Tim-Jonathan Huyeng, Timo Bittner, & Uwe Rüppel. (2022). Examining the Feasibility of LoRa-based Monitoring in Large-scale Disaster Response Scenarios. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 541–550). Tarbes, France.
Abstract: Following a natural disaster or other large-scale events which require emergency response assessing and monitoring the situation at hand is of critical importance. However, some infrastructure that is often relied upon such as cellular service or the power grid might be temporarily disrupted or entirely unavailable. In order to be able to still transmit relevant monitoring data gathered from sensors, the use of a low-cost LPWAN with LoRa modulation technique is suggested in the approach presented here. Combined with an analysis of disaster response in Germany the relevant aspects are consolidated in a concept utilizing LoRaWAN with a ChirpStack backend that is easy to set up and entirely independent of external infrastructure. The proposed addition which aims to support disaster control management in Germany is then tested in conjunction with a fictional flooding scenario where an area is monitored with autarkic sensors using LoRaWAN technology.
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Zainab Akhtar, Ferda Ofli, & Muhammad Imran. (2021). Towards Using Remote Sensing and Social Media Data for Flood Mapping. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 536–551). Blacksburg, VA (USA): Virginia Tech.
Abstract: Ghana's capital, the Greater Accra Metropolitan Area (GAMA) is most vulnerable to flooding due to its high population density. This paper proposes the fusion of satellite imagery, social media, and geospatial data to derive near real-time (NRT) flood maps to understand human activity during a disaster and the extent of infrastructure damage. To that end, the paper presents an automatic thresholding technique for NRT flood mapping using Sentinel-1 images where four different speckle filters are compared using the VV, VH and VV/VH polarization to determine the best polarization(s) for delineating flood extents. The VV and VH bands together on Perona-Malik filtered images achieved the highest accuracy with an F1-score of 81.6%. Moreover, all tweet text and images were found to be located in flooded regions or in very close proximity to a flooded region, thus allowing crisis responders to better understand vulnerable communities and what humanitarian action is required.
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Jingxian Wang, Lida Huang, Guofeng Su, Tao Chen, Chunhui Liu, & Xiaomeng Wang. (2021). UAV and GIS Based Real-time Display System for Forest Fire. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 527–535). Blacksburg, VA (USA): Virginia Tech.
Abstract: When a forest fire occurs, the commander cannot obtain information in time, and the rescue command is like groping in the dark. In order to solve the problem, this research establishes a real-time forest fire display system based on UAV and GIS. The UAV is equipped with visible light and thermal imaging cameras to transmit back forest fire scenes in real time. Based on GIS, the system can extract the boundary of the fire field through image processing and 3D modeling technology, and display various forest fire information on the screen. Through image processing and 3D modeling technology, the boundary of the fire field can be extracted and displayed on the screen. We conducted several experiments to test the accuracy and the reliability of the system. The result shows that the accuracy, reliability and real-time capability can be guaranteed in small-scale forest fires.
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Lucas Dorigueto, Carlos Brumatti, Erick Figueiredo, & Jugurta Lisboa-Filho. (2021). A Framework for Landslide Information Management Systems Development. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 515–526). Blacksburg, VA (USA): Virginia Tech.
Abstract: Volunteered Geographic Information (VGI) integrated with Disaster Information Management Systems (DIMS) has great potential to assist managers and the community in times of emergency. However, there is little research focusing on integrating VGI with DIMS, in addition, there are a lack of use of standards of interoperability and emergency, which can impair interoperability and the quality of the information contained in these systems. This work presents a fully interoperable framework aimed at the construction of DIMS, which integrates official data and VGI through ISO and OGC standards, allowing managers and the community to work with official data and VGI in order to assist managers in decision making. To show the viability of the framework, a case study using data from the risk situation of dams located in the municipality of Barão de Cocais in Brazil was carried out.
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Tinghao Zhang, Lida Huang, Tao Chen, & Shuo Bai. (2021). GIS Based Emergency Management Framework for Large-scale Events: A Case Study of the Torch Relay Activity. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 503–514). Blacksburg, VA (USA): Virginia Tech.
Abstract: Due to the high popular concentration of large-scale events, once an emergency (like a stampede) occurs, it will often cause severe casualties. Moreover, since the widespread of the COVID-19, the prevention of the novel coronavirus should also be considered during mass gatherings. How to reduce the probability and potential consequence of emergencies is of great significance. This research designs an emergency management framework using ArcGIS-based geographic information technology for large-scale events. To verify the effectiveness of our framework, we take the Winter Olympic torch relay in university as an example. The paper is mainly divided into two parts, emergency resource allocation and the emergency prevention model. The former part focuses on the site selection of emergency sentries and emergency hospitals during the torch relay. In the latter part, an emergency prevention model is designed for two significant emergencies: stampede and epidemic.
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