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Artur Ricardo Bizon, Luciana P. de Araújo Kohler, Adilson Luiz Nicoletti, Fernanda Dal Bosco, Murilo Schramm da Silva, & Thales Bohn Pessatti. (2020). Integration statistical systems for land cover mapping in Southern Brazil. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 498–505). Blacksburg, VA (USA): Virginia Tech.
Abstract: The remote sensing is a way to optimize the process of land cover classification allowing that this process will be by high definition images of satellite. For the research it was used the Google Earth Engine with JavaScript programming language to classify the images, identifying the areas with forest or reforest. It was identified that classifiers Random Forest and Logistic Regression have a high performance in classify the images. From them it was developed functions to process automatically of new images with purpose of classify them in relation to land cover.
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Einar Bjørgo. (2004). Satellite imagery and GIS for disaster response & management in the United Nations: The UNOSAT approach. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 105–110). Brussels: Royal Flemish Academy of Belgium.
Abstract: Remote sensing and Geographic Information Systems (GIS) have the potential to provide United Nations (UN) humanitarian agencies and their partners with much needed disaster related information and improved management of resources. However, the technical nature of these tools requires considerable expertise to fully benefit from satellite images and related geographic information. The UN Office for Project Services (UNOPS) is implementing the UNOSAT service on behalf of the UN Institute on Training and Research (UNITAR) together with several private actors. UNOSAT provides the UN and its partners with the expertise in Earth Observation (EO) and GIS applications. As a crisis is part of a spectrum of disaster related events, UNOSAT provides services in all phases of humanitarian assistance, including planning, crisis response, relief and development. UNOSAT's objectives are to facilitate the territory planning and monitoring processes of local authorities, local technicians, development project managers and humanitarian field operators working in coordination with or within the framework of UN activities, on issues such as disaster management, risk prevention, peace keeping operations, post conflict reconstruction, environmental rehabilitation and social and economic development. A key part of this work is to accelerate and expand the use of accurate geographic information derived from EO-satellite imagery. UNOSAT is also involved in several international initiatives aimed at improved crisis response and management, such as the International Charter “Space and Major Disasters”, an important asset in providing timely information to relief personnel on the ground. By working closely with its UN sister agencies, UNOPS/UNOSAT offers a one-stop-shop for satellite imagery and GIS services related to disaster response & management within the United Nations. © Proceedings ISCRAM 2004.
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Marline Claessens, Nicolas Lewyckyj, Jane Biesemans, & Jurgen Everaerts. (2005). Pegasus, a UAV project for disaster management. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 233–236). Brussels: Royal Flemish Academy of Belgium.
Abstract: The Flemish Institute for Technological Research (Vito) in Belgium has initiated in 2000 the PEGASUS (Policy support for European Governments by Acquisition of information from Satellite and UAV-borne Sensors) project which envisages the development of a solar powered UAV (Unmanned Aerial Vehicle) containing several types of instruments for remote sensing and flying at an altitude of about 20 km. The aircraft can be deployed rapidly in crisis situations and provide disaster managers with ~1 m resolution images (or better if required) of the affected area. High quality data shall be received in less than half an hour from a mobile ground station that is in direct contact with the UAV, which can operate as long as requested by the user. The PEGASUS HALE-UAV is a flexible and cost-effective tool that will allow officials and local authorities to dispose quickly over relevant geographical information in an emergency situation. The first demonstration flight of the PEGASUS HALE-UAV shall take place in the summer of 2005 over Flanders.
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Tom De Groeve, & Patrick Riva. (2009). Early flood detection and mapping for humanitarian response. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Space-based river monitoring can provide a systematic, timely and impartial way to detect floods of humanitarian concern. This paper presents a new processing method for such data, resulting in daily flood magnitude time series for any arbitrary observation point on Earth, with lag times as short as 4h. Compared with previous work, this method uses image processing techniques and reduces the time to obtain a 6 year time series for an observation site from months to minutes, with more accurate results and global coverage. This results in a daily update of major floods in the world, with an objective measure for their magnitude, useful for early humanitarian response. Because of its full coverage, the grid-based technique also allows the automatic creation of low-resolution flood maps only hours after the satellite passes, independent of cloud coverage.
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Tom De Groeve, Zsofia Kugler, & G. Robert Brakenridge. (2007). Near real time flood alerting for the global disaster alert and coordination system. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 33–39). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: A new flood monitoring module is in development for the Global Disaster Alert and Coordination System (GDACS). GDACS is an information system designed to assist humanitarian responders with their decisions in the early onset after a disaster. It provides near-real time flood alerts with an initial estimate of the consequences based on computer models. Subsequently, the system gathers information in an automated way from relevant information sources such as international media, mapping and scientific organizations. The novel flood detection methodology is based on daily AMSR-E passive microwave measurement of 2500 flood prone sites on 1435 rivers in 132 countries. Alert thresholds are determined from the time series of the remote observations and these are validated using available flood archives (from 2002 to present). Preliminary results indicate a match of 47% between detected floods and flood archives. Individual tuning of thresholds per site should improve this result.
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Sébastien Delhay, Mahamadou Idrissa, & Vinciane Lacroix. (2005). PARADIS: GIS tools for humanitarian demining. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 213–219). Brussels: Royal Flemish Academy of Belgium.
Abstract: Landmines and UXO (UneXploded Ordnance1) represent a constant and long-lasting threat to the life of millions of individuals. Moreover, these weapons have a strong socio-economic impact on contaminated countries as they involve serious effects as the loss of agricultural fields or access to water. Demining is a critical issue since contaminated areas are large and their clearance often requires investing much time and money into it. It is then fundamental to manage demining activities in an efficient manner. PARADIS 2 is a tool dedicated to Mine Action and helps demining campaigns planners take rational decisions. It fits the needs of all campaign actors, as it is based on the tasks assigned to both the campaign planner and the field operator. The tool is built upon GIS technology and uses satellite imagery as a substitute for background maps, in order to represent all data involved in demining in their most explicit form: a map.
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Klaus Granica, Thomas Nagler, Markus M. Eisl, Mathias Schardt, & Helmut Rott. (2005). Satellite remote sensing data for an alpine related disaster management GIS. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 221–232). Brussels: Royal Flemish Academy of Belgium.
Abstract: Natural disasters are an age-old problem that occur regularly in alpine regions, posing a major threat to the safety of settlements and transport routes. Within the project “Safety of Alpine Routes – Application of Earth Observation Combined with GIS (Hannibal)”, financed by the Ministry of Transport and Innovation, information relevant for disaster management has been extracted from satellite remote sensing and integrated into a newly developed GIS based Decision Support System (DSS). Some of the required map information were inferred from ERS- or from SPOT5- and QUICKBIRD satellites, others were taken from conventional data sources such as maps or Digital Terrain Models.
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Muhammad Tauhidur Rahman, & Tarek Rashed. (2007). Towards a geospatial approach to post-disaster environmental impact assessment. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 219–226). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Natural disasters often leave profound impacts on the environment. Existing disaster impact assessment methods fall short in facilitating the relief work and in conducting cross-sectional comparison of various facets of such impacts. The development of a standardized index for measuring/monitoring the environmental impacts of disasters is necessary to address this gap. This paper proposes a conceptual framework to study the environmental impacts via remote sensing/GIS based geospatial analytical approach by developing a post-disaster environmental severity index. It considers physical, social and built-in components of the environment and identifies several key indicators of disaster impacts. Through statistical decomposition of a large number of environmental impact indicators, the study proposes a composite post-disaster environmental severity index (PDESI). Mapping of the proposed index would help identification of areas and component of the environment that are severely affected by a disaster, and formulation of disaster mitigation and damage recovery plans accordingly.
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Rob Grace, & Michelle Potts. (2022). Opportunities for Multisensor Integration in Public-Safety Answering Points. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 895–904). Tarbes, France.
Abstract: Public-Safety Answering Points (PSAPs) coordinate emergency response by gathering critical information from 911 callers for dispatch to first responders. However, PSAPs fail to gather this information if 911 callers are unable, unwilling, or unavailable to report key details about an emergency. To address this problem, early-adopter PSAPs employ communication specialists to gather multimedia information from multiple sensing tools, including automated alarms, cameras, government databases, location systems, open-source websites, social media, and alternative communication channels such as text-to-911. Using preliminary usage data from an early- adopter PSAP, this study identifies 11 breakdowns in 911 call taking that create opportunities for multisensor integration. This study then characterizes use cases for multisensor tools based on usage patterns observed across five incident types. These findings highlight multisensor integration as a critical area for crisis informatics research.
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Mohamad Rukieh. (2007). The effects of lineaments and epicentres on risk reduction in arabian rift zone. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 227–234). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper describes the relationship between lineaments, which determined on space images, and the epicenters and their effects on spatial planning for risk reduction. Several studies have shown that most of the epicenters occur along these lineaments or their zones, or in the block regions which are bordered by these lineaments, or where these lineaments and different tectonic deformation are intersected. This paper presents a case study on the Arabian Rift Zone which is based on the linkages among lineaments, faults, and earthquakes that occurred in the region during 1910-93. Also, this study will show that most of these earthquakes were occurred along the main and secondary rift faults or in their zone, including the faults found in sea that helped in determining the courses of these earthquakes in the sea bottom. This confirms the importance of remote sensing techniques for providing space images of different scales in seismic studies.
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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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