Flavio Horita, Ricardo Vilela, Renata Martins, Danielle Bressiani, Gilca Palma, & João Porto de Albuquerque. (2018). Determining flooded areas using crowd sensing data and weather radar precipitation: a case study in Brazil. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1040–1050). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Crowd sensing data (also known as crowdsourcing) are of great significance to support flood risk management. With the growing volume of available data in the past few years, researchers have used in situ sensor data to filter and prioritize volunteers' information. Nevertheless, stationary, in situ sensors are only capable of monitoring a limited region, and this could hamper proper decision-making. This study investigates the use of weather radar precipitation to support the processing of crowd sensing data with the goal of improving situation awareness in a disaster and early warnings (e.g., floods). Results from a case study carried out in the city of São Paulo, Brazil, demonstrate that weather radar data are able to validate flooded areas identified from clusters of crowd sensing data. In this manner, crowd sensing and weather radar data together can not only help engage citizens, but also generate high-quality data at finer spatial and temporal resolutions to improve the decision-making related to weather-related disaster events.
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Raul Eduardo Simoni Castanhari, Roberto dos Santos Rocha, Sidgley Camargo de Andrade, & João Porto de Albuquerque. (2016). A Software Architecture to Integrate Sensor Data and Volunteered Geographic Information for Flood Risk Management. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Natural disasters are phenomena that can cause great damage to people in urban and rural areas, and thus require preventive and reactive measures. If they involve multiple sources of information, these measures can be more useful and effective. However, the integration of heterogeneous data still poses challenges due to the differences in their structures and contents. To overcome this difficulty, this paper outlines a service-oriented architecture, as part of the AGORA platform, which aims to support the integration of sensor data and Volunteered Geographic Information (VGI) related to floods. The composition of the architectural components enables sensor data to be integrated with VGI by using several algorithms in a flexible and automated manner. The architecture was implemented by means of a prototype as a proof of concept and the results were used to generate thematic maps. These maps can improve flood risk awareness and support decision-making in flood risk management.
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André Simões, Armanda Rodrigues, Patricia Pires, & Luis Sá. (2011). Evaluating emergency scenarios using historic data: Flood management. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The evaluation of an emergency scenario is often based on the use of simulation models. The specificity of these models involves the need for a complex evaluation of the problem domain, including the physical conditions behind the considered threat. Based on emergency occurrences data, provided by the Portuguese National Civil Protection Authority, we are currently developing a methodology for evaluating a real situation, based on past occurrences. The aim is to develop a platform that will enable the evaluation of a risk scenario based on existing civil protection data. The methodology under development should enable the evaluation of different scenarios based on the collected available data. This will be achieved thanks to the facilitated configuration of several aspects, such as the geographical region and relevant properties of the considered threat. In this paper, we describe the methodology development process and the current state of the platform for risk evaluation.
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Alicia Cabañas Ibañez, Dirk Schwanenberg, Luis Garrote De Marcos, Miguel Francés Mahamud, & Javier Arbaizar González. (2011). An example of Flood Forecasting and Decision-Support System for water management in Spain. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The paper provides an overview of past, present and future development in the program to implement a Flood Forecasting and Decision-Support System (DSS) for the SAIH network in some Spanish basins. These tools represent a significant advance by embedding the decision-making components for management of hydraulic infrastructure into the flood forecasting and flood early warning procedures. The DSS has been implemented based on an open-shell platform for integrating various data sources and different simulation models. So far, it covers the Segura, Jucar, Tajo, Duero and Miño-Sil basins, which represent 42% of Spanish territory. Special attention is paid to the decision-support for the operation of the 66 major reservoirs as a fundamental part of flood management.
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Flávio E. A. Horita, Maria C. Fava, Eduardo M. Mendiondo, Jairo Rotava, Vladimir C. Souza, Jo Ueyama, et al. (2014). AGORA-GeoDash: A geosensor dashboard for real-time flood risk monitoring. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 304–313). University Park, PA: The Pennsylvania State University.
Abstract: Flood management is an important approach to reduce damage caused by floods. In this context, technological architectures which work in real-time are needed. However, Brazil has faced many structural difficulties in obtaining updated information on the current state of its rivers. To address this problem, this paper outlines a geosensor dashboard called AGORA-GeoDash, which processes data streams from wireless sensor networks and makes them available in the form of a set of performance indicators that are essential to support real-time decision-making in flood risk monitoring. The dashboard was built on open-source frameworks, made use of geoservices that comply with the standards of Open Geospatial Consortium, and established a Wireless Sensor Network which monitors the rivers of São Carlos/SP in Brazil. The analysis of the indicators available in two rainfall events revealed that the dashboard can provide the key information required for the decision-making process involved in flood risk management.
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