBN 978-84-608-7984-54 Medium
Track Geospatial Data and Geographical Information Science Expedition Conference 13th International Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 1373
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Author Stephen Kelly; Xiubo Zhang; Khurshid Ahmad
Title Mining Multimodal Information on Social Media for Increased Situational Awareness Type Conference Article
Year 2017 Publication Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2017
Volume Issue (up) Pages 613-622
Keywords Spatio-temporal; Social media analysis; Multimodal analysis; Geolocation
Abstract Social media platforms have become a source of high volume, real-time information describing significant events in a timely fashion. In this paper we describe a system for the real-time extraction of information from text and image content in Twitter messages and combine the spatio-temporal metadata of the messages to filter the data stream for emergency events and visualize the output on an interactive map. Twitter messages for a geographic region are monitored for flooding events by analysing the text content and images posted. Events detected are compared with a ground truth to see if information in social media correlates with actual events. We propose an Intrusion Index as part of this prototype to facilitate ethical harvesting of data. A map layer is created by the prototype system that visualises the analysis and filtered Twitter messages by geolocation.
Address rinity College Dublin, Ireland
Corporate Author Thesis
Publisher Iscram Place of Publication Albi, France Editor Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN Medium
Track Social Media Studies Expedition Conference 14th International Conference on Information Systems for Crisis Response And Management
Notes Approved no
Call Number Serial 2049
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Author Alessandro Farasin; Paolo Garza
Title PERCEIVE: Precipitation Data Characterization by means on Frequent Spatio-Temporal Sequences Type Conference Article
Year 2018 Publication ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2018
Volume Issue (up) Pages 1081-1088
Keywords Spatio-temporal sequence mining, Data characterization
Abstract Nowadays large amounts of climatology data, including daily precipitation data, are collected by means of sensors located in different locations of the world. The data driven analysis of these large data sets by means of scalable machine learning and data mining techniques allows extracting interesting knowledge from data, inferring interesting patterns and correlations among sets of spatio-temporal events and characterizing them. In this paper, we describe the PERCEIVE framework. PERCEIVE is a data-driven framework based on frequent spatio-temporal sequences and aims at extracting frequent correlations among spatio-temporal precipitation events. It is implemented by using R and Apache Spark, for scalability reasons, and provides also a visualization module that can be used to intuitively show the extracted patterns. A preliminary set of experiments show the efficiency and the effectiveness of PERCEIVE.
Address
Corporate Author Thesis
Publisher Rochester Institute of Technology Place of Publication Rochester, NY (USA) Editor Kees Boersma; Brian Tomaszeski
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-0-692-12760-5 Medium
Track 1st International Workshop on Intelligent Crisis Management Technologies for Climate Events (ICMT) Expedition Conference ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 2180
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