Supporting Natural Hazards Management With Geospatial Technologies

2019 ◽  
Author(s):  
Diana Mitsova
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Natural Hazards ◽  
Spatial Data ◽  
Disaster Response ◽  
Early Warning Systems ◽  
Unmanned Aircraft ◽  
Time Data ◽  
Geospatial Technologies ◽  
Collaborative Efforts

On a global scale, natural disasters continue to inflict a heavy toll on communities and to pose challenges that either persist or amplify in complexity and scale. There is a need for flexible and adaptive solutions that can bridge collaborative efforts among public agencies, private and nonprofit organizations, and communities. The ability to explore and analyze spatial data, solve problems, visualize, and communicate outcomes to support the collaborative efforts and decision-making processes of a broad range of stakeholders is critical in natural hazards and disaster management. The adoption of geospatial technologies has long been at the core of natural hazards risk assessment, linking existing technologies in GIS (geographic information system) with spatial analytical techniques and modeling. Practice and research have shown that though risk-reduction strategies and the mobilization of disaster-response resources depend on integrating governance into the process of building disaster resilience, the implementation of such strategies is best informed by accurate spatial data acquisition, fast processing, analysis, and integration with other informational resources. In recent years, new and accessible sources and types of data have greatly enhanced the ability of practitioners and researchers to develop approaches that support rapid and efficient disaster response, including forecasting, early warning systems, and damage assessments. Innovations in geospatial technologies, including remote sensing, real-time Web applications, and distributed Web-based GIS services, feature platforms for systematizing and sharing data, maps, applications, and analytics. Distributed GIS offers enormous opportunities to strengthen collaboration and improve communication and efficiency by enabling agencies and end users to connect and interact with remotely located information products, apps, and services. Newer developments in geospatial technologies include real-time data management and unmanned aircraft systems (UAS), which help organizations make rapid assessments and facilitate the decision-making process in disasters.

scholarly journals Adoption of Geospatial Systems towards evolving Sustainable Himalayan Mountain Development

2014 ◽  
Vol XL-8 ◽  
pp. 1319-1324 ◽  
Author(s):  
M. S. R. Murthy ◽  
B. Bajracharya ◽  
S. Pradhan ◽  
B. Shestra ◽  
R. Bajracharya ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Earth Observation ◽  
Time Data ◽  
Geospatial Technologies ◽  
Unique Region ◽  
Formidable Challenge ◽  
Himalayan Mountain ◽  
Mountain Development ◽  
The Way

Natural resources dependence of mountain communities, rapid social and developmental changes, disaster proneness and climate change are conceived as the critical factors regulating sustainable Himalayan mountain development. The Himalayan region posed by typical geographic settings, diverse physical and cultural diversity present a formidable challenge to collect and manage data, information and understands varied socio-ecological settings. Recent advances in earth observation, near real-time data, in-situ measurements and in combination of information and communication technology have transformed the way we collect, process, and generate information and how we use such information for societal benefits. <br><br> Glacier dynamics, land cover changes, disaster risk reduction systems, food security and ecosystem conservation are a few thematic areas where geospatial information and knowledge have significantly contributed to informed decision making systems over the region. The emergence and adoption of near-real time systems, unmanned aerial vehicles (UAV), board-scale citizen science (crowd-sourcing), mobile services and mapping, and cloud computing have paved the way towards developing automated environmental monitoring systems, enhanced scientific understanding of geophysical and biophysical processes, coupled management of socio-ecological systems and community based adaptation models tailored to mountain specific environment. <br><br> There are differentiated capacities among the ICIMOD regional member countries with regard to utilization of earth observation and geospatial technologies. The region can greatly benefit from a coordinated and collaborative approach to capture the opportunities offered by earth observation and geospatial technologies. The regional level data sharing, knowledge exchange, and Himalayan GEO supporting geospatial platforms, spatial data infrastructure, unique region specific satellite systems to address trans-boundary challenges would go a long way in evolving sustainable Himalayan livelihoods.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

scholarly journals Near real-time GPS applications for tsunami early warning systems

2010 ◽  
Vol 10 (2) ◽  
pp. 181-189 ◽  
Author(s):  
C. Falck ◽  
M. Ramatschi ◽  
C. Subarya ◽  
M. Bartsch ◽  
A. Merx ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Tide Gauge ◽  
Warning System ◽  
Early Warning Systems ◽  
Time Data ◽  
Essential Information ◽  
Tsunami Early Warning ◽  
Land Mass

Abstract. GPS (Global Positioning System) technology is widely used for positioning applications. Many of them have high requirements with respect to precision, reliability or fast product delivery, but usually not all at the same time as it is the case for early warning applications. The tasks for the GPS-based components within the GITEWS project (German Indonesian Tsunami Early Warning System, Rudloff et al., 2009) are to support the determination of sea levels (measured onshore and offshore) and to detect co-seismic land mass displacements with the lowest possible latency (design goal: first reliable results after 5 min). The completed system was designed to fulfil these tasks in near real-time, rather than for scientific research requirements. The obtained data products (movements of GPS antennas) are supporting the warning process in different ways. The measurements from GPS instruments on buoys allow the earliest possible detection or confirmation of tsunami waves on the ocean. Onshore GPS measurements are made collocated with tide gauges or seismological stations and give information about co-seismic land mass movements as recorded, e.g., during the great Sumatra-Andaman earthquake of 2004 (Subarya et al., 2006). This information is important to separate tsunami-caused sea height movements from apparent sea height changes at tide gauge locations (sensor station movement) and also as additional information about earthquakes' mechanisms, as this is an essential information to predict a tsunami (Sobolev et al., 2007). This article gives an end-to-end overview of the GITEWS GPS-component system, from the GPS sensors (GPS receiver with GPS antenna and auxiliary systems, either onshore or offshore) to the early warning centre displays. We describe how the GPS sensors have been installed, how they are operated and the methods used to collect, transfer and process the GPS data in near real-time. This includes the sensor system design, the communication system layout with real-time data streaming, the data processing strategy and the final products of the GPS-based early warning system components.

scholarly journals SPATIAL DATA INTEGRATION USING ONTOLOGY-BASED APPROACH

2015 ◽  
Vol XL-1-W5 ◽  
pp. 293-296 ◽  
Author(s):  
S. Hasani ◽  
A. Sadeghi-Niaraki ◽  
M. Jelokhani-Niaraki
Keyword(s):  
Data Integration ◽  
Real Time ◽  
Spatial Data ◽  
Service Oriented Architecture ◽  
Low Cost ◽  
Time Integration ◽  
Semantic Heterogeneity ◽  
Sources Of Information ◽  
Time Data ◽  
Service Oriented

In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.

scholarly journals Real-Time Data Processing

2021 ◽  
pp. 147-156
Author(s):  
Fabiana Fournier ◽  
Inna Skarbovsky
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Processing System ◽  
Event Processing ◽  
Time Data ◽  
System Architectures ◽  
Real Time Processing ◽  
Operational Decision Making ◽  
Real Time Data Processing ◽  
High Level

AbstractTo remain competitive, organizations are increasingly taking advantage of the high volumes of data produced in real time for actionable insights and operational decision-making. In this chapter, we present basic concepts in real-time analytics, their importance in today’s organizations, and their applicability to the bioeconomy domains investigated in the DataBio project. We begin by introducing key terminology for event processing, and motivation for the growing use of event processing systems, followed by a market analysis synopsis. Thereafter, we provide a high-level overview of event processing system architectures, with its main characteristics and components, followed by a survey of some of the most prominent commercial and open source tools. We then describe how we applied this technology in two of the DataBio project domains: agriculture and fishery. The devised generic pipeline for IoT data real-time processing and decision-making was successfully applied to three pilots in the project from the agriculture and fishery domains. This event processing pipeline can be generalized to any use case in which data is collected from IoT sensors and analyzed in real-time to provide real-time alerts for operational decision-making.

scholarly journals Still normal? Contextualizing real-time data with long-term statistics to monitor anomalies and systematic changes in storm surge activity – Introduction of a prototype web tool storm surge monitor for the German coasts

2021 ◽  
Author(s):  
Xin Liu ◽  
Insa Meinke ◽  
Ralf Weisse
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Storm Surge ◽  
Storm Surges ◽  
Added Value ◽  
Time Data ◽  
Storm Activity ◽  
The Public ◽  
Real Time Data

Abstract. Storm surges represent a major threat to many low-lying coastal areas in the world. While most places can cope with or are more or less adapted to present-day risks, future risks may increase from factors such as sea level rise, subsidence, or changes in storm activity. This may require further or alternative adaptation and strategies. For most places, both forecasts and real-time observations are available. However, analyses of long-term changes or recent severe extremes that are important for decision-making are usually only available sporadically or with substantial delay. In this paper, we propose to contextualize real-time data with long-term statistics to make such information publicly available in near real-time. We implement and demonstrate the concept of a ”storm surge monitor” for tide gauges along the German North Sea and Baltic Sea coasts. It provides automated near real-time assessments of the course and severity of the ongoing storm surge season and its single events. The assessment is provided in terms of storm surge height, frequency, duration, and intensity. It is proposed that such near real-time assessments provide added value to the public and decision-making. It is further suggested that the concept is transferable to other coastal regions threatened by storm surges.

Integration of operational Multi-Hazard Early Warning Systems and COVID-19 data for the humanitarian community

2021 ◽  
Author(s):  
Chiara Proietti ◽  
Alessandro Annunziato ◽  
Pamela Probst ◽  
Stefano Paris ◽  
Thomas Peter
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Forest Fires ◽  
Large Scale ◽  
Warning System ◽  
Early Warning Systems ◽  
Research Centre ◽  
Time Data ◽  
Joint Research ◽  
Coordination System

&lt;p&gt;To improve preparedness and response in case of large-scale disasters, the international humanitarian community needs to understand the anticipated impact of an event as soon as possible in order to take informed operational decisions. The European Commission&amp;#8217;s Joint Research Centre (JRC), DG ECHO, and the United Nations&amp;#8217; OCHA and UNOSAT launched the Global Disaster Alert and Coordination System (www.GDACS.org) in 2002-03 as cooperation platform to provide early disaster warning and coordination services to humanitarian actors. After more than 15 years, GDACS has around 30k registered users among humanitarian organisations at global level.&lt;/p&gt;&lt;p&gt;At the beginning, one of GDACS&amp;#8217;s main tasks was the dissemination of automatic alerts for earthquakes, tsunamis and tropical cyclones; today, the system has been augmented to include also floods, droughts and volcanoes, and it will soon include forest fires. &amp;#160;Alerts are sent to the international humanitarian community to ensure timely warning in severe events that are expected to require international assistance. Alert levels are determined by automated algorithms without, or with very limited, human intervention, using automatic real-time data-feeds from various scientific institutes or the JRC&amp;#8217;s own systems.&lt;/p&gt;&lt;p&gt;From 2020, because of the potential impact of the COVID-19 emergency on international preparedness and response activities, the COVID-19 situation in affected countries is now also monitored by the system, providing real time information updates on the website. This new feature allows to consider in the planning of the emergency response, the severity of the outbreak in the affected countries.&lt;/p&gt;&lt;p&gt;This contribution presents the challenges and outcomes of combining science-based information from different independent systems into a single Multi-Hazard Early Warning System and introduces new functionalities that were recently developed to address the new challenges related to the COVID-19 emergency.&lt;/p&gt;

IoT-based system for communication and coordination of football robot team

2017 ◽  
Vol 27 (2) ◽  
pp. 162-181 ◽  
Author(s):  
Zhuming Bi ◽  
Guoping Wang ◽  
Li Da Xu ◽  
Matt Thompson ◽  
Raihan Mir ◽  
...  
Keyword(s):  
Decision Making ◽  
Information System ◽  
Sensor Networks ◽  
Real Time ◽  
System Level ◽  
Time Data ◽  
Content Type ◽  
Iot Applications ◽  
Real Time Data ◽  
Communication And Coordination

Purpose The purpose of this paper is to develop an information system which is based on the Internet of things (IoT) and used to support the communication and coordination in a cooperative robot team. Design/methodology/approach The architecture of the IoT applications for decision-making activities in a complex system is elaborated, the focus lies on the effective implementation of system interactions at the device-level. A case study is provided to verify system performances. Findings The IoT concept has been introduced in an information system of a football robot team to support the coordination among team players. Various sensors are used to collect data from IoT, and data are processed for the controls of robotic players to achieve the better performance at the system level. The field test has shown the feasibility and effectiveness. Research limitations/implications To investigate how IoT can be utilized in an information system for making complex decisions effectively, the authors use the decision-support system for a football robot team to illustrate the approaches in developing data acquisition infrastructure, processing and utilizing real-time data for the communication and coordination of robot players in a dynamic competing environment. While the presented work has shown the feasibility of an IoT-based information system, more work are needed to integrate advanced sensors within the IoT and develop more intelligent algorithms to replace manually remote control for the operations of robot players. Practical implications The proposed system is specifically for a football robot team; however, the associated approaches are applicable to any decentralized system for developing an information system to support IoT-based communication and coordination within the system in the real-time mode. Originality/value The exploration of IoT applications is still at its early stage, existing relevant work is mostly limited to the development of system architecture, sensor networks, and communication protocols. In this paper, the methods on how to use massive real-time data for decision-making of a decentralized team have been investigated, and the proposed system has its theoretical significance to developing other decentralized wireless sensor networks and decision-making systems.

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