| Comparing four operational SAR-based water and flood detection approaches. | Summary
Comparison of:œ Water Mask Processor (WaMaPro); œ Rapid Mapping of Flooding (RaMaFlood); œ TSX Flood Service (TFS); œ TanDEM-X Water Indication Mask processor (TDX WAM). |
| Optimal Path Selection under Emergency Based on the Fuzzy Comprehensive Evaluation Method. | Summary
Algorithm development and simulation |
| Cross-domain integrating and reasoning spaces for offsite nuclear emergency response. | Summary
Furthermore, with a fictive nuclear accident , the relevant CDIRS spaces and ordering rules are constructed, and then the appropriate cross-domain integrated is obtained and verified effectively by reasoning and simulating in the CDIRS modelA fictitious example (the ‘‘A” shown in Fig. 1) is used here to illustrate the principle and the implementation process of CDIRS: In this scenario, a chain is caused by a nuclear accident ‘‘cooling system failing”; and it has rapidly evolved from ‘‘core melting” to ‘‘containment broken”, and then from ‘‘containment broken” to ‘‘radiation leaking” event which may cause a large number of casualties. |
| Geotagging Twitter Messages in Crisis Management. | Summary
Software developmentFirst, we evaluated the system by comparing its output against human judgement as ground truth for a selection of 500 tweetsSecondly, we tested our geotagger performance with the testing dataset against other geocoding platforms including: The Alchemy API NER and the Yahoo! GeoPlanet service.The IBM research (Australia) plans the OzCrsisTracker 2.0 deployment in the Australian Bushfire and Flood season 2014. |
| Modeling and representation for earthquake emergency response knowledge: perspective for working with geo-ontology. | Summary
In this paper, we suggest a to this problem using earthquake (EDER) knowledge.We present a computer-based modeling and representation method for EDER knowledge, which is a foundation for computer-aided knowledge use. |
| Preparing for Emergency Situations. | Summary
development, development of Test Scenarios and Test Data Collection in progress |
| Towards a Holistic Framework for the Evaluation of Emergency Plans in Indoor Environments. | Summary
Holistic framework descriptionImplementationtesting |
| Context-based automatic reconstruction and texturing of 3D urban terrain for quick-response tasks. | Summary
Presentation of a robust, modular algorithm for context-based urban terrain modeling from sensor datawe proposed and described an automatic and a semi-automatic method for pose estimationAlgortihm for: geometric reconstruction, roof analysis and visibility analysis and texturing processes, to synthesise data |
| Supporting synthesis in geovisualization. | Summary
Eighteen participants were recruited for this study, including eight disease surveillance and biological/chemical threat analysts from PNNL, five GIScience experts from the Penn State GeoVISTA Center, and five infectious disease experts from the Penn State Center for Infectious Disease Dynamics (CIDD).Participants are asked to devise hypotheses from the collection of artifacts, and to arrange and modify artifacts and the workspace using standard office tools such as pens, post-it notes, and markersThis article reports synthesis results from sessions with analysts at Pacific Northwest National Laboratory (PNNL) and experts at The Pennsylvania State University (PSU)Our featured an hour-long synthesis activity in which participants work in isolation to organize and annotate a set of physical artifactsParticipants were provided markers, pens, adhesive tags, and post-it notes of multiple sizes and colors to modify the workspace and artifacts as desired. |
| Simulating effects of signage, groups, and crowds on emergent evacuation patterns. | Summary
Planning of the simulation:During the simulation, the dynamic attribute values are updated at each process stage as described belowThe Perception Module updates four attributes such as:• cues, such as smoke and alarm, that are visible or audible to the agent.• Visible floor objects, such as doors and signs, that are visible to the agent.• Visible group members that are visible to the agent.• Neighboring agents that are visible to and are located within a certain radius from the agentThe Interpretation Module maps the current knowledge of the agent into a set of internal thresholds that describe the urge and well-being of the agent.The decision-making module invokes the decision tree modeling the behavior assigned to the agent. Given the agent’s characteristics and the invoked decision tree, it looks up the agent’s behavior and determines the long- term navigation goal, such as the familiar exit of the agent or the location of the group leader, and the intermediate navigation point given the agent’s knowledge and location.The Locomotion Module calculates the agent’s movement toward the navigation target and returns the updated spatial position of the agents, which areCartesian coordinates (x, y, and z) in the continuous space.The Memory Module registers the decision made during the simulation cycle and updates the spatial knowledge. The spatial knowledge is an array storing the navigation points that the agents have visited. The agents remembered the traveled navigation points and can later refer to the spatial knowledge to avoid backtracking. |
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Portfolio of Solutions web site has been initially developed in the scope of DRIVER+ project. Today, the service is managed by AIT Austrian Institute of Technology GmbH., for the benefit of the European Management. PoS is endorsed and supported by the Disaster Competence Network Austria (DCNA) as well as by the STAMINA and TeamAware H2020 projects. |