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Author |
Stephen Kelly; Xiubo Zhang; Khurshid Ahmad |
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Title |
Mining Multimodal Information on Social Media for Increased Situational Awareness |
Type |
Conference Article |
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Year |
2017 |
Publication |
Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management |
Abbreviated Journal |
Iscram 2017 |
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Volume |
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Issue |
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Pages |
613-622 |
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Keywords |
Spatio-temporal; Social media analysis; Multimodal analysis; Geolocation |
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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. |
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Address |
rinity College Dublin, Ireland |
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Publisher |
Iscram |
Place of Publication  |
Albi, France |
Editor |
Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
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Track |
Social Media Studies |
Expedition |
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Conference |
14th International Conference on Information Systems for Crisis Response And Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
2049 |
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Author |
Sophia B. Liu; Leysia Palen |
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Title |
Spatiotemporal mashups: A survey of current tools to inform next generation crisis support |
Type |
Conference Article |
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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 |
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Issue |
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Pages |
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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 |
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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. |
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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 |
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Thesis |
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Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Gothenburg |
Editor |
J. Landgren, S. Jul |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9789163347153 |
Medium |
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Track |
Human-Computer Interaction |
Expedition |
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Conference |
6th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
717 |
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Author |
Sérgio Freire; Christoph Aubrecht |
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Title |
Assessing spatio-temporal population exposure to tsunami hazard in the Lisbon Metropolitan Area |
Type |
Conference Article |
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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 |
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Volume |
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Issue |
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Pages |
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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 |
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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. |
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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 |
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Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Lisbon |
Editor |
M.A. Santos, L. Sousa, E. Portela |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9789724922478 |
Medium |
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Track |
Geographic Information Science |
Expedition |
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Conference |
8th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
511 |
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Author |
Sérgio Freire; Aneta Florczyk; Martino Pesaresi |
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Title |
New Multi-temporal Global Population Grids ? Application to Volcanism |
Type |
Conference Article |
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Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
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Volume |
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Issue |
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Pages |
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Keywords |
Built up; GHSL; Population Distribution; Dasymetric Mapping; Volcanoes; Spatio-temporal Analysis |
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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. |
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Thesis |
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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 |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3433 |
ISBN |
978-84-608-7984-54 |
Medium |
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Track |
Geospatial Data and Geographical Information Science |
Expedition |
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Conference |
13th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1373 |
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Author |
Alessandro Farasin; Paolo Garza |
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Title |
PERCEIVE: Precipitation Data Characterization by means on Frequent Spatio-Temporal Sequences |
Type |
Conference Article |
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Year |
2018 |
Publication |
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2018 |
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Volume |
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Issue |
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Pages |
1081-1088 |
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Keywords |
Spatio-temporal sequence mining, Data characterization |
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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. |
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Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
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Track |
1st International Workshop on Intelligent Crisis Management Technologies for Climate Events (ICMT) |
Expedition |
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Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
2180 |
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Author |
Christoph Aubrecht; Klaus Steinnocher; Hermann Huber |
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Title |
DynaPop – Population distribution dynamics as basis for social impact evaluation in crisis management |
Type |
Conference Article |
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Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
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Volume |
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Issue |
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Pages |
314-318 |
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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 |
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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. |
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Address |
AIT Austrian Institute of Technology, Energy Department, Austria; AIT Austrian Institute of Technology, Safety and Security Department, Austria |
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Thesis |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
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Track |
Geographic Information Science |
Expedition |
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Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
279 |
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Author |
Christopher E. Oxendine; Emily Schnebele; Guido Cervone; Nigel Waters |
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Title |
Fusing non-authoritative data to improve situational awareness in emergencies |
Type |
Conference Article |
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Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
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Volume |
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Issue |
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Pages |
762-766 |
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Keywords |
Damage detection; Earth (planet); Damage assessments; Emergency; Emergency evacuation; Emergency operations; Evacuation; Non-authoritative data; Situational awareness; Spatio-temporal data; Information systems |
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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. |
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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 |
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Corporate Author |
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Thesis |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
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Track |
Social Media in Crisis Response and Management |
Expedition |
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Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
825 |
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