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Towards using Volunteered Geographic Information to monitor post-disaster recovery in tourist destinations

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... Today, however, a variety of geographical features are constantly added to OSM's database, including buildings and their functionality, land use and public transportation information [15]. This data allows local governments and communities to better perform risk assessment and emergency planning [16][17][18] and is routinely utilized for various disaster risk management applications [19,20]. As of today, there are more than 5.5 million OSM users and one million contributors who generate more than 3 million changes every day. ...
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Over the last few decades, many countries, especially islands in the Caribbean, have been challenged by the devastating consequences of natural disasters, which pose a significant threat to human health and safety. Timely information related to the distribution of vulnerable population and critical infrastructure is key for effective disaster relief. OpenStreetMap (OSM) has repeatedly been shown to be highly suitable for disaster mapping and management. However, large portions of the world, including countries exposed to natural disasters, remain incompletely mapped. In this study, we propose a methodology that relies on remotely sensed measurements (e.g., Visible Infrared Imaging Radiometer Suite (VIIRS), Sentinel-2 and Sentinel-1) and derived classification schemes (e.g., forest and built-up land cover) to predict the completeness of OSM building footprints in three small island states (Haiti, Dominica and St. Lucia). We find that the combinatorial effects of these predictors explain up to 94% of the variation of the completeness of OSM building footprints. Our study extends the existing literature by demonstrating how remotely sensed measurements could be leveraged to evaluate the completeness of the OSM database, especially in countries with high risk of natural disasters. Identifying areas that lack coverage of OSM features could help prioritize mapping efforts, especially in areas vulnerable to natural hazards and where current data gaps pose an obstacle to timely and evidence-based disaster risk management.
... Today, a variety of geographical features, including buildings and their functionality, land use and public transportation information are constantly added to OSM [16]. Such data allows local governments and communities to better perform risk assessment and emergency planning [17] [18] [19] and is routinely utilized for various disaster risk management applications [20] [21]. As of today, there are more than 5.5 million OSM users and one million contributors who generate more than 3 million changes every day, as well as specialized groups such as Humanitarian OpenStreetMap Team (HOT-OSM) that conduct activities aimed at enriching OSM data to support emergency relief operations i . ...
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Over the last few decades, many countries, especially Caribbean island ones, have been challenged by the devastating consequences of natural disasters, which pose a significant threat to human health and safety. Timely information related to the distribution of vulnerable population and critical infrastructure are key for an effective disaster relief. OpenStreetMap (OSM) has repeatedly been shown to be highly suitable for disaster mapping and management. However, large portions of the world, including countries exposed to natural disasters, remain unmapped. In this study, we propose a methodology that relies on remotely sensed measurements (e.g. VIIRS, Sentinel-2 and Sentinel-1) and derived classification schemes (e.g. forest and built-up land cover) to predict the completeness of OSM building footprints in three small island states (Haiti, Dominica and St. Lucia). We find that the combinatorial effects of these predictors explain up to 94% of the variation of the completeness of OSM building footprints. Our study extends the existing literature by demonstrating how remotely sensed measurements could be leveraged to evaluate the completeness of OSM database, especially in countries at high risk of natural disasters. Identifying areas that lack coverage of OSM features could help prioritize mapping efforts, especially in areas vulnerable to natural hazards and where current data gaps pose an obstacle to timely and evidence-based disaster risk management actions.
... Over the last couple of years, OSM data repeatedly proved its potential for disaster applications, in the disaster response as well as the other phases of the disaster cycle (Palen et al. 2015;Dittus et al. 2016b;Eckle et al. 2017). The mapping activations that are supported by many volunteers with various levels of experience oftentimes raise questions related to the quality of the provided Volunteered Geographic Information (VGI). ...
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Over the last couple of years, the growing OpenStreetMap (OSM) database repeatedly proved its potential for various use cases, including disaster management. Disaster mapping activations show increasing numbers of contributions, but oftentimes raise questions related to the quality of the provided Volunteered Geographic Information. In order to better monitor and understand OSM mapping and data quality, we developed the ohsome software platform that applies big data technology to OSM full history data. OSM full history data monitoring allows detailed analyses of the OSM data evolution and the detection of remarkable patterns over time. This paper illustrates the specific potential of our platform for disaster activations by means of two case studies. Initial results demonstrate that our flexible and scalable platform structure enables fast and easy information extraction and supports mapping processes and data quality assurance.
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Natural hazards have the potential to cause catastrophic damage and significant socioeconomic loss. The actual damage and loss observed in the recent decades has shown an increasing trend. As a result, disaster managers need to take a growing responsibility to proactively protect their communities by developing efficient management strategies. A number of research studies apply artificial intelligence (AI) techniques to process disaster-related data for supporting informed disaster management. This study provides an overview of current applications of AI in disaster management during its four phases: mitigation, preparedness, response, and recovery. It presents example applications of different AI techniques and their benefits for supporting disaster management at different phases, as well as some practical AI-based decision support tools. We find that the majority of AI applications focus on the disaster response phase. This study also identifies challenges to inspire the professional community to advance AI techniques for addressing them in future research.
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Offene Lösungen gewinnen in der Geoinformationswirtschaft seit geraumer Zeit an Bedeutung. Mittlerweile sind gut nutzbare und stabile Open Source Bibliotheken und Werkzeuge für die Verarbeitung, Management und Visualisierung räumlicher Daten verfügbar. Neben dem Trend zu Open Source stellt das Thema Interoperabilität durch offene Schnittstellen, wie sie durch das Open Geospatial Consortium (OGC) spezifiziert werden, ebenfalls ein Dauerthema dar. Auch die Kombination dieser beiden Aspekte von „Offen“ durch Open Source Frameworks wie deegree, 52°North oder GeoTools/JTS etc. stellt als Konsequenz eine lange wohlbekannte Entwicklung dar. Diese Bibliotheken bieten Implementierungen der gebräuchlichen OGC Service Spezifikationen. Mit unserer Initiative zur Implementierung einer weiteren Familie von OGC-Spezifikationen wird eine Lücke geschlossen. Hierbei handelt es sich um die im Rahmen der OGC Open Location Services (OpenLS) Spezifikation definierten Dienste (vgl. Neis 2007, Zipf 2005). Neben der bekannten Implementierung des Route Service (Neis et al. 2007), sind mittlerweile eine Reihe der hier definierten Dienste umgesetzt worden. Hierzu zählt der OpenLS Presentation Service, der OpenLS Location Utility Service (GeoCoder/Reverse GeoCoder), sowie (zur Zeit noch nicht vollständig) der OpenLS Directory Service. Außerdem wird auch der im Winter 2007 neu definierte OpenLS Tracking Service implementiert werden. Eine weitere Idee für einen Dienst im Rahmen der OpenLS Initiative - der “Navigation Service” – wurde zwar schon 2000 andiskutiert, aber blieb bisher ein Entwurf. Nachdem nun vor kurzem die Version 1.2 der OpenLS Spezifikation herausgekommen ist, soll dieser Navigation Service nun im Rahmen der Spezifikation der Version 1.3 der OpenLS Spezifikationen hinzukommen. Dieser Dienst wird im Rahmen des Projektes MoNa3D (Mobile Navigation mit 3D-Stadtmodellen) (Coors & Zipf 2007) eine zentrale Rolle spielen und hierbei voraussichtlich implementiert werden. Ein Teil dieser Service-Implementierungen soll nun in absehbarer Zukunft als neues Open Source Project unter www.freeOpenLS.org der GI- Community zur Verfügung gestellt werden.