122,834 research outputs found
A google earth engine tool to investigate, map and monitor volcanic thermal anomalies at global scale by means of mid-high spatial resolution satellite data
No full textSeveral satellite-based systems have been developed over the years to study and monitor thermal volcanic activity. Most of them use high temporal resolution satellite data, provided by sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) that if on the one hand guarantee a continuous monitoring of active volcanic areas on the other hand are less suited to map thermal anomalies, and to provide accurate information about their features. The Multispectral Instrument (MSI) and the Operational Land Imager (OLI), respectively, onboard the Sentinel-2 and Landsat-8 satellites, providing Short-Wave Infrared (SWIR) data at 20 m (MSI) and 30 m (OLI) spatial resolution, may make an important contribution in this area. In this work, we present the first Google Earth Engine (GEE) App to investigate, map and monitor volcanic thermal anomalies at global scale, integrating Landsat-8 OLI and Sentinel-2 MSI observations. This open tool, which implements the Normalized Hot spot Indices (NHI) algorithm, enables the analysis of more than 1400 active volcanoes, with very low processing times, thanks to the high GEE computational resources. Performance and limitations of the tool, such as its next upgrades, aiming at increasing the user-friendly experience and extending the temporal range of data analyses, are analyzed and discussed
A robust satellite technique for monitoring seismically active areas: the case of Bhuj - Gujarat earthquake.
No full textA robust satellite data analysis technique (RAT) has been recently proposed as a suitable tool for satellite TIR surveys in seismically active regions and already successfully tested in different cases of earthquakes (both high and medium–low magnitudes).
In this paper, the efficiency and the potentialities of the RAT technique have been tested even when it is applied to a wide area with extremely variable topography, land coverage and climatic characteristics (the whole Indian subcontinent). Bhuj–Gujarat's earthquake (occurred on 26th January 2001, MS ∼ 7.9) has been considered as a test case in the validation phase, while a relatively unperturbed period (no earthquakes with MS ≥ 5, in the same region and in the same period) has been analyzed for confutation purposes. To this aim, 6 years of Meteosat-5 TIR observations have been processed for the characterization of the TIR signal behaviour at each specific observation time and location.
The anomalous TIR values, detected by RAT, have been evaluated in terms of time–space persistence in order to establish the existence of actually significant anomalous transients. The results indicate that the studied area was affected by significant positive thermal anomalies which were identified, at different intensity levels, not far from the Gujarat coast (since 15th January, but with a clearer evidence on 22nd January) and near the epicentral area (mainly on 21st January). On 25th January (1 day before Gujarat's earthquake) significant TIR anomalies appear on the Northern Indian subcontinent, showing a remarkable coincidence with the principal tectonic lineaments of the region (thrust Himalayan boundary).
On the other hand, the results of the confutation analysis indicate that no meaningful TIR anomalies appear in the absence of seismic events with MS ≥ 5
Investigating Phases of Thermal Unrest at Ambrym (Vanuatu) Volcano through the Normalized Hot Spot Indices Tool and the Integration with the MIROVA System
No full textRobust Satellite Techniques for Detecting Preseismic Thermal Anomalies
No full textSeveral satellite techniques have been proposed in recent decades to monitor geophysical phenomena possibly associated with earthquakes. Among them, several studies suggest the existence of a relation between space–time anomalies of Earth’s thermally emitted radiation (usually referred as “TIR anomalies”) and earthquake occurrence.
More recently a robust approach has been proposed which seems to be suitable for recognizing space–time anomalies in the measured TIR signal even in the presence of highly variable contributions coming from Earth’s surface and atmosphere (due for instance to meteorological factors) as well as from specific observational conditions. This Chapter presents that approach together with a modality of its implementation in the framework of an operational multiparametric system for a time‐Dependent Assessment of Seismic Hazard (t‐DASH)
First Implementation of a Normalized Hotspot Index on Himawari-8 and GOES-R Data for the Active Volcanoes Monitoring: Results and Future Developments
No full textThe Advanced Himawari Imager (AHI) and Advanced Baseline Imager (ABI), respectively aboard Himawari-8 and GOES-R geostationary satellites, are two important instruments for the near-real time monitoring of active volcanoes in the Eastern Asia/Western Pacific region and the Pacific Ring of Fire. In this work, we use for the first time AHI and ABI data, at 10 min temporal resolution, to assess the behavior of a Normalized Hotspot Index (NHI) in presence of active lava flows/lakes, at Krakatau (Indonesia), Ambrym (Vanuatu) and Kilauea (HI, USA) volcanoes. Results show that the index, which is used operationally to map hot targets through the Multispectral Instrument (MSI) and the Operational Land Imager (OLI), is sensitive to high-temperature features even when short-wave infrared (SWIR) data at 2 km spatial resolution are analyzed. On the other hand, thresholds should be tailored to those data to better discriminate thermal anomalies from the background in daylight conditions. In this context, the multi-temporal analysis of NHI may enable an efficient identification of high-temperature targets without using fixed thresholds. This approach could be exported to SWIR data from the Flexible Combined Imager (FCI) instrument aboard the next Meteosat Third Generation (MTG) satellites
A Tailored Approach for the Global Gas Flaring Investigation by Means of Daytime Satellite Imagery
No full textThe Daytime Approach for gas Flaring Investigation (DAFI), running in Google Earth Engine (GEE) environment, exploits a Normalized Hotspot Index (NHI), analyzing near-infrared and short-wave infrared radiances, to detect worldwide high-temperature gas flaring sites (GFs). Daytime Landsat 8—Operational Land Imager (OLI) observations, of 2013–2021, represents the employed dataset. A temporal persistence criterion is applied to a gas flaring customized NHI product to select the GFs. It assures the 99% detection accuracy of more intense and stable GFs, with a very low false positive rate. As a result, the first daytime database and map of GF sites, operating during the last 9 years at global scale, has been generated. For each site, geographical metadata, frequency of occurrence and time persistence levels, at both monthly and annual scale, may be examined, through the specific developed GEE App. The present database will complement/integrate existing gas flaring maps. The joint use of global scale daytime and nighttime GFs inventories, in fact, will allow for tracking gas flaring dynamics in a timely manner. Moreover, it enables a better evaluation of GF emissions into the atmosphere. Finally, the next DAFI implementation on Landsat 9 and Sentinel 2 data will further improve our capabilities in identifying, mapping, monitoring and characterizing the GFs
Monitoring the Mauna Loa (Hawaii) eruption of November–December 2022 from space: Results from GOES-R, Sentinel-2 and Landsat-8/9 observations
No full textMauna Loa, one of the most actives volcanoes on Earth, is a shield volcano, located on the Island of Hawaii (USA). On 27 November 2022, after about 38 years of quiescence, a new eruptive activity took place at the Moku‘āweoweo caldera, continuing in the following days (i.e. until 10 December) from the fissure vents opening on the Northeast Rift Zone. In this work, we investigate the Mauna Loa November − December 2022 eruption from space, integrating the information from different satellite sensors. The analysis of short-wave infrared (SWIR) data, at 10 min temporal resolution, from the Advanced Baseline Imager (ABI), aboard the Geostationary Operational Environmental Satellites − R series (GOES-R), performed through the Normalised Hotspot Indices (NHI), indicates that the Mauna Loa eruption started on 27 November in between 23:10–23:20 LT (28 November at 09:10–09:20 UTC). The same analysis shows the increase of thermal activity and its progressive reduction from the early morning of 28 November, in agreement with the eruption migration from the summit caldera to the Northeast Rift Zone. By analysing the second phase of eruption through SWIR data from the Multispectral Instrument (MSI) and Operational Land Imager (OLI), respectively aboard Sentinel-2 and Landsat 8/9 satellites, we estimated a maximum lava flow length of 17 km. Moreover, we retrieved values of the volcanic radiative power (VRP) up to 65 GW, and a time-averaged discharge rate (TADR) of ∼1000 (±500) m3/s. These results show that SWIR observations, at different spatial and temporal resolution, may give an important contribution to the monitoring, mapping and characterisation of intense lava effusions
Statistical Correlation Analysis Between Thermal Infrared Anomalies Observed From MTSATs and Large Earthquakes Occurred in Japan (2005–2015)
No full textThe literature often reports space–time relations between the abnormal variations of different kinds of nonseismological (i.e., geophysical, geochemical, and atmospheric) parameters and the occurrence of earthquakes. The integration of such observations with seismological ones could improve
the quality of the seismic hazard assessment in the medium-short term (months to days). Each considered parameter has, in principle, its capabilities to provide useful (and utilizable) information about seismic processes. Therefore, to define a system based on different observations, the first step is to estimate the
informative contribution that each considered parameter could provide. In this paper, we will evaluate the potential of Significant Sequence of Thermal Anomalies (SSTAs). In particular, we adopted the broadly used Robust Satellite Techniques (RST) data analysis methodology to identify SSTAs over 11 years (June 2005 to December 2015) of nighttime satellite images acquired by MTSAT satellites over Japan. Aiming at reducing the false-positive rate, we introduced and tested an innovative configuration of the RST, whichis here presented. We executed a correlation analysis between SSTAs and Japanese earthquakes with
MJMA ≥ 6 by applying suitable constraints concerning space, time, and magnitude. The analysis highlights (a) the occurrence of just 29 SSTAs in the 11-year period of observation, (b) 18 SSTAs (i.e., 62%) occur in an apparent space–time relation to earthquakes, and (c) 13 of them occur before the quake. Results of the random test analysis, based on error diagrams, confirm a noncasual correlation between “RST-based satellite thermal anomalies” and earthquake occurrences. In particular, for MJMA ≥ 6.5 earthquakes, probability gain is up to better than 4.3 as compared with the random guess
Monitoring the Mauna Loa (Hawaii) eruption of November–December 2022 from space: Results from GOES-R, Sentinel-2 and Landsat-8/9 observations
No full textMauna Loa, one of the most actives volcanoes on Earth, is a shield volcano, located on the Island of Hawaii (USA). On 27 November 2022, after about 38 years of quiescence, a new eruptive activity took place at the Moku'a over bar weoweo caldera, continuing in the following days (i.e. until 10 December) from the fissure vents opening on the Northeast Rift Zone. In this work, we investigate the Mauna Loa November - December 2022 eruption from space, integrating the information from different satellite sensors. The analysis of short-wave infrared (SWIR) data, at 10 min temporal resolution, from the Advanced Baseline Imager (ABI), aboard the Geostationary Operational Environmental Satellites - R series (GOES-R), performed through the Normalised Hotspot Indices (NHI), indicates that the Mauna Loa eruption started on 27 November in between 23:10-23:20 LT (28 November at 09:10-09:20 UTC). The same analysis shows the increase of thermal activity and its progressive reduction from the early morning of 28 November, in agreement with the eruption migration from the summit caldera to the Northeast Rift Zone. By analysing the second phase of eruption through SWIR data from the Multispectral Instrument (MSI) and Operational Land Imager (OLI), respectively aboard Sentinel-2 and Landsat 8/9 satellites, we estimated a maximum lava flow length of 17 km. Moreover, we retrieved values of the volcanic radiative power (VRP) up to 65 GW, and a time-averaged discharge rate (TADR) of similar to 1000 (+/- 500) m(3)/s. These results show that SWIR observations, at different spatial and temporal resolution, may give an important contribution to the monitoring, mapping and characterisation of intense lava effusions
Significant Cases of Preseismic Thermal Infrared Anomalies
No full textFrom appropriate identification and real‐time integration of independent observations we expect to improve significantly our present capability to assess the seismic hazard in the short term (from weeks to days before an earthquake). One specific observation (e.g. anomaly in one parameter) sometimes can be used as a trigger or as a reference point (in the space and/or time domain) for activating/improving analysis on other independent parameters whose systematic computation otherwise could be computationally very expensive or impossible. In this chapter, we briefly exemplify these advantages, and the utility of the Robust Satellite Technique (RST) approach. The RST data analysis approach has been implemented on daily TIR satellite records collected over three different
areas (Italy, Greece, and Turkey) by the geostationary satellite sensor Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat Second Generation (MSG) satellite, in order to evaluate its possible contribution to an improved multiparametric system for a time‐dependent assessment of seismic hazard
- …
