Smart Decision Support Systems for Volcanic Applications

The huge amount of information coming from remote sensors on satellites has allowed monitoring changes in the planetary environment from about 50 years. These instruments are widely adopted to observe extreme thermal events such as eruptive phenomena in volcanic areas. Although the availability of so many different infrared sensors makes these instruments suitable to observe different kind of thermal phenomena, choosing the right infrared sensor to monitor each thermal event is not straightforward. In fact, the decision should take into account both the main features of the phenomena under investigation, e.g., its size and temperatures, that are often not known a priori, and the instruments specifications, e.g., spatial resolution. Here, a smart decision support system (SDSS) is proposed to address this task. In particular, we used a SDSS to simulate remote sensors responses, collect data coming from three different classes of remote sensors, retrieve information about the main features of the observed thermal event and, consequently, select the most suitable infrared remote sensor for the specific observed phenomena. Results obtained for a real case of study at Etna volcano is shown.

[1]  T. Nightingale,et al.  Sentinel-3 SLSTR active fire detection and FRP product: Pre-launch algorithm development and performance evaluation using MODIS and ASTER datasets , 2012 .

[2]  Gianfranco Vulpiani,et al.  Mass discharge rate retrieval combining weather radar and thermal camera observations , 2016 .

[3]  Andrew J. L. Harris,et al.  VAST: a program to locate and analyse volcanic thermal anomalies automatically from remotely sensed data , 1997 .

[4]  Matthew Blackett,et al.  An Overview of Infrared Remote Sensing of Volcanic Activity , 2017, J. Imaging.

[5]  Carlos Roberto de Souza Filho,et al.  Calculating radiant flux from thermally mixed pixels using a spectral library , 2014 .

[6]  C. Del Negro,et al.  3D Lava flow mapping of the 17–25 May 2016 Etna eruption using tri-stereo optical satellite data , 2018, Annals of Geophysics.

[7]  R. A. Vaughan,et al.  Volcano detection and monitoring using AVHRR data: the Krafla eruption, 1984 , 1995 .

[8]  F. Ferrucci,et al.  Automated monitoring of high-temperature volcanic features: from high-spatial to very-high-temporal resolution , 2016, Special Publications.

[9]  C. Del Negro,et al.  Lava flow hazard modeling during the 2014–2015 Fogo eruption, Cape Verde , 2015 .

[10]  C. Negro,et al.  Separating the thermal fingerprints of lava flows and simultaneous lava fountaining using ground‐based thermal camera and SEVIRI measurements , 2013 .

[11]  A. Harris,et al.  Monitoring an effusive eruption at Piton de la Fournaise using radar and thermal infrared remote sensing data: insights into the October 2010 eruption and its lava flows , 2016, Special Publications.

[12]  Barbara Hirn,et al.  Synergetic exploitation of meteorological geostationary payloads «SEVIRI» and «JAMI» for quantitative, real-time, global volcano monitoring , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[13]  Y. Kaufman,et al.  Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release , 2005 .

[14]  C. Negro,et al.  Quantifying lava flow hazards in response to effusive eruption , 2016 .

[15]  A. Harris.  Thermal Remote Sensing of Active Volcanoes: A User's Manual , 2013 .

[16]  M. Ripepe,et al.  Enhanced volcanic hot-spot detection using MODIS IR data: results from the MIROVA system , 2015, Special Publications.

[17]  C. Negro,et al.  Satellite-driven modeling approach for monitoring lava flow hazards during the 2017 Etna eruption , 2017, Annals of Geophysics.

[18]  Valerio Tramutoli,et al.  Time domain analysis of robust satellite techniques (RST) for near real-time monitoring of active volcanoes and thermal precursor identification , 2009 .

[19]  C. Justice,et al.  The collection 6 MODIS active fire detection algorithm and fire products , 2016, Remote sensing of environment.

[20]  C. Del Negro,et al.  HOTSAT: a multiplatform system for the thermal monitoring of volcanic activity using satellite data , 2015, Special Publications.

[21]  C. Negro,et al.  An emergent strategy for volcano hazard assessment: From thermal satellite monitoring to lava flow modeling , 2012 .

[22]  C. Del Negro,et al.  Mapping Volcanic Deposits of the 2011–2015 Etna Eruptive Events Using Satellite Remote Sensing , 2018, Front. Earth Sci..

[23]  M. Ramsey,et al.  Operational thermal remote sensing and lava flow monitoring at the Hawaiian Volcano Observatory , 2015, Special Publications.

[24]  Klemen Zaksek,et al.  Satellite and Ground Based Thermal Observation of the 2014 Effusive Eruption at Stromboli Volcano , 2015, Remote. Sens..

[25]  Gaetana Ganci,et al.  Quantifying Effusion Rates at Active Volcanoes through Integrated Time-Lapse Laser Scanning and Photography , 2015, Remote. Sens..

[26]  G. Shao,et al.  The progress of operational forest fire monitoring with infrared remote sensing , 2017, Journal of Forestry Research.

[27]  M. Wooster,et al.  Fire radiative energy for quantitative study of biomass burning: derivation from the BIRD experimental satellite and comparison to MODIS fire products. , 2003 .