Chronology of the 2014–2016 Eruptive Phase of Volcán de Colima and Volume Estimation of Associated Lava Flows and Pyroclastic Flows Based on Optical Multi-Sensors

Dávila, Norma; Capra, Lucía; Ferrés, Dolors; Gavilanes-Ruiz, J.C.; Flores, Pablo

doi:10.3390/rs11101167

Cited by 12 publications

(4 citation statements)

References 40 publications

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“…Instead, Dávila et al [19] relied on satellite images to revise and improve the chronological reconstruction of the different eruptive phases that occurred from September 2014 to September 2016 at Volcán de Colima in Mexico, including the eruption on 10-11 July 2015, which was the most violent since the 1913 Plinian eruption. Their analysis mainly relied on satellite products.…”

Section: Investigation Mapping and Prediction Of Lava Flows And Laharsmentioning

confidence: 99%

Remote Sensing of Volcanic Processes and Risk

2020

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Remote sensing data and methods are increasingly being embedded into assessments of volcanic processes and risk. This happens thanks to their capability to provide a spectrum of observation and measurement opportunities to accurately sense the dynamics, magnitude, frequency, and impacts of volcanic activity in the ultraviolet (UV), visible (VIS), infrared (IR), and microwave domains. Launched in mid-2018, the Special Issue “Remote Sensing of Volcanic Processes and Risk” of Remote Sensing gathers 19 research papers on the use of satellite, aerial, and ground-based remote sensing to detect thermal features and anomalies, investigate lava and pyroclastic flows, predict the flow path of lahars, measure gas emissions and plumes, and estimate ground deformation. The strong multi-disciplinary character of the approaches employed for volcano monitoring and the combination of a variety of sensor types, platforms, and methods that come out from the papers testify the current scientific and technology trends toward multi-data and multi-sensor monitoring solutions. The research advances presented in the published papers are achieved thanks to a wealth of data including but not limited to the following: thermal IR from satellite missions (e.g., MODIS, VIIRS, AVHRR, Landsat-8, Sentinel-2, ASTER, TET-1) and ground-based stations (e.g., FLIR cameras); digital elevation/surface models from airborne sensors (e.g., Light Detection And Ranging (LiDAR), or 3D laser scans) and satellite imagery (e.g., tri-stereo Pléiades, SPOT-6/7, PlanetScope); airborne hyperspectral surveys; geophysics (e.g., ground-penetrating radar, electromagnetic induction, magnetic survey); ground-based acoustic infrasound; ground-based scanning UV spectrometers; and ground-based and satellite Synthetic Aperture Radar (SAR) imaging (e.g., TerraSAR-X, Sentinel-1, Radarsat-2). Data processing approaches and methods include change detection, offset tracking, Interferometric SAR (InSAR), photogrammetry, hotspots and anomalies detection, neural networks, numerical modeling, inversion modeling, wavelet transforms, and image segmentation. Some authors also share codes for automated data analysis and demonstrate methods for post-processing standard products that are made available for end users, and which are expected to stimulate the research community to exploit them in other volcanological application contexts. The geographic breath is global, with case studies in Chile, Peru, Ecuador, Guatemala, Mexico, Hawai’i, Alaska, Kamchatka, Japan, Indonesia, Vanuatu, Réunion Island, Ethiopia, Canary Islands, Greece, Italy, and Iceland. The added value of the published research lies on the demonstration of the benefits that these remote sensing technologies have brought to knowledge of volcanoes that pose risk to local communities; back-analysis and critical revision of recent volcanic eruptions and unrest periods; and improvement of modeling and prediction methods. Therefore, this Special Issue provides not only a collection of forefront research in remote sensing applied to volcanology, but also a selection of case studies proving the societal impact that this scientific discipline can potentially generate on volcanic hazard and risk management.

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Section: Investigation Mapping and Prediction Of Lava Flows And Laharsmentioning

confidence: 99%

Remote Sensing of Volcanic Processes and Risk

2020

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“…2 ). Again, non-intense pre-eruptive VT or LP seismicity was reported 55 . However, the SE shows a pre-eruptive decay two days in advance.…”

Section: Resultsmentioning

confidence: 99%

Tracking volcanic explosions using Shannon entropy at Volcán de Colima

Rey-Devesa

Prudencio

Benítez

et al. 2023

Sci Rep

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The main objective of this work is to show that Shannon Entropy (SE) calculated on continuous seismic signals can be used in a volcanic eruption monitoring system. We analysed three years of volcanic activity of Volcán de Colima, México, recorded between January 2015 and May 2017. This period includes two large explosions, with pyroclastic and lava flows, and intense activity of less energetic explosion, culminating with a period of quiescence. In order to confirm the success of our results, we used images of the Visual Monitoring system of Colima Volcano Observatory. Another of the objectives of this work is to show how the decrease in SE values can be used to track minor explosive activity, helping Machine Learning algorithms to work more efficiently in the complex problem of distinguishing the explosion signals in the seismograms. We show that the two big eruptions selected were forecasted successfully (6 and 2 days respectively) using the decay of SE. We conclude that SE could be used as a complementary tool in seismic volcano monitoring, showing its successful behaviour prior to energetic eruptions, giving time enough to alert the population and prepare for the consequences of an imminent and well predicted moment of the eruption.

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“…As evidenced in Figure 2, the decay of the SE to values close to zero occurred just before the vulcanian explosion. Again, non-intense pre-eruptive VT or LP seismicity was reported (Dávila et al, 2019). However, the SE shows a pre-eruptive decay two days in advance.…”

Section: According Tomentioning

confidence: 92%

Forecasting and Tracking Volcanic Explosions using Shannon Entropy at Volcán de Colima.

Rey-Devesa

Prudencio

Benítez

et al. 2023

Preprint

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In this work we demonstrate that Shannon Entropy (SE) calculated on continuous seismic signals can be used efficiently in a volcanic monitoring system. We analysed three years of volcanic activity of Volcán de Colima, México, recorded between January 2015 and May 2017. This period includes two large explosions, with pyroclastic and lava flows, and intense activity of less energetic explosion, culminating with a period of quiescence. In order to confirm the success of our results, we used images of the Visual Monitoring system of Colima Volcano Observatory. Another of the objectives of this work is to show how the decrease in the SE values can be used to track minor explosive activity, helping Machine Learning algorithms to work more efficiently in the complex problem of distinguishing the explosion signals in the seismograms. We demonstrated the two big eruptions selected were forecasted successfully (6 and 2 days respectively) using the decay of the SE. We conclude that the SE could be used as a complementary tool in seismic volcano monitoring, showing its successful behaviour prior to energetic eruptions, giving time enough to alert the population and prepare for the consequences of an imminent and well predicted moment of the eruption.

show abstract

Chronology of the 2014–2016 Eruptive Phase of Volcán de Colima and Volume Estimation of Associated Lava Flows and Pyroclastic Flows Based on Optical Multi-Sensors

Cited by 12 publications

References 40 publications

Remote Sensing of Volcanic Processes and Risk

Remote Sensing of Volcanic Processes and Risk

Tracking volcanic explosions using Shannon entropy at Volcán de Colima

Forecasting and Tracking Volcanic Explosions using Shannon Entropy at Volcán de Colima.

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