The RST approach (Robust Satellite Techniques) is an original scheme of satellite data analysis, that computes a local variation index, in MIR spectral band, in order to identify hot spots, processing multi-years historical time series of homogeneous satellite records (i.e. collected in the same month at same acquisition time). This method was optimized, in the frame project, by a long-term time domain analysis performed on several satellite records, covering Mt. Etna area and acquired at different time passes (day/night). Moreover, it was implemented both on NOAA-AVHRR and EOS-MODIS data (acquired at IMAA-DIFA laboratories), by an automatic processing chain developed and tested in the frame of the project, even in a pre-operational context. The RST-LAVA products (together with requested MODIS raw data) were provided, in near real time, to RU01, immediately after the onset of an eruptive event began on 10th May 2008, supporting activities devoted to effusion rate estimation. Two scientific reports, one for the period 1-23 May 2008, and another for the period 1 May-16 July 2008, arisen from this strict collaboration. A preliminary implementation of RST scheme on SEVIRI data was also performed, in order to verify its capabilities in timely identifying the beginning of new eruptive events. An inter-comparison among different satellite techniques for hot spot detection was carried out on a specific test case (the Mt. Etna 14-24 July eruption), with AVHRR and MODIS hot spots products, together with RST based cloud masks, added to the project database. A real time provision of text alert files, from December 2008 to June 2009 (six months), was also performed, as a preoperational test of RST-LAVA product delivery. Finally, as a contribution in developing and testing a preliminary interface for DPC operational system, three years of AVHRR and MODIS-RST hot spot products, from 2007 to 2009, were generated and integrated into a preliminary Web-GIS.
Progetto V3-LAVA - Realization of the lava flow hazard map at Mount Etna and set up of a method for its dynamic update, Research Unit: RU V3/10
N Pergola;F Marchese;G Mazzeo;M Lisi;C Filizzola;T Lacava;R Paciello;
2010
Abstract
The RST approach (Robust Satellite Techniques) is an original scheme of satellite data analysis, that computes a local variation index, in MIR spectral band, in order to identify hot spots, processing multi-years historical time series of homogeneous satellite records (i.e. collected in the same month at same acquisition time). This method was optimized, in the frame project, by a long-term time domain analysis performed on several satellite records, covering Mt. Etna area and acquired at different time passes (day/night). Moreover, it was implemented both on NOAA-AVHRR and EOS-MODIS data (acquired at IMAA-DIFA laboratories), by an automatic processing chain developed and tested in the frame of the project, even in a pre-operational context. The RST-LAVA products (together with requested MODIS raw data) were provided, in near real time, to RU01, immediately after the onset of an eruptive event began on 10th May 2008, supporting activities devoted to effusion rate estimation. Two scientific reports, one for the period 1-23 May 2008, and another for the period 1 May-16 July 2008, arisen from this strict collaboration. A preliminary implementation of RST scheme on SEVIRI data was also performed, in order to verify its capabilities in timely identifying the beginning of new eruptive events. An inter-comparison among different satellite techniques for hot spot detection was carried out on a specific test case (the Mt. Etna 14-24 July eruption), with AVHRR and MODIS hot spots products, together with RST based cloud masks, added to the project database. A real time provision of text alert files, from December 2008 to June 2009 (six months), was also performed, as a preoperational test of RST-LAVA product delivery. Finally, as a contribution in developing and testing a preliminary interface for DPC operational system, three years of AVHRR and MODIS-RST hot spot products, from 2007 to 2009, were generated and integrated into a preliminary Web-GIS.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
