Explicit Modeling and Visualization of Imperfect Information in the Context of Decision Support for Tsunami Early Warning in Indonesia

A certainty model and appropriate visualization techniques are presented which are applied in a newly developed Decision Support System (DSS) for tsunami early warning deployed in Jakarta, Indonesia. Our decision support approach makes use of multi-sensor fusion and pre-computed tsunami scenario simulations to create situational awareness as basis for reasonable early warning. As the Indonesian coastline is prone to near-field tsunami scenarios decision making must take place under time-critical conditions based on incomplete and uncertain information. In order to reduce the probability and the consequences of a false decision, we have developed and employed a certainty model which implies a classification of imperfect information suitable for the tsunami early warning domain and the quantification of imperfect data. The model is mapped onto and supported by appropriate visual representations

The Decision Support System for improved Tsunami Early Warning in Indonesia: Approach and Implementation

In recent years numerous tsunami events in the Indian Ocean have shown how vulnerable human society and the environment is to this sudden-onset type of disaster. Especially the December 2004 tsunami demonstrated the need for an effective tsunami early warning system for the Indian Ocean. The German-Indonesian Early Warning System (GITEWS) project uses the best sensor technologies available today to detect indicators or evidence for a tsunami, combining those information with up-to-date modelling techniques and integrating them in a newly developed Decision Support System. Combining a-priori knowledge, simulation runs and analysis results with real-time information from different types of sensors, the newly developed Decision Support System (DSS) serve as a back-bone to allow an assessment for the tsunami threat at the earliest time possible and support the decision maker whether to issue a tsunami warning or not. GITEWS therefore adds additional components in order to achieve the best situation awareness possible by compiling a huge scenario-based repository of a-priori knowledge: A tsunami simulation system generates a large number of pre-calculated tsunami scenarios; in case of a potential tsunami, sensor observations can be compared and matched with these scenarios in order to find the most likely tsunami scenario descriptions, and a risk and vulnerability analysis component that helps to assess probable consequences and impacts on coastal communities exposed to tsunamis. Once the decision to disseminate a warning has been made, the DSS is able to generate regionalized warning messages, which are then transmitted to different dissemination systems using the standardized Common Alerting Protocol (CAP)

Decision Support Interface for Tsunami Early Warning in Indonesia - Dealing with Information Fusion, Uncertainty, and Time Pressure

In recent years numerous tsunami events in the Indian Ocean, most prominent the December 2004 disaster, demonstrated the need for an effective tsunami early warning system. The work presented here is embedded in the German-Indonesian Tsunami Early Warning System (GITEWS) project. The system combines a variety of sensor technologies such as terrestrial observation networks of seismology and geodesy, marine measuring sensors, satellite technologies, and pre-calculated simulation scenarios. The versatile sensor and simulation data is integrated, processed, and assessed by the newly developed Decision Support System (DSS). The DSS aims at the best possible situation awareness and decision-making of the operator to enable him to disseminate an appropriate warning at the earliest point in time if required. For this purpose, we attach great importance to the DSS user interface. Due to a high degree of initial uncertainty, operation under time pressure, and the challenge of combining a considerable amount of data to a global picture following regular user interface design guidelines is not sufficient. In this work the main principles of situation awareness design are examined and mapped onto design decisions, work in progress, and future prospects

Concepts and applications of spatiotemporal interoperability in environmental and emergency management

Abstract: Interoperability of Systems and Services is gaining importance, but is mostly limited to a specific domain, e.g. the geospatial or modeling & simulation (M&S) domains. Spatiotemporal Interoperability describes an approach to exploit the synergies of coupling OGC-compliant services and HLA-based simulations in a standardized manner. The paper describes the current status of the Distributed spAtiotemporaL Interoperability Architecture (DALI), potential aplications as well as two prototypes in the area of Environmental and Emergency Management

Understanding end-user needs for an efficient multi-hazard emergency management service platform design

There is a higher concentration and impact of natural and man-made disasters which have a similar course but are nevertheless different. Current disaster management systems focus on single crisis and have the drawback that they cannot be flexibly adapted to the respective situation. The presented approach developed during the PHAROS project is to provide an integrated platform which offers tools for multi-hazard emergency management during the complete emergency management cycle. The system has a modular structure which is flexible and scalable. PHAROS assets include:(i) data collecting, processing tools, (ii) communication and alerting means, (iii) disaster prediction and assessment, (iv) decision support. We present in addition to the system description the PHAROS pilot demonstration used to evaluate the system. For this evaluation the system was adapted during the project for the forest fire case and tested in Solsona, Spain in March 2016 during a real operational prescribed burn

The Integration of an Operational Fire Hot Spots Processing Chain in a Multi-Hazard Emergency Management Service Platform (PHAROS)

The project PHAROS (Project on a Multi-Hazard Open Platform for Satellite Based Downstream Services) designs and implements a multi-hazard open service platform which integrates space-based earth observation, satellite communications and navigation (Galileo/GNSS) assets to provide sustainable (pre-operational) services for a wide variety of users in multi-application domains, such as prediction/early detection of emergencies, population alerting, environmental monitoring and crisis management. While the service platform is designed to be multi-hazard, the specific developments for the pre-operational system and pilot demonstration will be focused on the forest fire scenario. The platform will integrate data from EO satellites and in-situ sensors process it and provide the results to a series of key services for disaster management in its different phases. One of the main concerns is to provide fire hot spots as an input for the PHAROS Simulation Service. These fire hot spots (thermal anomalies) are derived automatically and in near real time (NRT) from MODIS data. The MODIS data are available in a high (1d) temporal and in a medium (250m – 1000m) spatial resolution. For the detection of high temperature events (HTE) the MOD14 algorithm is used. The algorithm is based on the shift of the radiances/reflectance to shorter wavelengths (middle infrared) with an increasing surface temperature. MOD14 is well documented and tested in operational services and guarantees comparability and reproducibility as well as a standardized international acknowledged product. The thermal information is collected at 1000 m spatial resolution twice daily by each sensor (Terra and Aqua) providing up to four thermal observations daily. The MODIS images used for fire detection are acquired from two direct broadcast receiving stations from DLR located in Oberpfaffenhofen and Neustrelitz (Germany). This Poster will give an overview of the processing chain from the reception, the processing and derivation of the fire hot spots to the dissemination in the Pharos system

A Newly Developed Decision Support System for Improved Tsunami Early Warning in Indonesia

As part of the German contribution to the Indonesian Tsunami Early Warning System InaTEWS, an innovative Decision Support System (DSS) has been developed in order to support the tsunami early warning process in an unique way. The paper describes the modular and open environment in which the DSS operates in, its main tasks and components, the Graphical User Interface (GUI) and the focus on standardization and interoperability which led the design and development of the DSS