Towards operational use of satellite SO2 measurements in a volcano observatory

Author(s):  
Matthieu Epiard ◽  
Simon Carn

<p>Along with monitoring of seismic activity and ground deformation, the measurement of volcanic gas emissions and composition plays a key role in the surveillance of active volcanoes and the mitigation of volcanic hazards. Volcanic gas emissions also potentially impact the environment, human health and climate, providing further motivation for study. Currently, volcano observatories typically employ ground-based or airborne techniques to monitor volcanic gas emissions, mainly sulfur dioxide (SO<sub>2</sub>) fluxes and its ratios over other species (e.g., CO<sub>2</sub>, H<sub>2</sub>S). However, in recent years there have been significant breakthroughs in satellite observations of passive volcanic SO<sub>2</sub> emissions, including high-resolution ultraviolet (UV) measurements from the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite, and the development of long-term records of volcanic SO<sub>2</sub> degassing from the Ozone Monitoring Instrument (OMI) on NASA’s Aura satellite. Satellite measurements offer some advantages over traditional gas monitoring techniques, e.g., synoptic coverage of large regions, relative immunity to variations in wind direction, and ability to map the spatial extent and dispersion of volcanic SO<sub>2</sub> plumes with applications for health hazard mitigation. Although these satellite datasets are potentially valuable for active volcano monitoring and as a supplement to other gas monitoring techniques, significant barriers remain to their use at many volcano observatories, particularly in low-income countries. Notably, the increasing volume of satellite datasets (NASA’s database is bigger than 3 petabytes) and the demands of data processing represent challenges to their operational use at observatories with limited internet connectivity or computational capacity. Here, we present an ongoing effort to develop open-source Python software to access and process SO<sub>2</sub> data directly through NASA’s Earthdata portal Application Processing Interface (API), in order to streamline the satellite SO<sub>2</sub> data processing workflow for a volcano observatory. By allowing server-side satellite data subsetting around the volcano of interest, this API greatly reduces the processing burden and only requires an internet connection to the NASA server hosting the required datasets (including S5P/TROPOMI, Aura/OMI and many others). We present some examples of software output and potential applications. Our current goal is to deploy and test the software for operational use in a volcano observatory.  </p>

2008 ◽  
Vol 25 (5) ◽  
pp. 287-300 ◽  
Author(s):  
B. Martin ◽  
A. Al‐Shabibi ◽  
S.M. Batraneanu ◽  
Ciobotaru ◽  
G.L. Darlea ◽  
...  

2021 ◽  
Author(s):  
Bo Galle ◽  

<p>We present a detailed global data-set of volcanic sulphur dioxide (SO2) emissions during the period 2005-2017. Measurements were obtained by scanning-DOAS instruments of the NOVAC network at 32 volcanoes, and processed using a standardized procedure. We reveal the daily statistics of volcanic gas emissions under a variety of volcanological and meteorological conditions. Data from several volcanoes are presented for the first time. Our results  are compared with yearly averages derived from measurements from space by the Aura/OMI instrument and with historical inventories of GEIA. This comparison shows some interesting differences which reasons are briefly discussed. Data is openly available through the web repository at https://novac.chalmers.se/.</p>


2021 ◽  
Author(s):  
Davide Festa ◽  
Pierluigi Confuorto ◽  
Matteo Del Soldato ◽  
Silvia Bianchini ◽  
Nicola Casagli

<p>The launch of the Sentinel-1 constellation by the European Copernicus Program, primarily devoted to scientific community research, has allowed acquiring huge volumes of radar images with worldwide coverage and a short temporal sampling (12 days reduced to 6 days thanks to their position at 180° in the same orbit). The systematic collection of imagery and the repeated processing of each new pair of images acquired opened the unprecedent possibility of conducting a continuous monitoring of Earth surface deformations, such as subsidence and slope instabilities over different geomorphological settings. At present, Tuscany, Veneto and Valle d’Aosta regions (Italy) are benefiting from systematical Sentinel-1-based monitoring of geological and geomorphological hazards. The promising outcomes so far obtained constitute a decisive step towards near-real-time monitoring and therefore a valid support for geohazard risk management activities. Retracing the pattern set by the encouraging results from the three Italian Regions, an operating workflow chain is proposed in the framework of an operational monitoring service, from the collection of satellite images to the possibility of conducting field surveys. The procedure is based on 4 different steps: i) continuous collection of Sentinel-1 images, constant data processing through an MT-InSAR (Multi-Temporal Interferometric Synthetic Aperture Radar) technique and exploitation of a data-mining algorithm able to retain only meaningful Measurement Points (MP) in terms of abrupt change of displacement rate; ii) radar-interpretation of the filtered MP for the detection of the possible causes of the anomalies through the use of ancillary informative layers or pre-existing databases; iii) dissemination of the relevant radar-interpreted information to hydrological risk managing actors by a direct alert or periodic bulletins; iv) field investigation, preliminary risk assessment and possible remedial works design. The procedure was successfully applied gathering evidence of its usefulness in practical terms. The cases of the Bosmatto landslide (Valle d’Aosta Region) and the case of the Zeri Landslide (Tuscany Region) which belong to two alpine and apennine environments, respectively, are reported. In the first example, in response to a relevant acceleration interpreted from the MP available on the area of interest, an alert was sent to the regional officers who increased their awareness related to the risk posed by the Bosmatto Landslide. In the second example, a monitoring bulletin which is periodically delivered for the Tuscany Region pointed out the meaningfulness and persistency of anomalies identified in the Zeri municipality. This led the regional authorities to conduct a site investigation oriented to the assessment of preliminary risks. The presented results highlight the effective benefits-cost ratio, the high precision and the short amount of time required to complete the procedure representing a best practice for the early detection of ground deformation events.</p>


2020 ◽  
Vol 58 (12) ◽  
pp. 8531-8540
Author(s):  
MinJie Zhao ◽  
FuQi Si ◽  
Yu Wang ◽  
HaiJin Zhou ◽  
ShiMei Wang ◽  
...  

Author(s):  
Hailiang Shi ◽  
Zhiwei Li ◽  
Hanhan Ye ◽  
Haiyan Luo ◽  
Wei Xiong ◽  
...  

2002 ◽  
Vol 21 (8) ◽  
pp. 498-514 ◽  
Author(s):  
Jorge.A Diaz ◽  
Clayton F Giese ◽  
W.Ronald Gentry

1997 ◽  
Vol 102 (B7) ◽  
pp. 15039-15055 ◽  
Author(s):  
Grazyna Zreda-Gostynska ◽  
Philip R. Kyle ◽  
D. Finnegan ◽  
Kimberly Meeker Prestbo

Author(s):  
C. Dou ◽  
H. Guo ◽  
C. Han ◽  
X. Yue ◽  
Y. Zhao

Short temporal baseline and multiple ground deformation information can be derived from the airborne differential synthetic aperture radar Interforemetry (D-InSAR). However, affected by the turbulence of the air, the aircraft would deviate from the designed flight path with high frequent vibrations and changes both in the flight trajectory and attitude. Restricted by the accuracy of the position and orientation system (POS), these high frequent deviations can not be accurately reported, which would pose great challenges in motion compensation and interferometric process. Thus, these challenges constrain its wider applications. The objective of this paper is to investigate the accurate estimation and compensation of the residual motion errors in the airborne SAR imagery and time-varying baseline errors between the diffirent data acquirations, furthermore, to explore the integration data processing theory for the airborne D-InSAR system, and thus help to accomplish the correct derivation of the ground deformation by using the airborne D-InSAR measurements.


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