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| Author | Douglas Alem; Alistair Clark | ||||
| Title | Insights from two-stage stochastic programming in emergency logistics | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
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| Keywords | disaster in Rio de Janeiro; disaster relief; Emergency logistics; floods, landslides; scenario generation; two-stage stochastic programming | ||||
| Abstract | This paper discusses the practical aspects and resulting insights of the results of a two-stage mathematical network flow model to help make the decisions required to get humanitarian aid quickly to needy recipients as part of a disaster relief operation. The aim of model is to plan where to best place aid inventory in preparation for possible disasters, and to make fast decisions about how best to channel aid to recipients as fast as possible. Humanitarian supply chains differ from commercial supply chains in their greater urgency of response and in the poor quality of data and increased uncertainty about important inputs such as transportation resources, aid availability, and the suddenness and degree of “demand”. The context is usually more chaotic with poor information feedback and a multiplicity of decision-makers in different aid organizations. The model attempts to handle this complexity by incorporating practical decisions, such as pre-allocation of emergency goods, transportation policy, fleet management and procurement, in an uncertainty environment featured by a scenario-based approach. Preliminary results based on the floods and landslides disaster of the Mountain Region of Rio de Janeiro state, Brazil, point to how to cope with these challenges by using the mathematical model. | ||||
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| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
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| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Analytical Modelling and Simulation | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1186 | |||
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| Author | Jorge Vargas-Florez; Grovher Palomino; Andres Flores; Gloria Valdivia; Carlos Saito; Daniel Arteaga; Mario Balcazar; Miguel Fernandez; José Oliden | ||||
| Title | Identifying potential landslide location using Unmanned Aerial Vehicles (UAVs) | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages | |||
| Keywords | Susceptibility mapping, disaster prevention, landslides, drones | ||||
| Abstract | The impact of landslides is determined by the previous state of vulnerability and susceptibility present in a community. Vulnerability is related to physical aspects and susceptibility is defined as the propensity or tendency of an area to be affected by the occurrence of a given hazard. Knowledge of geography allows us to characterize and measure some of these factors. For example, in landslides called huaicos in Peru, these are related to the existence of a slope and soil type of the hills favorable to the loosening of land masses, as well as the increase in rainfall and the presence of streams. The use of UAVs (Unmanned Aerial Vehicles, commonly called drones) for the identification of susceptibility zones is presented in this paper. The result is positive for using the georeferenced data to identify potential landslide flow using as unique criterion surface slopes. |
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| Address | Pontifical Catholic University of Peru, Peru;National University of Engineering, Peru | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
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| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T6- Geospatial Technologies and Geographic Information Science for Crisis Management (GIS) | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1887 | |||
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| Author | Tiago Badre Marino; Bruno Santos Do Nascimento; Marcos R. S. Borges | ||||
| Title | GIS supporting data gathering and fast decision making in emergencies situations | Type | Conference Article | ||
| Year | 2012 | Publication | ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2012 |
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| Keywords | Geographic information systems; Information systems; Landslides; Mobile devices; Mobile telecommunication systems; Risk management; Telecommunication networks; Wireless networks; Data gathering; Data Sharing; Disaster areas; Emergency management; Field assessment; Latin America; Online registration; Web database; Disasters | ||||
| Abstract | This proposal rises from the Center for Disasters Scientific Support experience over eleven years supporting over a hundred disasters in Latin America. It also presents a case study applied to landslides assessments in Teresopolis (Brazil) city, when all field-generated knowledge was still registered in paper and later, at the base station, uploaded to database and finally available for managers evaluation and decision. The proposed methodology creates a platform (still under development) which allows online registration from different field agents during their evaluations enabling data upload combining mobile devices and telecommunication network (or Wi-Fi) technologies. Teams can also customize forms for different information classes (i.e. landslide assessment, rescued person, blocked road) and still retain the possibility to attach images, videos, other files related to each inspection. Incoming data are stored into a web database available for a real-time coordinators evaluation wherever they are (sometimes over a thousand of miles away from disaster area). © 2012 ISCRAM. | ||||
| Address | Universidade Federal Do Rio de Janeiro, Brazil | ||||
| Corporate Author | Thesis | ||||
| Publisher | Simon Fraser University | Place of Publication | Vancouver, BC | Editor | L. Rothkrantz, J. Ristvej, Z.Franco |
| Language | English | Summary Language | English | Original Title | |
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| ISSN | 2411-3387 | ISBN | 9780864913326 | Medium | |
| Track | Geographic Information Science and Technology | Expedition | Conference | 9th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 163 | |||
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| Author | Aibek Musaev; De Wang; Calton Pu | ||||
| Title | LITMUS: Landslide detection by integrating multiple sources | 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 | Pages | 677-686 | ||
| Keywords | Bayesian networks; Disasters; Hazards; Information systems; Integration; Landslides; Nasa; Rain; Rain gages; Landslide detection; Litmus; Multi-source integrations; Physical sensors; Social sensors; Data integration | ||||
| Abstract | Disasters often lead to other kinds of disasters, forming multi-hazards such as landslides, which may be caused by earthquakes, rainfalls, water erosion, among other reasons. Effective detection and management of multihazards cannot rely only on one information source. In this paper, we evaluate a landslide detection system LITMUS, which combines multiple physical sensors and social media to handle the inherent varied origins and composition of multi-hazards. LITMUS integrates near real-time data from USGS seismic network, NASA TRMM rainfall network, Twitter, YouTube, and Instagram. The landslide detection process consists of several stages of social media filtering and integration with physical sensor data, with a final ranking of relevance by integrated signal strength. Applying LITMUS to data collected in October 2013, we analyzed and filtered 34.5k tweets, 2.5k video descriptions and 1.6k image captions containing landslide keywords followed by integration with physical sources based on a Bayesian model strategy. It resulted in detection of all 11 landslides reported by USGS and 31 more landslides unreported by USGS. An illustrative example is provided to demonstrate how LITMUS' functionality can be used to determine landslides related to the recent Typhoon Haiyan. | ||||
| Address | Georgia Institute of Technology, 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 | |
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| 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 | 801 | |||
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