ALBERT

Description: Most of the world’s 1500 active volcanoes are not instrumentally monitored, resulting in deadly eruptions which can occur without observation of precursory activity. The new Sentinel missions are now providing freely available imagery with unprecedented spatial and temporal resolutions, with payloads allowing for a comprehensive monitoring of volcanic hazards. We here present the volcano monitoring platform MOUNTS (Monitoring Unrest from Space), which aims for global monitoring, using multisensor satellite-based imagery (Sentinel-1 Synthetic Aperture Radar SAR, Sentinel-2 Short-Wave InfraRed SWIR, Sentinel-5P TROPOMI), ground-based seismic data (GEOFON and USGS global earthquake catalogues), and artificial intelligence (AI) to assist monitoring tasks. It provides near-real-time access to surface deformation, heat anomalies, SO2 gas emissions, and local seismicity at a number of volcanoes around the globe, providing support to both scientific and operational communities for volcanic risk assessment. Results are visualized on an open-access website where both geocoded images and time series of relevant parameters are provided, allowing for a comprehensive understanding of the temporal evolution of volcanic activity and eruptive products. We further demonstrate that AI can play a key role in such monitoring frameworks. Here we design and train a Convolutional Neural Network (CNN) on synthetically generated interferograms, to operationally detect strong deformation (e.g., related to dyke intrusions), in the real interferograms produced by MOUNTS. The utility of this interdisciplinary approach is illustrated through a number of recent eruptions (Erta Ale 2017, Fuego 2018, Kilauea 2018, Anak Krakatau 2018, Ambrym 2018, and Piton de la Fournaise 2018–2019). We show how exploiting multiple sensors allows for assessment of a variety of volcanic processes in various climatic settings, ranging from subsurface magma intrusion, to surface eruptive deposit emplacement, pre/syn-eruptive morphological changes, and gas propagation into the atmosphere. The data processed by MOUNTS is providing insights into eruptive precursors and eruptive dynamics of these volcanoes, and is sharpening our understanding of how the integration of multiparametric datasets can help better monitor volcanic hazards.

Description: Lava domes grow by extrusions and intrusions of viscous magma often initiating from a central volcanic vent, and they are frequently defining the source region of hazardous explosive eruptions and pyroclastic density currents. Thus, close monitoring of dome building processes is crucial, but often limited to low data resolution, hazardous access, and poor visibility. Here, we investigated the 2016–2017 eruptive sequence of the dome building Bezymianny volcano, Kamchatka, with spot-mode TerraSAR-X acquisitions, and complement the analysis with webcam imagery and seismic data. Our results reveal clear morphometric changes preceding eruptions that are associated with intrusions and extrusions. Pixel offset measurements show 〉7 months of precursory plug extrusion, being locally defined and exceeding 30 m of deformation, chiefly without detected seismicity. After a short explosion, three months of lava dome evolution were characterised by extrusions and intrusion. Our data suggest that the growth mechanisms were significantly governed by magma supply rate and shallow upper conduit solidification that deflected magmatic intrusions into the uppermost parts of the dome. The integrated approach contributes significantly to a better understanding of precursory activity and complex growth interactions at dome building volcanoes, and shows that intrusive and extrusive growth is acting in chorus at Bezymianny volcano.

Description: The increase in mosquito populations following extreme weather events poses a major threat to humans because of mosquitoes’ ability to carry disease-causing pathogens, particularly in low-lying, poorly drained coastal plains vulnerable to tropical cyclones. In areas with reservoirs of disease, mosquito abundance information can help to identify the areas at higher risk of disease transmission. Using a Geographic Information System (GIS), mosquito abundance is predicted across the City of Chesapeake, Virginia. The mosquito abundance model uses mosquito light trap counts, a habitat suitability model, and dynamic environmental variables (temperature and precipitation) to predict the abundance of the species Culiseta melanura, as well as the combined abundance of the ephemeral species, Aedes vexans and Psorophora columbiae, for the year 2003. Remote sensing techniques were used to quantify environmental variables for a potential habitat suitability index for the mosquito species. The goal of this study was to produce an abundance model that could guide risk assessment, surveillance, and potential disease transmission. Results highlight the utility of integrating field surveillance, remote sensing for synoptic landscape habitat distributions, and dynamic environmental data for predicting mosquito vector abundance across low-lying coastal plains. Limitations of mosquito trapping and multi-source geospatial environmental data are highlighted for future spatial modeling of disease transmission risk.

Description: The increase in mosquito populations following extreme weather events poses a major threat to humans because of mosquitoes’ ability to carry disease-causing pathogens, particularly in low-lying, poorly drained coastal plains vulnerable to tropical cyclones. In areas with reservoirs of disease, mosquito abundance information can help to identify the areas at higher risk of disease transmission. Using a Geographic Information System (GIS), mosquito abundance is predicted across the City of Chesapeake, Virginia. The mosquito abundance model uses mosquito light trap counts, a habitat suitability model, and dynamic environmental variables (temperature and precipitation) to predict the abundance of the species Culiseta melanura, as well as the combined abundance of the ephemeral species, Aedes vexans and Psorophora columbiae, for the year 2003. Remote sensing techniques were used to quantify environmental variables for a potential habitat suitability index for the mosquito species. The goal of this study was to produce an abundance model that could guide risk assessment, surveillance, and potential disease transmission. Results highlight the utility of integrating field surveillance, remote sensing for synoptic landscape habitat distributions, and dynamic environmental data for predicting mosquito vector abundance across low-lying coastal plains. Limitations of mosquito trapping and multi-source geospatial environmental data are highlighted for future spatial modeling of disease transmission risk.

Description: New volcanic unrest has been detected in the Domuyo Volcanic Center (DVC), to the east of the Andes Southern Volcanic Zone in Argentina. To better understand this activity, we investigated new seismic monitoring data, gravimetric and magnetic campaign data, and interferometric synthetic aperture radar (InSAR) deformation maps, and we derived an image of the magma plumbing system and the likely source of the unrest episode. Seismic events recorded during 2017–2018 nucleate beneath the southwestern flank of the DVC. Ground deformation maps derived from InSAR processing of Sentinel-1 data exhibit an inflation area exceeding 300 km2, from 2014 to at least March 2018, which can be explained by an inflating sill model located 7 km deep. The Bouguer anomaly reveals a negative density contrast of ~35 km wavelength, which is spatially coincident with the InSAR pattern. Our 3D density modeling suggests a body approximately 4–6 km deep with a density contrast of –550 kg/m3. Therefore, the geophysical and geodetic data allow identification of the plumbing system that is subject to inflation at these shallow crustal depths. We compared the presence and dimensions of the inferred doming area to the drainage patterns of the area, which support long-established incremental uplift according to morphometric analysis. Future studies will allow us to investigate further whether the new unrest is hydrothermal or magmatic in origin.

Description: Remote Sensing, Vol. 10, Pages 1514: Radar Path Delay Effects in Volcanic Gas Plumes: The Case of Láscar Volcano, Northern Chile Remote Sensing doi: 10.3390/rs10101514 Authors: Stefan Bredemeyer Franz-Georg Ulmer Thor H. Hansteen Thomas R. Walter Modern volcano monitoring commonly involves Interferometric Synthetic Aperture Radar (InSAR) measurements to identify ground motions caused by volcanic activity. However, InSAR is largely affected by changes in atmospheric refractivity, in particular by changes which can be attributed to the distribution of water (H2O) vapor in the atmospheric column. Gas emissions from continuously degassing volcanoes contain abundant water vapor and thus produce variations in the atmospheric water vapor content above and downwind of the volcano, which are notably well captured by short-wavelength X-band SAR systems. These variations may in turn cause differential phase errors in volcano deformation estimates due to excess radar path delay effects within the volcanic gas plume. Inversely, if these radar path delay effects are better understood, they may be even used for monitoring degassing activity, by means of the precipitable water vapor (PWV) content in the plume at the time of SAR acquisitions, which may provide essential information on gas plume dispersion and the state of volcanic and hydrothermal activity. In this work we investigate the radar path delays that were generated by water vapor contained in the volcanic gas plume of the persistently degassing Láscar volcano, which is located in the dry Atacama Desert of Northern Chile. We estimate water vapor contents based on sulfur dioxide (SO2) emission measurements from a scanning UV spectrometer (Mini-DOAS) station installed at Láscar volcano, which were scaled by H2O/SO2 molar mixing ratios obtained during a multi-component Gas Analyzer System (Multi-GAS) survey on the crater rim of the volcano. To calculate the water vapor content in the downwind portion of the plume, where an increase of water vapor is expected, we further applied a correction involving estimation of potential evaporation rates of water droplets governed by turbulent mixing of the condensed volcanic plume with the dry atmosphere. Based on these estimates we obtain daily average PWV contents inside the volcanic gas plume of 0.2–2.5 mm equivalent water column, which translates to a slant wet delay (SWD) in DInSAR data of 1.6–20 mm. We used these estimates in combination with our high resolution TerraSAR-X DInSAR observations at Láscar volcano, in order to demonstrate the occurrence of repeated atmospheric delay patterns that were generated by volcanic gas emissions. We show that gas plume related refractivity changes are significant and detectable in DInSAR measurements. Implications are two-fold: X-band satellite radar observations also contain information on the degassing state of a volcano, while deformation signals need to be interpreted with care, which has relevance for volcano observations at Láscar and for other sites worldwide.

Description: To better understand the Earth system, it is important to investigate the interactions between precipitation, land use/land cover (LULC), and the land surface, especially vegetation. An improved understanding of these land-atmosphere interactions can aid understanding of the climate system and modeling of time series satellite data. Here, we investigate the effect of precipitation and LULC on the reflectance of the land surface in the northern U.S. Great Plains. We utilize time series satellite data from the 45 year Landsat archive. The length of the Landsat record allows for analysis of multiple periods of drought and wet conditions (reflecting climate, as well as weather), such that the precipitation-reflectance relationship can be investigated robustly for every individual pixel in the study area. The high spatial resolution of Landsat (30 m) allows for investigation of spatial patterns in weather (i.e., precipitation extremes) interactions with land surface reflectance at the scale of individual fields. Weather history is represented by a drought index that describes effective moisture availability, the Standardized Precipitation and Evaporation Index (SPEI). We find that effective moisture has a robust and consistent effect on reflectance over many types of land cover, with ∼90% of all pixels having significantly ( p 〈 0.01 ) higher visible reflectance during dry periods than during wet, occurring in nearly all regional, temporal, and LULC categories investigated. In grassland, the relationship is especially strong; there is an average reflectance increase of more than a third between very wet and very dry conditions (red band), and ∼99% of pixels have a significant relationship. In cropland, the effective moisture-reflectance relationship is more variable, suggesting that management decisions are an important factor in cropland-reflectance relationships.

Description: Vulcanian explosions are hazardous and are often spontaneous and direct observations are therefore challenging. Ebeko is an active volcano on Paramushir Island, northern Kuril Islands, showing characteristic Vulcanian-type activity. In 2019, we started a comprehensive survey using a combination of field station records and repeated unoccupied aircraft system (UAS) surveys to describe the geomorphological features of the edifice and its evolution during ongoing activity. Seismic data revealed the activity of the volcano and were complemented by monitoring cameras, showing a mean explosion interval of 34 min. Digital terrain data generated from UAS quadcopter photographs allowed for the identification of the dimensions of the craters, a structural architecture and the tephra deposition at cm-scale resolution. The UAS was equipped with a thermal camera, which in combination with the terrain data, allowed it to identify fumaroles, volcano-tectonic structures and vents and generate a catalog of 282 thermal spots. The data provide details on a nested crater complex, aligned NNE-SSW, erupting on the northern rim of the former North Crater. Our catalog of thermal spots also follows a similar alignment on the edifice-scale and is also affected by topography on a local scale. This paper provides rare observations at Ebeko volcano and shows details on its Vulcanian eruption style, highlighting the relevance of structural and morphologic control for the geometry of craters and tephra fallout as well as for structurally controlled geothermal activity.

Description: Lava domes grow by extrusions and intrusions of viscous magma often initiating from a central volcanic vent, and they are frequently defining the source region of hazardous explosive eruptions and pyroclastic density currents. Thus, close monitoring of dome building processes is crucial, but often limited to low data resolution, hazardous access, and poor visibility. Here, we investigated the 2016–2017 eruptive sequence of the dome building Bezymianny volcano, Kamchatka, with spot-mode TerraSAR-X acquisitions, and complement the analysis with webcam imagery and seismic data. Our results reveal clear morphometric changes preceding eruptions that are associated with intrusions and extrusions. Pixel offset measurements show 〉7 months of precursory plug extrusion, being locally defined and exceeding 30 m of deformation, chiefly without detected seismicity. After a short explosion, three months of lava dome evolution were characterised by extrusions and intrusion. Our data suggest that the growth mechanisms were significantly governed by magma supply rate and shallow upper conduit solidification that deflected magmatic intrusions into the uppermost parts of the dome. The integrated approach contributes significantly to a better understanding of precursory activity and complex growth interactions at dome building volcanoes, and shows that intrusive and extrusive growth is acting in chorus at Bezymianny volcano.