Track 5: Geospatial Data and Geographical Information Science
Spatiotemporal Distribution of Automobile Users: Estimation Method and Applications to Disaster Mitigation Planning
When discussing human casualties from a severe earthquake with regard to urban disaster mitigation planning, it is important to clarify the characteristics of the spatiotemporal distribution of people. In this paper, we construct a model that estimates the spatiotemporal distribution of automobile users using data from the Person Trip Survey and the Road Traffic Census. We use this model to estimate the spatiotemporal distribution of automobile users in Tokyo and demonstrate several ways to apply this data to urban disaster mitigation planning.
This paper describes how enthusiasts from the radio-amateur and red-cross communities developed and applied position tracking to search and rescue services in Norway. This was based on the APRS standard which has been used by radio-amateurs for some time.
The document describes how radio-amateurs designed a tracking device which was robust and simple to use along with a web-based online service, a map server, to display positions along with other geographical information on electronic maps. The software for the tracker and the map server is free and open source. This system has been used in a number of search and rescue missions in Norway since 2009, to support decisions making in the command and control centre.
Samuel Lee Toepke, R. Scott Starsman
In the event of a disaster, high resolution knowledge of expected population distribution is a boon to the situational awareness of disaster managers and first responders. Knowing the expected locations of large throngs of people can greatly affect distribution of aid and response infrastructure. Effective dissemination of this information can be realized by using a myriad of readily available technologies.
With the modern proliferation of smart phones, pervasive Internet and freely available social media applications, population distribution can be estimated from the constant aggregation of crowd sourced data. Twitter and Instagram both publish geolocated data, which is then processed by a cloud-based, enterprise application to generate heat maps. The heat maps are then shown in a real-time geographic information system that is visible to any mobile device with a web browser.
Alexander Almer, Thomas Schnabel, Johann Raggam, Armin Köfler, Roland Wack, Richard Feischl
This paper describes the development of a multi-functional airborne management support system within the frame of the Austrian national safety and security research programme. The objective was to assist crisis management tasks of emergency teams and armed forces in disaster management by providing multi spectral, near real-time airborne image data products. As time, flexibility and reliability as well as objective information are crucial aspects in emergency management, the used components are tailored to meet these requirements. This article includes the individual system components as well as their performance using examples from lab tests and real-life deployments. Based on this, the impact of existing command and control processes as well as the benefits for time critical decision making processes are described based on expertise of the involved end users. In addition, it gives an outlook on future perspectives.
Development of a Geographic Information System for Riverine Flood Disaster Evacuation in Canberra, Australia: Trip Generation and Distribution Modelling
Ahmed T. Elsergany, Amy L. Griffin, Paul Tranter, Sameer Alam
Given the importance of geographic information for riverine flood evacuations, a geographic information system (GIS) is a vital tool for supporting successful flood evacuation operations. This paper discusses the development of a GIS-based riverine flood evacuation model which used to model trip distributions between flooded areas and relocation shelters. As the ultimate goal of this research is to simulate, model, and optimise a planned evacuation, all components of evacuation time have been considered (e.g., travel time between flooded areas and relocation shelters, warning time for each flooded area, and the time needed for evacuation before these areas get inundated). As well, variation in population (static and dynamic population) within the flooded areas has been considered.
Petra Füreder, Stefan Lang, Michael Hagenlocher, Dirk Tiede, Lorenz Wendt, Edith Rogenhofer
Critical information on refugee/internally displaced people (IDP) camps can be provided to humanitarian organisations to support planning of emergency response and relief using multi-temporal and multi-scale information from satellite imagery and GIS data. Since 2011 we are providing Earth observation-based information services to Médecins Sans Frontières (MSF) on demand. A service on population monitoring has already reached an operational stage. Thereby indicators on population are derived by automated dwelling extraction from (multi-temporal) very high resolution (VHR) satellite imagery. Based on such information, further added-value products are provided to analyse internal camp structure or camp evolution. Two additional services to support groundwater extraction and assess the impact of the camps on the environment are currently under development. So far twenty-five sites in nine countries have been analysed and more than a hundred maps were provided to MSF and other humanitarian organisations.
Ikki Niwa, Toshihiro Osaragi, Takuya Oki, Noriaki Hirokawa
In a large earthquake, rescue operations and fire-fighting are obstructed by fire-spreading and street-blockages. Therefore, it is important to quickly collect and utilize disaster information for disaster mitigation. In this paper, firstly, we develop a Web application for posting and viewing information collected by users in real time. Using this system, it is possible not only to easily share disaster information among users but also to apply to damage forecast such as fire-spreading. Next, we demonstrate the usefulness of the Web application by the following evaluation view points: (1) relationship between the access time of emergency vehicles from fire stations to the locations of fires and the ratio of collected information on street-blockage which is assumed to be collected with this system; (2) reciprocating time between a server and a client which is dependent on the number of users and band limitation after the occurrence of a disaster.
Modeling Day- and Nighttime Population Exposure at High Resolution: Application to Volcanic Risk Assessment in Campi Flegrei
Sérgio Freire, Aneta Florczyk, Stefano Ferri
Improving analyses of population exposure to potential natural hazards, especially sudden ones, requires more detailed geodemographic data. Availability of such information for large areas is limited by specific database requirements and their cost.
This paper introduces and tests a new approach for refining spatio-temporal population distribution at high resolution by combining diverse geoinformation layers. Its value is demonstrated in the context of disaster risk analysis and emergency management by using the data in a real volcanic risk scenario in Campi Flegrei, located within the metropolitan area of Naples, Italy. Results show that there is significant variation in exposure from nighttime to daytime in the study area.
The proposed modeling approach can be applied and customized for other metropolitan areas, ultimately benefiting disaster risk assessment and mitigation.
Melanie Eckle, João Porto de Albuquerque
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.