MyJournals Home  

RSS FeedsRemote Sensing, Vol. 11, Pages 2879: The July/August 2019 Lava Flows at the Sciara del Fuoco, Stromboli-Analysis from Multi-Sensor Infrared Satellite Imagery (Remote Sensing)

 
 

4 december 2019 02:00:01

 
Remote Sensing, Vol. 11, Pages 2879: The July/August 2019 Lava Flows at the Sciara del Fuoco, Stromboli-Analysis from Multi-Sensor Infrared Satellite Imagery (Remote Sensing)
 


On 3 July 2019 a rapid sequence of paroxysmal explosions at the summit craters of Stromboli (Aeolian-Islands, Italy) occurred, followed by a period of intense Strombolian and effusive activity in July, and continuing until the end of August 2019. We present a joint analysis of multi-sensor infrared satellite imagery to investigate this eruption episode. Data from the Spinning-Enhanced-Visible-and-InfraRed-Imager (SEVIRI) was used in combination with those from the Multispectral-Instrument (MSI), the Operational-Land-Imager (OLI), the Advanced-Very High-Resolution-Radiometer (AVHRR), and the Visible-Infrared-Imaging-Radiometer-Suite (VIIRS). The analysis of infrared SEVIRI-data allowed us to detect eruption onset and to investigate short-term variations of thermal volcanic activity, providing information in agreement with that inferred by nighttime-AVHRR-observations. By using Sentinel-2-MSI and Landsat-8-OLI imagery, we better localized the active lava-flows. The latter were quantitatively characterized using infrared VIIRS-data, estimating an erupted lava volume of 6.33×106±3.17×106 m3 and a mean output rate of 1.26 ± 0.63 m3/s for the July/August 2019 eruption period. The estimated mean-output-rate was higher than the ones in the 2002–2003 and 2014 Stromboli effusive eruptions, but was lower than in the 2007-eruption. These results confirmed that a multi-sensor-approach might provide a relevant contribution to investigate, monitor and characterize thermal volcanic activity in high-risk areas.


 
201 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 11, Pages 2880: The Influence of Vegetation Characteristics on Individual Tree Segmentation Methods with Airborne LiDAR Data (Remote Sensing)
Remote Sensing, Vol. 11, Pages 2878: An Object-Based Markov Random Field Model with Anisotropic Penalty for Semantic Segmentation of High Spatial Resolution Remote Sensing Imagery (Remote Sensing)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics


Copyright © 2008 - 2024 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Nachrichten