Abstract: Understanding that disasters and conflicts do not occur in a vacuum, but are integrally linked to the broader context in which they take place, building resilience within both state and society structures becomes a crucial tool to speed recovery and lessen the likelihood of recurrence as local and institutional capacities are put in place to respond to, manage and reduce emerging risks. Since, 2008, United Nations Development Programme in Sudan has through its Crisis and Recovery Mapping and Analysis Project been developing a participatory mapping and analysis methodology to enhance crisis responsiveness and evidence-based strategic planning both within the United Nations system and national government. Using innovative technologies and GIS, sensitive issues are contextualized and depoliticized through novel correlations and visualisations, allowing previously contesting state and society actors to jointly identify priorities for intervention and response. The process has fostered an open dialogue, strengthening the capacities of local actors to respond to emerging crises in a timely and appropriate manner. Participatory mapping has thus become a key tool in managing complexities in peacebuilding and recovery in post-crisis settings. © 2012 ISCRAM.

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.

Abstract: Emergency situations often play out over extended geographic regions and can present response personnel with numerous types of data at various level of detail. Such data may be displayed in mapping software tools that organize the data into layers. Sufficiently complex scenarios can result in dense, occluded, and cluttered map displays. We investigated a localized, detail-on-demand filtering strategy called semantic lensing that in certain situations provides a more efficient and desirable approach than filtering global layers for mitigating clutter and occlusion. An initial formal user study with these semantic lenses has shown their value in aiding decision makers during tasks that might occur during detection of and response to emergency situations. Completion times are significantly faster when using lenses, and workloads are significantly lower. Future work will evaluate additional features and task-specific applicability, and may support the distribution of such a lens tool to emergency preparedness and response personnel.

Abstract: This practitioner report describes a recent example of the growing opportunities between humanitarian health organizations and the crisis mapping community. The World Health Organization (WHO) partnered with volunteer crisis mappers to quickly collect information and map over 600 health facilities after the 2011 Libya Crisis. This new collaboration between WHO staff, volunteers, technologists, GIS specialists, health cluster partners and a researcher helped provide health and geographic information to support the planning phases of an in-depth countrywide health facility assessment. Outcomes of this collaboration will also aid recovery and reconstructions efforts for the Libyan health system. © 2012 ISCRAM.

Abstract: Recent advances in the Unmanned Aerial Vehicles (UAVs) sector have allowed such systems to carry a range of sensors, thus increasing their versatility and adaptability to a wider range of tasks and services. Furthermore, the agility of these vehicles allows them to adapt to rapidly changing environments making them an effective tool for emergency situations. A single UAV, or a swarm working in collaboration, can be a handy and helpful tool for First Responders (FRs) during mission planning, mission monitoring, and the tracking of evolving risks. UAVs, with their on-board sensors, can, among other things, capture visual information of the disaster scene in a safe and quick manner, and generate an up-to-date map of the area. This work presents a system for UAV-assisted mapping optimized for FRs, including the generation of routes for the UAVs to follow, data collection and processing, and map generation.

Abstract: Social media serves as an important communication channel for people affected by crises, creating a data source for emergency responders wanting to improve situational awareness. In particular, social listening on Twitter has been widely used for real-time analysis of crisis-related messages. This approach, however, is often hindered by the small fraction of (hyper-)localized content and by the inability to explicitly ask affected populations about aspects with the most operational value. Here, we explore a new form of social media data collected through targeted poll ads on Facebook. Using geo-targeted ads during flood events in six countries, we show that it is possible to collect thousands of poll responses within hours of launching the ad campaign, and at a cost of a few (US dollar) cents per response. We believe that this flexible, fast, and affordable data collection can serve as a valuable complement to existing approaches.

Abstract: Floods are one of the major natural hazards in terms of affected people and economic damages. The increasing and often uncontrolled urban sprawl together with climate change effects will make future floods more frequent and impacting. An accurate flood mapping is of paramount importance in order to update hazard and risk maps and to plan prevention measures. In this paper, we propose the use of a supervised machine learning approach for flood delineation from satellite data. We train and evaluate the proposed algorithm using Sentinel-1 acquisition and certified flood delineation maps produced by the Copernicus Emergency Management Service across different geographical regions in Europe, achieving increased performances against previously proposed supervised machine learning approaches for flood mapping.

Abstract: Globally floods are categorized as one of most devastating natural disasters and annually causing a major loss to human lives and economy. For rapid damage assessment and planning relief activities a large scale spatio-temporal overview is required to assist local authorities. This paper aims to provide an overview of a Sentinel-1 based near-real time flood mapping/monitoring service; which is implemented as an operational service under the framework of I-REACT (Improving Resilience to Emergencies through Advanced Cyber Technologies) project.

Abstract: This paper examines the relationship between collaborative disaster mapping and conceptions of risk. It looks at improvised mapmaking during the 2007 wildfires in Southern California to identify and analyze social and technological issues in creating a shared understanding through collaboration. By comparing and contrasting two different, yet intertwined, mapping practices this paper focuses on how the distribution of social and technological actors change how risk, threat, and uncertainty are approached. One, more centralized mapmaking collaboration produced risks related to managing authority and security. The other, more distributed collaboration, produced risks related to public trust and safety. This paper argues that map-making is characterized as a messy, distributed network of knowledge production in which the meaning of risk emerges through the unplanned collaborations that evolve as those involved work to make sense of the wildfires, not as an a-priori definition.

Abstract: Over the last couple of years Volunteered Geographic Information (VGI) and particularly OpenStreetMap (OSM) have emerged as an important additional source of information in disaster management. The so-called OSM Crisis Maps are primarily developed by OSM contributors who work remotely. While local OSM contributors know their area of interest and rely upon local knowledge, often the sole basis for the remote mapping is satellite imagery. This fact may raise doubts about the quality of the Crisis Maps. This study introduces an experimental approach to assess the data quality that remote mappers produce. In an experimental setting, data sets produced by a group of remote mappers are evaluated by comparing them to data sets created by a selected expert mapper with local knowledge. The presented approach proved to be useful for assessing data quality of remote mapping and can be used to support decisions about the suitability of crowdsourced geographic data.

Abstract: After a natural disaster or other crisis, humanitarian organizations need to know where affected people are located
and what resources they need. While this information is difficult to capture quickly through conventional methods,
aggregate usage patterns of social media apps like Facebook can help fill these information gaps.
In this paper, we describe the data and methodology that power Facebook Disaster Maps. These maps utilize
information about Facebook usage in areas impacted by natural hazards, producing aggregate pictures of how the
population is affected by and responding to the hazard. The maps include insights into evacuations, cell network
connectivity, access to electricity, and long-term displacement.
In addition to descriptions and examples of each map type, we describe the source data used to generate the maps,
and efforts taken to ensure the security and privacy of Facebook users. We also describe limitations of the current
methodologies and opportunities for improvement.

Abstract: A wide range of local, regional, and federal authorities will generate maps to help respond to and recover from a disaster. It is essential that map users in an emergency situation can readily understand what they are seeing on these maps. Standardizing map symbology is one mechanism for ensuring that geospatial information is interpretable during an emergency situation, but creating an effective map symbol standard is a complex and evolving task. Here we present preliminary results from research into the application of the ANSI 415-2006 INCITS Homeland Security Map Symbol Standard, a point symbol standard intended to support emergency management mapping for the U.S. Department of Homeland Security. This standard has so far not been widely adopted across the full range of DHS missions, and we elaborate on key issues and challenges that should be accounted for when developing future map symbol standards for crisis management.

Abstract: The use of social media to support emergency operators in the first hours of the response phases can improve the
quality of the information available and awareness on ongoing emergency events. Social media contain both textual
and visual information, in the form of pictures and videos. The problem related to the use of social media posts
as a source of information during emergencies lies in the difficulty of selecting the relevant information among
a very large amount of irrelevant information. In particular, we focus on the extraction of images relevant to an
event for rapid mapping purpose. In this paper, a set of possible filters is proposed and analyzed with the goal of
selecting useful images from posts and of evaluating how precision and recall are impacted. Filtering techniques,
which include both automated and crowdsourced steps, have the goal of providing better quality posts and easy
manageable data volumes both to emergency responders and rapid mapping operators. The impact of the filters on
precision and recall in extracting relevant images is discussed in the paper in two different case studies.