Video monitoring of the persistent strombolian activity of Stromboli volcano represents a window on its plumbing system and an opportunity for understanding the eruptive processes

Since 1994 a video-surveillance camera located on a peak just above the active volcanic vents of Stromboli island records the explosive activity of one of the few volcanoes on the world performing a persistent eruptive activity. From 2003, after one of the larger lava flow eruption of the last century, the video- surveillance system was enhanced with more stations having both thermal and visual cameras. The video-surveillance helps volcanologists to characterize the mild explosive activity of Stromboli named Strombolian and to distinguish between the frequent “ordinary” Strombolian explosions and the occasional “extraordinary” strong Strombolian explosions that periodically occur. A new class of extraordinary explosions was discovered filling the gap between the ordinary activity and the strong explosions named major explosions when the tephra fallout covers large areas on the volcano summit and paroxysmal ones when the bombs fall down to the inhabited area along the coast of the island. In order to quantify the trend of the ordinary Strombolian explosions and to understand the occurring of the extraordinary strong Strombolian explosions a computer assisted image analysis was developed to process the huge amount of thermal and visual images recorded in several years. The results of this complex analysis allow us to clarify the processes occurring in the upper plumbing system where the pockets/trains of bubbles coalesce and move into the active vent conduits producing the ordinary Strombolian activity, and to infer the process into the deeper part of the plumbing system where new magma supply and its evolution lead to the formation of the extraordinary strong Strombolian explosions

A real-time framework for fast data retrieval in an image database of volcano activity scenarios

Explosive Activity at Stromboli Volcano (Aeolian Islands) is continuously monitored by INGV-OE in order to analyze its eruptive dynamics and specific scenarios. In particular, the images acquired from thermal cameras represent a big collection of data. In order to extract useful information from thermal image sequences, we need an efficient way to explore and retrieve information from a huge amount of data. In this work, a novel framework capable of fast data retrieval, using the "metric space" concept, is shown. In the light of it, we implemented an indexing algorithm related to similarity laws. The focal point is finding objects of a set that are “close” in relation to a given query, according to a similarity criterion. In order to perform this task, we performed morphological image processing techniques to each video frame, in order to map the shape area of each explosion into a closed curve, representing the explosion contour itself. In order to constitute a metric space, we chose a certain number of features obtained from parameters related to this closed curve and used them as objects of this metric space where similarity can be evaluated, using an appropriate “metric” function to calculate the distances. Unfortunately, this approach has to deal with an intrinsic issue involving the complexity and the number of distance functions to be calculated on a large amount of data. To overcome this drawback, we used a novel abstract data structure called "K-Pole Tree", having the property of minimizing the number of distances to be calculated among objects. Our method allows for fast retrieval of similar objects using an euclidean distance function among the features of the metric space. Thus, we can cluster explosions related to different kinds of volcanic activity, using "pivot" items. For example, given a known image sequence related to a particular type of explosion, it is possible to quickly and easily find all the image sequences that contain only similar explosions. Our framework is able to both classify each new explosion and dynamically insert the corresponding object into our tree data structure. This approach is able to cluster the entire data space, ensuring that objects with similar features are grouped and classified together

Assessing and improving the measuring capability of the Etna_NETVIS camera network for lava flow rapid mapping

This work is aimed at improving the performance of the ground NEtwork of Thermal and VIsible and cameras located on Mt. Etna volcano (Etna_NETVIS) by optimizing its observational capability on lava flows evolution and by developing dedicated tools for systematically measuring quantitative parameters of known accuracy. The first goal will be achieved through the analysis of the geometrical configuration and its improvement by means of the establishment of additional observation sites to be equipped with mobile stations, depending on the area of interest. This will increment the spatial coverage and improve the observation of the most active areas for surface sin-eruptive processes. For the second objective we will implement new processing tools to permit a reliable quantitative use of the data collected by the surveillance sensors of NETVIS, extending their capability in monitor the lava flow thermal and spatial evolution and by providing georeferenced data for rapid mapping scope. The tool will be used to automatically pre-process multitemporal datasets and will be tested on both simulated and real scenarios. Thanks to data collected and archive by the NETVIS INGV team, we will have the opportunity to develop and test the procedure in different operational conditions selected among the large number of lava flows coupled to lava fountan events occurred between 2011 and 2013. Additionally, Etna_NETVIS data can be used to downscale the information derived from satellite data and/or to integrate the satellite datasets in case of incomplete coverage or missing acquisitions (both due to low revisiting time or bad geometrical conditions). Therefore an additional goal is that of comparing/integrating quantitative data derived from visible and radar satellite sensors with the maps obtained using Etna_NETVIS. The procedure will take into account the discrepancy among the different datasets in terms of accuracy and resolution and will attempt to provide a combined approach (based on error analysis and data weighting) to evaluate the final results reliability. Preliminary results on the procedure and algorithm adopted for geometric and radiometric sensor calibration, definition of optimized configurations through simulation and for extracting updated mapping data from multi-temporal dataset will be presented. This work is developed in the framework of the EU-FP7 project “MED-SUV” (MEDiterranean SUpersite Volcanoes)

Ristrutturazione e potenziamento delle stazioni Video di Stromboli

INGVPublished5V. Sorveglianza vulcanica ed emergenzeope

Vorrichtung und Verfahren zum Erfassen zumindest eines Vitalparameters einer Person; Vitalparametererfassungssystem

EP 2218395 A2 UPAB: 20100827 NOVELTY - The device has an optoelectronic sensor arrangement detecting a vital parameter by light transmission. The arrangement has a light-sensitive element (1') i.e. light sensor, and a light source (1) i.e. LED, which is arranged in a side part (110) of a support frame (120) of eyeglasses such that a direction of a maximum light output of the source corresponds to a shortest path (180) of the light from the source to the element. The element is arranged in another side part (110') of the frame, where one of the side parts (110') is provided opposite to the other side part (110). DETAILED DESCRIPTION - An INDEPENDENT CLAIM is also included for a method for detecting vital parameters of a person by an optoelectronic sensor arrangement. USE - Device for detecting vital parameters of a patient i.e. person, in a field of preventive, monitoring and accompanying medical care. Uses include but are not limited to arterial plethysmogram, heart rate, heart rate variability, oxygen content of arterial blood and pulse wave transmission time. ADVANTAGE - The light-sensitive element is arranged in one of the side parts of the support frame of the pair of spectacles and the light source is arranged in the other side part of the support frame such that the direction of the maximum light output of the light source corresponds to the shortest path of the light from the light source to the light-sensitive element, thus reducing the power requirement of the sensor arrangement. The device hence enables simple, efficient and reliable detection of the vital parameters with high quality even in stressful situations and situations of low blood pressure or hypothermia

Video monitoring of the persistent strombolian activity of Stromboli volcano represents a window on its plumbing system and an opportunity for understanding the eruptive processes

Since 1994 a video-surveillance camera located on a peak just above the active volcanic vents of Stromboli island records the explosive activity of one of the few volcanoes on the world performing a persistent eruptive activity. From 2003, after one of the larger lava flow eruption of the last century, the video- surveillance system was enhanced with more stations having both thermal and visual cameras. The video-surveillance helps volcanologists to characterize the mild explosive activity of Stromboli named Strombolian and to distinguish between the frequent “ordinary” Strombolian explosions and the occasional “extraordinary” strong Strombolian explosions that periodically occur. A new class of extraordinary explosions was discovered filling the gap between the ordinary activity and the strong explosions named major explosions when the tephra fallout covers large areas on the volcano summit and paroxysmal ones when the bombs fall down to the inhabited area along the coast of the island. In order to quantify the trend of the ordinary Strombolian explosions and to understand the occurring of the extraordinary strong Strombolian explosions a computer assisted image analysis was developed to process the huge amount of thermal and visual images recorded in several years. The results of this complex analysis allow us to clarify the processes occurring in the upper plumbing system where the pockets/trains of bubbles coalesce and move into the active vent conduits producing the ordinary Strombolian activity, and to infer the process into the deeper part of the plumbing system where new magma supply and its evolution lead to the formation of the extraordinary strong Strombolian explosions.PublishedVienna, Austria3V. Dinamiche e scenari eruttiviope

A real-time framework for fast data retrieval in an image database of volcano activity scenarios

Explosive Activity at Stromboli Volcano (Aeolian Islands) is continuously monitored by INGV-OE in order to analyze its eruptive dynamics and specific scenarios. In particular, the images acquired from thermal cameras represent a big collection of data. In order to extract useful information from thermal image sequences, we need an efficient way to explore and retrieve information from a huge amount of data. In this work, a novel framework capable of fast data retrieval, using the "metric space" concept, is shown. In the light of it, we implemented an indexing algorithm related to similarity laws. The focal point is finding objects of a set that are “close” in relation to a given query, according to a similarity criterion. In order to perform this task, we performed morphological image processing techniques to each video frame, in order to map the shape area of each explosion into a closed curve, representing the explosion contour itself. In order to constitute a metric space, we chose a certain number of features obtained from parameters related to this closed curve and used them as objects of this metric space where similarity can be evaluated, using an appropriate “metric” function to calculate the distances. Unfortunately, this approach has to deal with an intrinsic issue involving the complexity and the number of distance functions to be calculated on a large amount of data. To overcome this drawback, we used a novel abstract data structure called "K-Pole Tree", having the property of minimizing the number of distances to be calculated among objects. Our method allows for fast retrieval of similar objects using an euclidean distance function among the features of the metric space. Thus, we can cluster explosions related to different kinds of volcanic activity, using "pivot" items. For example, given a known image sequence related to a particular type of explosion, it is possible to quickly and easily find all the image sequences that contain only similar explosions. Our framework is able to both classify each new explosion and dynamically insert the corresponding object into our tree data structure. This approach is able to cluster the entire data space, ensuring that objects with similar features are grouped and classified together.PublishedVienna, Austria3IT. Calcolo scientifico e sistemi informaticiope

Emergenza Stromboli 2014. Monitoraggio e sorveglianza vulcanologica con telecamere termiche e nel visibile

Il monitoraggio e la sorveglianza vulcanologica con telecamere fisse sull'isola di Stromboli è iniziata circa 20 anni fa con la prima telecamera fissa al Pizzo. Nel 1994 fu istallata la prima telecamera e nel 96 dello stesso anno fu danneggiata dal parossismo del 4 Settembre 1996.PublishedRoma, Italy5V. Sorveglianza vulcanica ed emergenzeope