Evolution of lava flow-fields at Mount Etna, 27-28 October 1999, observed by Landsat 7 ETM+

2001 ◽  
Vol 63 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Robert Wright ◽  
Luke Flynn ◽  
Andrew Harris
Keyword(s):  
Lava Flow ◽  
Flow Fields ◽  
Mount Etna ◽  
Landsat 7

The Growth of AA Lava Flow Fields on Mount Etna, Sicily

2014 ◽  
pp. 14759-14772
Author(s):  
Christopher R. J. Kilburn ◽  
Rosaly M. C. Lopes
Keyword(s):  
Lava Flow ◽  
Flow Fields ◽  
Mount Etna ◽  
Aa Lava

The growth of AA lava flow fields on Mount Etna, Sicily

1988 ◽  
Vol 93 (B12) ◽  
pp. 14759-14772 ◽  
Author(s):  
Christopher R. J. Kilburn ◽  
Rosaly M. C. Lopes
Keyword(s):  
Lava Flow ◽  
Flow Fields ◽  
Mount Etna ◽  
Aa Lava

The evolution of lava flow-fields: observations of the 1981 and 1983 eruptions of Mount Etna, Sicily

1987 ◽  
Vol 49 (3) ◽  
pp. 527-540 ◽  
Author(s):  
J. E. Guest ◽  
C. R. J. Kilburn ◽  
H. Pinkerton ◽  
A. M. Duncan
Keyword(s):  
Lava Flow ◽  
Flow Fields ◽  
Mount Etna

scholarly journals The 1974 West Flank Eruption of Mount Etna: A Data-Driven Model for a Low Elevation Effusive Event

2020 ◽  
Vol 8 ◽  
Author(s):  
Charline Lormand ◽  
Andrew J. L. Harris ◽  
Magdalena Oryaëlle Chevrel ◽  
Sonia Calvari ◽  
Lucia Gurioli ◽  
...  
Keyword(s):  
Phase I ◽  
Lava Flow ◽  
Phase Ii ◽  
Flow System ◽  
Flow Fields ◽  
Mount Etna ◽  
Effusion Rate ◽  
Flow Units ◽  
Levee Failure ◽  
Effusion Rates

Low elevation flank eruptions represent highly hazardous events due to their location near, or in, communities. Their potentially high effusion rates can feed fast moving lava flows that enter populated areas with little time for warning or evacuation, as was the case at Nyiragongo in 1977. The January–March 1974 eruption on the western flank of Mount Etna, Italy, was a low elevation effusive event, but with low effusion rates. It consisted of two eruptive phases, separated by 23 days of quiescence, and produced two lava flow fields. We describe the different properties of the two lava flow fields through structural and morphological analyses using UAV-based photogrammetry, plus textural and rheological analyses of samples. Phase I produced lower density (∼2,210 kg m−3) and crystallinity (∼37%) lavas at higher eruption temperatures (∼1,080°C), forming thinner (2–3 m) flow units with less-well-developed channels than Phase II. Although Phase II involved an identical source magma, it had higher densities (∼2,425 kg m−3) and crystallinities (∼40%), and lower eruption temperatures (∼1,030°C), forming thicker (5 m) flow units with well-formed channels. These contrasting properties were associated with distinct rheologies, Phase I lavas having lower viscosities (∼103 Pa s) than Phase II (∼105 Pa s). Effusion rates were higher during Phase I (≥5 m3/s), but the episodic, short-lived nature of each lava flow emplacement event meant that flows were volume-limited and short (≤1.5 km). Phase II effusion rates were lower (≤4 m3/s), but sustained effusion led to flow units that could still extend 1.3 km, although volume limits resulted from levee failure and flow avulsion to form new channels high in the lava flow system. We present a petrologically-based model whereby a similar magma fed both phases, but slower ascent during Phase II may have led to greater degrees of degassing resulting in higher cooling-induced densities and crystallinities, as well as lower temperatures. We thus define a low effusion rate end-member scenario for low elevation effusive events, revealing that such events are not necessarily of high effusion rate and velocity, as in the catastrophic event scenarios of Etna 1669 or Kilauea 2018.

scholarly journals Mapping Recent Lava Flows at Mount Etna Using Multispectral Sentinel-2 Images and Machine Learning Techniques

2019 ◽  
Vol 11 (16) ◽  
pp. 1916 ◽  
Author(s):  
Claudia Corradino ◽  
Gaetana Ganci ◽  
Annalisa Cappello ◽  
Giuseppe Bilotta ◽  
Alexis Hérault ◽  
...  
Keyword(s):  
Machine Learning ◽  
Lava Flow ◽  
Flow Behavior ◽  
Flow Fields ◽  
Lava Flows ◽  
Mount Etna ◽  
Machine Learning Techniques ◽  
Automated Classification ◽  
Learning Techniques ◽  
Sentinel 2

Accurate mapping of recent lava flows can provide significant insight into the development of flow fields that may aid in predicting future flow behavior. The task is challenging, due to both intrinsic properties of the phenomenon (e.g., lava flow resurfacing processes) and technical issues (e.g., the difficulty to survey a spatially extended lava flow with either aerial or ground instruments while avoiding hazardous locations). The huge amount of moderate to high resolution multispectral satellite data currently provides new opportunities for monitoring of extreme thermal events, such as eruptive phenomena. While retrieving boundaries of an active lava flow is relatively straightforward, problems arise when discriminating a recently cooled lava flow from older lava flow fields. Here, we present a new supervised classifier based on machine learning techniques to discriminate recent lava imaged in the MultiSpectral Imager (MSI) onboard Sentinel-2 satellite. Automated classification evaluates each pixel in a scene and then groups the pixels with similar values (e.g., digital number, reflectance, radiance) into a specified number of classes. Bands at the spatial resolution of 10 m (bands 2, 3, 4, 8) are used as input to the classifier. The training phase is performed on a small number of pixels manually labeled as covered by fresh lava, while the testing characterizes the entire lava flow field. Compared with ground-based measurements and actual lava flows of Mount Etna emplaced in 2017 and 2018, our automatic procedure provides excellent results in terms of accuracy, precision, and sensitivity.

The volume and shape of the 1991-1993 lava flow field at Mount Etna, Sicily

1997 ◽  
Vol 58 (6) ◽  
pp. 449-454 ◽  
Author(s):  
Nicki F. Stevens ◽  
John B. Murray ◽  
Geoff Wadge
Keyword(s):  
Flow Field ◽  
Lava Flow ◽  
Mount Etna ◽  
Lava Flow Field

scholarly journals DOWNFLOW code and LIDAR technology for lava flow analysis and hazard assessment at Mount Etna

2011 ◽  
Vol 54 (5) ◽  
Author(s):  
Massimiliano Favalli ◽  
Simone Tarquini ◽  
Alessandro Fornaciai
Keyword(s):  
Lava Flow ◽  
Hazard Assessment ◽  
Flow Analysis ◽  
Mount Etna
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