327 research outputs found
Volcanic Risk System (SRV): ASI Pilot Project to Support The Monitoring of Volcanic Risk In Italy by Means of EO Data
The ASI-SRV(Sistema Rischio Vulcanico) project
started at the beginning of the 2007 is funded by the Italian
Space Agency (ASI) in the frame of the National Space Plan
2003-2005 under the Earth Observations section for natural
risks management. Coordinated by the Istituto Nazionale di
Geofisica e Vulcanologia (INGV), which is responsible at national
level for the volcanic monitoring, the project has as main
objective to develop a pre-operative system based on EO data
and ground measurements integration to support the volcanic
risk monitoring of the Italian Civil Protection Department. The
project philosophy is to implement specific modules which allow
to process, store and visualize through Web GIS tools EO derived
parameters considering three activity phases: 1) knowledge and
prevention; 2) crisis; 3) post crisis. In order to combine
effectively the EO data and the ground networks measurements
the system will implement a multi-parametric analysis tool,
which represents and unique tool to analyze contemporaneously
a large data set of data in “near real time”. The SRV project will
be tested his operational capabilities on three Italian Volcanoes:
Etna,Vesuvio and Campi Flegrei
Volcanic Risk System (SRV): ASI Pilot Project to Support The Monitoring of Volcanic Risk In Italy by Means of EO Data
The ASI-SRV(Sistema Rischio Vulcanico) project
started at the beginning of the 2007 is funded by the Italian
Space Agency (ASI) in the frame of the National Space Plan
2003-2005 under the Earth Observations section for natural
risks management. Coordinated by the Istituto Nazionale di
Geofisica e Vulcanologia (INGV), which is responsible at national
level for the volcanic monitoring, the project has as main
objective to develop a pre-operative system based on EO data
and ground measurements integration to support the volcanic
risk monitoring of the Italian Civil Protection Department. The
project philosophy is to implement specific modules which allow
to process, store and visualize through Web GIS tools EO derived
parameters considering three activity phases: 1) knowledge and
prevention; 2) crisis; 3) post crisis. In order to combine
effectively the EO data and the ground networks measurements
the system will implement a multi-parametric analysis tool,
which represents and unique tool to analyze contemporaneously
a large data set of data in “near real time”. The SRV project will
be tested his operational capabilities on three Italian Volcanoes:
Etna,Vesuvio and Campi Flegrei
Volcanic Risk System (SRV): ASI Pilot Project to Support The Monitoring of Volcanic Risk In Italy by Means of EO Data
The ASI-SRV(Sistema Rischio Vulcanico) project
started at the beginning of the 2007 is funded by the Italian
Space Agency (ASI) in the frame of the National Space Plan
2003-2005 under the Earth Observations section for natural
risks management. Coordinated by the Istituto Nazionale di
Geofisica e Vulcanologia (INGV), which is responsible at national
level for the volcanic monitoring, the project has as main
objective to develop a pre-operative system based on EO data
and ground measurements integration to support the volcanic
risk monitoring of the Italian Civil Protection Department. The
project philosophy is to implement specific modules which allow
to process, store and visualize through Web GIS tools EO derived
parameters considering three activity phases: 1) knowledge and
prevention; 2) crisis; 3) post crisis. In order to combine
effectively the EO data and the ground networks measurements
the system will implement a multi-parametric analysis tool,
which represents and unique tool to analyze contemporaneously
a large data set of data in “near real time”. The SRV project will
be tested his operational capabilities on three Italian Volcanoes:
Etna,Vesuvio and Campi Flegrei.I.N.G.V. - O.V. SEZIONE DI NAPOLI
I.R.E.A. - C.N.R.
E.S.A.
A.S.I.PublishedNapoli1.10. TTC - Telerilevamentoope
Volcanic Activity: Processing of Observation and Remote Sensing Data (VAPOR)
The World Bank makes a very clear distinction between disasters and natural phenomena. Natural phenomena are events like volcanic eruptions. A disaster only occurs when the ability of the community to cope with natural phenomenon has been surpassed, causing widespread human, material, economic or environmental losses. By these definitions, volcanic eruptions do not have to lead to disasters. On November 13, 1985, the second most deadly eruption of the twentieth century occurred in Colombia. Within a few hours of the eruption of the Nevado del Ruiz volcano, 23,000 people were dead because no infrastructure existed to respond to such an emergency. Six years later, the 1991 eruption of Mount Pinatubo in the Philippines was the largest volcanic eruption in the 21st century to affect a heavily populated area. Because the volcano was monitored, early warning of the eruption was provided and thousands of lives were saved. Despite these improvements, some communities still face danger from volcanic events and volcano-monitoring systems still require further development. There remain clear gaps in monitoring technologies, in data sharing, and in early warning and hazard tracking systems. A global volcano-monitoring framework such as the VIDA framework can contribute to filling these gaps. VIDA stands for “VAPOR Integrated Data-sharing and Analysis” and is also the Catalan and Spanish word for ‘life’. The ultimate goal for this project is to help save the lives of people threatened by volcanic hazards, while protecting infrastructure and contributing to decision support mechanisms in disaster risk management scenarios
Automatic detection of changes in volcanic activity using ground based near-infrared cameras to monitor thermal incandescence
Thesis (M.S.) University of Alaska Fairbanks, 2017An increase in thermal activity is a common precursor of volcanic eruptions and, if identified, can be used to advise local observatories to disseminate the appropriate advanced warnings. As continuously operating near-infrared (NIR) cameras are becoming more readily available at active volcanoes around the world, this investigation explores the use of identifying changes in pixel brightness in webcam imagery resulting from increased thermal incandescence. A fast, efficient, and fully automated Python algorithm has been developed with a primary focus on effective volcano monitoring and reducing overall financial costs. The algorithm includes three important tests (statistical analysis, edge detection, and Gaussian mixture model) to identify changes in activity in near-real time. The developed algorithm can be installed locally with a webcam or at a central location, with no need for additional costs. This algorithm approach was preliminarily tested on data from a permanently installed thermal infrared camera at Stromboli volcano, with a successful detection rate of 75.34%. The algorithm based methodology was further developed and applied to freely available online webcam imagery from Shiveluch volcano, with an overall accuracy of 96.0%, and a critical success index (CSI) of 76.7%. Further refinements to the algorithm were made to reduce the false alarm rate (FAR) and number of missed events, and applied to four additional image datasets at Shiveluch, Fuego, Popocatepetl, and Stromboli. The algorithm successfully identified two large eruptions at Shiveluch, between 40 minutes and 2.5 hours prior to other satellite remote sensing methods, correctly identified the beginning of a large eruption at Fuego, which corresponded with local seismic data, and successfully identified a 90-minutes window of increased activity leading to a large paroxysm event at Popocatepetl, which was describe by the local observatory as having 'little to no warning'. The algorithm underperformed at Stromboli as the images here were capture in the thermal infrared (TIR) instead of the NIR, identifying the need for further improvements to ensure the algorithm performs correctly across multiple datasets. Overall, the algorithm developed here identifies thermally incandescent activity from increases in image pixel brightness remarkably well, and would complement existing volcano observatory monitoring tools, especially in remote or financially restricted locations as the equipment and coding language used here are extremely cheap compared to many other monitoring methods
GROUND DEFORMATION STUDIES AND EVACUATION BEHAVIOR DURING ERUPTIONS AT GUATEMALAN VOLCANOES
Volcanic eruptions can be an especially problematic hazard when considering the uncertainty in eruption timing and magnitude coupled with challenges associated with delivering warnings to remote areas and facilitating effective evacuations. The hazards presented by Guatemala’s active volcanoes demand enhanced monitoring capabilities and instrumentation infrastructure. Strengthening the link between the physical and social sciences should lead to more accurate, reliable, and timely hazard information to the people living in proximity to the volcano and facilitate rational decisions and actions that reduce their level of risk. While there is no one single technique that can provide unambiguous diagnostics about the timing, behavior, and outcome of a volcanic eruption, the use of GPS geodesy can provide valuable insight into the internal dynamics of a volcano allowing for enhanced interpretation of unrest signals that can be relayed to crisis management officials. The 2010 eruption of Pacaya lead to evacuations of more than 2500 people and resulted in damage and destruction to hundreds of homes. During this period of unrest, Pacaya was a poorly monitored volcano with little available quantitative geophysical data. However, despite a pronounced increase in activity prior to the eruption, and the heightened threat of injury or death during the eruption, many residents in communities surrounding the volcano chose to stay in their home throughout the eruptive crisis. Part of this research presents measurements from a campaign GPS network at Pacaya volcano, combined with InSAR data that reveals a large downward vertical and outward horizontal deformation signal at several locations around the volcano associated with two eruptive periods. We invert the available geodetic data to model the magma plumbing system and produce analytical models, which suggest that deformation was dominated by inflation of a sub-vertical dike high within the edifice while deflation of one or two deeper, spherical sources embedded below the edifice occurred during part of the observation period. The second part of this research seeks to understand why some chose to stay in harm’s way. Using data obtained from a door-to-door survey we found that evacuation behavior was strongly influenced by one’s exposure to and perception of the hazards as well as their perception of readiness. We also found that future intention to evacuate is strongly influenced by prior evacuation experience, perception of home vulnerability and warning messages. The research presented in this dissertation integrates geophysics and social vulnerability research with the aim to better understand magmatic system dynamics and associated hazards in volcanic regions in an effort to improve warning messages and evacuation behavior
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