Mapping Of Lava Flows Research Articles

Lava Mapping Using Sentinel-1 Data after the Occurrence of a Volcanic Eruption-The Case of Cumbre Vieja Eruption on La Palma, Canary Islands, Spain.

Volcanic eruptions pose a great threat to humans. In this context, volcanic hazard and risk assessment constitute crucial issues with respect to mitigating the effects of volcanic activity and ensuring the health and safety of inhabitants. Lava flows directly affect communities living near active volcanoes. Nowadays, remote sensing advances make it possible to effectively monitor eruptive activity, providing immediate and accurate information concerning lava evolution. The current research focuses on the mapping of the surface deformation and the analysis of lava flow evolution occurred on the island of La Palma, during the recent (2021) eruptive phase of the volcano. Sentinel-1 data covering the island were collected throughout the entire eruptive period, i.e., September 2021 until January 2022. The processing was based on amplitude-based and phase-based detection methods, i.e., Synthetic Aperture Radar interferometry (InSAR) and offset tracking. In particular, ground deformation occurred on the island, while Line-Of-Sight (LOS) displacements were derived from Sentinel-1 interferograms. Moreover, the evolution of lava flow velocity was estimated using Sentinel-1 imagery along with offset tracking technique. The maximum lava flow velocity was calculated to be 2 m/day. It was proved that both approaches can provide rapid and useful information in emergencies, especially in inaccessible areas. Although offset tracking seems a quite promising technique for the mapping of lava flows, it still requires improvement.

Lava flow mapping Karangetang Volcano during 2019 eruption using Sentinel-2 Images and Random Forest model

Karangetang is one of Indonesia’s most active volcanoes, located in northern Sulawesi. At least 200 people were evacuated due to the threat of lava during the nearly year-long eruption of 2019. In this study, we aim to map the lava flow using Sentinel-2 images. We used a random forest algorithm to separate lava and non-lava classes. Approximately 402 training points were visually interpreted from a pair of pre- and post-event images in 2019 classified as cloud, cloud shadow, bare land, settlement, vegetation, recent lava, and historical lava. To begin, we employed all bands and spectral indices previously identified as useful for separating lava from other materials. A region growing algorithm was used along with additional input data (temperature anomalies product, Normalized Hotspot Indices, and digital terrain model) to differentiate recent and old lava. Only the significant variables from the first run were kept that had a cumulative contribution to the model of greater than 10%. The top 6 important features are Digital Terrain Model, bands 11 and 12 (SWIR) of post-image and pre-image, and band 8A (NIR) of post-image. In the cross-validation of the Random Forest classification, our preliminary results indicate an accuracy of 97% for the test data (N-tree=100). The region’s growing algorithm helped distinguish between recent and historical lava. In the future, we intend to validate the map using an independent dataset and test the model at various locations

Petrogenetic implications of Fe–Mg substitution in clinopyroxene lattices of basaltic suites of Khandwa area, eastern Deccan volcanic province, Central India

Field investigations and lava flow mapping around Khandwa (21°49′ N:76°21′ E), Central India (within the eastern Deccan volcanic province) record three distinct lava flows which are in general, characterized by several structural zones, for example, Lower Vesicular Zone, Lower Colonnade Zone, Entablature Zone (EZ), Upper Colonnade Zone (UCZ), and Upper Vesicular Zone (UVZ). Different lava flows (often with chilled zones) in the field have been marked by discontinuous thin intertrappean beds. The occasional presence of chilled dyke and feeder dyke (both associated with Flow II) has also been noticed. The entire lava succession rests over coarse‐grained (cumulate) gabbroic (apparent) basement. Deduced clinopyroxene ordering clearly indicates that 100% initial ordering had been achieved for Flow II chilled zone, Flow II UCZ, Flow III UCZ, Flow III EZ, and cumulate gabbro. On the contrary, Flow II UCZ (97.35% initial ordering), feeder dyke (98.76% initial ordering), chilled dyke (99.82% initial ordering), and Flow I chilled zone (99.07% initial ordering) show initial clinopyroxene disordering (<100% ordering), which were later subjected to a gradual process to achieve ordering. Second‐order regression analyses clearly indicate that the progressive clinopyroxene ordering‐process is controlled by several differentiation parameters namely An% of coexisting plagioclase, lower thermometric values, and FeOt/MgO. In addition, roles of AlVI, Ti4+, and Fe3 were also suggested to influence the clinopyroxene ordering‐style. Based on Ti/6ox versus Al/6ox relation of clinopyroxene, it was deduced that cooling rate appreciably controls the clinopyroxene ordering‐behaviour. We contemplate that variation in clinopyroxene ordering‐pattern in basaltic rocks of Khandwa represents interplay of differentiation parameters and cooling rate of the ambient magma.

Detailed Mapping of Lava and Ash Deposits at Indonesian Volcanoes by Means of VHR PlanetScope Change Detection

Mapping of lava flows in unvegetated areas of active volcanoes using optical satellite data is challenging due to spectral similarities of volcanic deposits and the surrounding background. Using very high-resolution PlanetScope data, this study introduces a novel object-oriented classification approach for mapping lava flows in both vegetated and unvegetated areas during several eruptive phases of three Indonesian volcanoes (Karangetang 2018/2019, Agung 2017, Krakatau 2018/2019). For this, change detection analysis based on PlanetScope imagery for mapping loss of vegetation due to volcanic activity (e.g., lava flows) is combined with the analysis of changes in texture and brightness, with hydrological runoff modelling and with analysis of thermal anomalies derived from Sentinel-2 or Landsat-8. Qualitative comparison of the mapped lava flows showed good agreement with multispectral false color time series (Sentinel-2 and Landsat-8). Reports of the Global Volcanism Program support the findings, indicating the developed lava mapping approach produces valuable results for monitoring volcanic hazards. Despite the lack of bands in infrared wavelengths, PlanetScope proves beneficial for the assessment of risk and near-real-time monitoring of active volcanoes due to its high spatial (3 m) and temporal resolution (mapping of all subaerial volcanoes on a daily basis).

Combining Radar and Optical Satellite Imagery with Machine Learning to Map Lava Flows at Mount Etna and Fogo Island

Lava flow mapping has direct relevance to volcanic hazards once an eruption has begun. Satellite remote sensing techniques are increasingly used to map newly erupted lava, thanks to their capability to survey large areas with frequent revisit time and accurate spatial resolution. Visible and infrared satellite data are routinely used to detect the distributions of volcanic deposits and monitor thermal features, even if clouds are a serious obstacle for optical sensors, since they cannot be penetrated by optical radiation. On the other hand, radar satellite data have been playing an important role in surface change detection and image classification, being able to operate in all weather conditions, although their use is hampered by the special imaging geometry, the complicated scattering process, and the presence of speckle noise. Thus, optical and radar data are complementary data sources that can be used to map lava flows effectively, in addition to alleviating cloud obstruction and improving change detection performance. Here, we propose a machine learning approach based on the Google Earth Engine (GEE) platform to analyze simultaneously the images acquired by the synthetic aperture radar (SAR) sensor, on board of Sentinel-1 mission, and by optical and multispectral sensors of Landsat-8 missions and Multi-Spectral Imager (MSI), on board of Sentinel-2 mission. Machine learning classifiers, including K-means algorithm (K-means) and support vector machine (SVM), are used to map lava flows automatically from a combination of optical and SAR images. We describe the operation of this approach by using a retrospective analysis of two recent lava flow-forming eruptions at Mount Etna (Italy) and Fogo Island (Cape Verde). We found that combining both radar and optical imagery improved the accuracy and reliability of lava flow mapping. The results highlight the need to fully exploit the extraordinary potential of complementary satellite sensors to provide time-critical hazard information during volcanic eruptions.

Basalt lava flows of the intraplate Newer Volcanic Province in south-east Australia (Melbourne region): 40Ar/39Ar geochronology reveals ~8 Ma of episodic activity

Intraplate basaltic volcanism is one of the most common, yet poorly understood, types of volcanism. Intraplate continental basaltic volcanic provinces (ICBVPs) typically comprise tens to hundreds of usually monogenetic, small-volume eruption centres, often cumulatively producing significant volumes of mainly primitive basaltic magmas. A wide range of mechanisms have been invoked to account for ICBVP melt generation, ranging from deep mantle plumes to local tectonic perturbations of the lithospheric mantle. The key to understanding the cause(s) of intraplate volcanism is understanding the geochemical evolution of magmatism within a regional tectonic framework. Unfortunately, many ICBVPs contain complex arrays of overlying lava flows, with uncertain eruption sources and a lack of precise age constraints.The Newer Volcanic Province (NVP) in south-eastern Australia is a young (~4.6 Ma–5 ka), geochemically and volcanologically diverse ICBVP, comprising ≥416 volcanic centres covering an area of ~23,000 km2. As with other ICBVPs, elucidating the underlying controls on magmatism has proved contentious, with recent studies favouring edge-driven convection, but divided as to the changing nature of volcanism. At the eastern boundary of the NVP, in the Melbourne area, previous work has indicated a complex network of lava flows representing almost the entire age and geochemical range of the NVP, making this an ideal microcosm for studying the evolution of the NVP.In this study, a holistic approach to lava flow mapping is utilised to unravel the complex network, incorporating diagnostic petrography, geochemistry and precise 40Ar/39Ar geochronology. This work reveals seven major lava flows, here named the Tullamarine, Redstone Hill, Aitken Hill, Mount Kororoit, Fenton Hill, Tulloch Hill and Mount Fraser flows, along with eight smaller-volume flows, here named the Pretty Sally, Green Hill, Bald Hill, Mount Cooper, Mount Ridley, Crowe Hill, Springs Hill and Summerhill Road flows. 40Ar/39Ar ages for eleven lava flows and eruption centres span an age range of 7.9–0.8 Ma. These new data reveal that alkalic, small-volume eruptions in the Melbourne area occurred exclusively between ~8 and 3.8 Ma. Post ~3.8 Ma, large-volume, tholeiitic eruptions dominated. A local progression from alkalic to tholeiitic volcanism is contrary to a province-wide progression from tholeiitic to alkalic volcanism inferred by previous studies.The earliest four eruptions (ca. 8 Ma) were aligned with the Cosgrove hotspot track and are probably unrelated to the broader NVP. The ages and geochemical variations of the younger flows are consistent with melt generation due to edge-driven convection. Magma composition might have been controlled by local perturbations within the convective cell, with tholeiitic magmas generated during high-degree melting in regions of more intense upwelling, and alkalic melts reflecting lower-degree melting and less-intense upwelling. The episodic nature of volcanism is likely due to restricted magma transport to the surface, which was only possible during brief periods of favourable tectonic conditions.

3D Lava flow mapping of the 17–25 May 2016 Etna eruption using tri-stereo optical satellite data

During basaltic eruptions, the average rate at which lava is erupted (effusion rate) is one of the most important factor controlling the evolution, growth and extent of the flow field. This has implication both for forecasting purposes as input parameter into physics-based numerical models, and for advancing knowledge on the shallow feeder system by constraining the mass supplied. Satellite remote sensing provides a means to estimate the average effusion rate by applying a direct conversion from the measured radiant heat loss by an active lava flow. This conversion relies on a set of parameters of lava (e.g. rock density, heat capacity, vesicularity, emissivity, etc.) and suffers of multiple sources of uncertainties and measurements errors, whose quantification is still an open problem. Here we constrain the lava volume emitted at Mt Etna on 17-25 May 2016, by using pre-eruptive and post eruptive digital elevation models (DEMs) obtained processing satellite images acquired by the Pleiades constellation, which provides images at 50 cm resolution in stereo and tri-stereo mode. The 3D processing of the tri-stereo Pleiades imagery (acquired on 24 December 2015 and 18 July 2016), performed using the free and open source MicMac photogrammetric library provides estimations of the distribution of thickness and the bulk volume emitted. The integration of multi-platform remote sensing products represents a new potential of merging capabilities to enable a more comprehensive response to effusive crises.

The Use of Surveillance Cameras for the Rapid Mapping of Lava Flows: An Application to Mount Etna Volcano

In order to improve the observation capability in one of the most active volcanic areas in the world, Mt. Etna, we developed a processing method to use the surveillance cameras for a quasi real-time mapping of syn-eruptive processes. Following an evaluation of the current performance of the Etna permanent ground NEtwork of Thermal and Visible Sensors (Etna_NETVIS), its possible implementation and optimization was investigated to determine the locations of additional observation sites to be rapidly set up during emergencies. A tool was then devised to process time series of ground-acquired images and extract a coherent multi-temporal dataset of georeferenced map. The processed datasets can be used to extract 2D features such as evolution maps of active lava flows. The tool was validated on ad-hoc test fields and then adopted to map the evolution of two recent lava flows. The achievable accuracy (about three times the original pixel size) and the short processing time makes the tool suitable for rapidly assessing lava flow evolutions, especially in the case of recurrent eruptions, such as those of the 2011–2015 Etna activity. The tool can be used both in standard monitoring activities and during emergency phases (eventually improving the present network with additional mobile stations) when it is mandatory to carry out a quasi-real-time mapping to support civil protection actions. The developed tool could be integrated in the control room of the Osservatorio Etneo, thus enabling the Etna_NETVIS for mapping purposes and not only for video surveillance.

The 1928 eruption of Mount Etna (Italy): Reconstructing lava flow evolution and the destruction and recovery of the town of Mascali

Mount Etna in Sicily (Italy) shows >2500years of interactions between volcanic eruptions and human activity, and these are well documented in historical sources. During the last 400years, flank eruptions have had major impacts on the urban fabric of the Etna region, especially in 1651–54, 1669, 1923 and 1928, and it is the last of these which is the focus of this paper. A detailed field and historical reconstruction of the 1928 eruption is presented which allows three themes to be discussed: the evolution of the flow field, lava volume and average magma discharge rate trend; the eruption's human impact, particularly the destruction of the town of Mascali; and the recovery of the region with re-construction of Mascali in a new location. Detailed mapping of lava flows allowed the following dimensions to be calculated: total area, 4.38×106m2; maximum length, 9.4km; volume, 52.91±5.21×106m3 and an average effusion rate of 38.5m3s−1. Time-averaged discharged rates are calculated allowing the reconstruction of their temporal variations during the course of the eruption evidencing a high maximum effusion rate of 374m3s−1. These trends, in particular with regard to the Lower Fissure main phase of the eruption, are in accordance with the ‘idealized discharge model’ of Wadge (1981), proposed for basaltic eruptions driven by de-pressurization of magma sources, mainly through reservoir relaxation (i.e. elastic contraction of a magma body). The eruption took place when Italy was governed by Mussolini and the fascist party. The State response both, during and in the immediate aftermath of the eruption and in the years that followed during which Mascali was reconstructed, was impressive. This masked a less benign legacy, however, that can be traced for several subsequent decades of using responses to natural catastrophes to manufacture State prestige by reacting to, rather than planning for, disasters.

Geomorphology Analysis of Lava Flow of Mt. Guntur in West Java Using Synthetic Aperture Radar (SAR) with Fully Polarimetry

Mt. Guntur is one of active volcanoes in Indonesia, which has a very unique product of lava flows than other volcanoes. In order to minimize the adverse effects of volcanic eruptions of Mt. Guntur, one mitigation measure that can be done is to map the volcano landform through geomorphological analysis and identification of lava flow characteristics. It is very obvious that Mt. Guntur lava flow is visible and clear so it is possible to do the landform lava flow mapping. However, this kind of study is very rare especially in Indonesia. Thus, this research aims to analyse the geomorphologic and identify lava flows using high-resolution optical imagery through characterization (signature) landforms by using L band SAR polarimetry backscattering in combination with decision tree classification techniques using the QUEST algorithm (Quick, Unbiased, Efficient Statistical Trees). Moreover, the accuracy of the classification results is calculated using matrix analysis accuracy and Kappa coefficient calculation. In addition, the characterization of the object is also performed using analysis of spectral separation. The analysis showed that the geomorphological analysis can be used for volcanic (V) landforms mapping based on morfocronologi aspect. The identification of the image depends on the spatial resolution of the image. The objects were identified using IKONOS imagery, Google Earth, and PALSAR imagery. The results of showed that the HV and VV polarization serves as the best combination to identify the lava flows. Classification results showed a good accuracy value which is 51.80% with a Kappa coefficient of 0.43. This suggests that the identification of a lava flow using linear polarization combined with decision tree classification has a good level of confidence.

Geologic Map of Kalaupapa Peninsula, Moloka‘i, Hawai‘i, USA

Kalaupapa Peninsula, along the northern coast of East Moloka‘i volcano, is a remarkably well-preserved example of rejuvenated-stage volcanism from a Hawaiian volcano. Mapping of lava flows, vents and other volcanic constructs reveals a diversity of landforms on this small monogenetic basaltic shield. The late-stage lava distributary system of this shield is dominated by a prominent lava channel and tube system emanating from the primary vent, Kauhakō crater. This system, along with several smaller examples, fed five prominent rootless vents downslope from Kauhakō. This map shows the subaerial part of this volcanic construct at 1:30,000 scale and encompasses an area of approximately 20.6 km2.

Tracking lava flow emplacement on the east rift zone of Kīlauea, Hawai‘i, with synthetic aperture radar coherence

Lava flow mapping is both an essential component of volcano monitoring and a valuable tool for investigating lava flow behavior. Although maps are traditionally created through field surveys, remote sensing allows an extraordinary view of active lava flows while avoiding the difficulties of mapping on location. Synthetic aperture radar (SAR) imagery, in particular, can detect changes in a flow field by comparing two images collected at different times with SAR coherence. New lava flows radically alter the scattering properties of the surface, making the radar signal decorrelated in SAR coherence images. We describe a new technique, SAR Coherence Mapping (SCM), to map lava flows automatically from coherence images independent of look angle or satellite path. We use this approach to map lava flow emplacement during the Pu‘u ‘Ō‘ō‐Kupaianaha eruption at Kīlauea, Hawai‘i. The resulting flow maps correspond well with field mapping and better resolve the internal structure of surface flows, as well as the locations of active flow paths. However, the SCM technique is only moderately successful at mapping flows that enter vegetation, which is also often decorrelated between successive SAR images. Along with measurements of planform morphology, we are able to show that the length of time a flow stays decorrelated after initial emplacement is linearly related to the flow thickness. Finally, we use interferograms obtained after flow surfaces become correlated to show that persistent decorrelation is caused by post‐emplacement flow subsidence.

Temperature distribution analysis of July 2001 Mt. Etna eruption observed by the airborne hyperspectral sensor MIVIS

On 17th and 18th July 2001, several fractures opened on Mt. Etna southern flank generating different lava flows spreading both in Valle del Bove and towards Nicolosi. On 29th July the image spectrometer MIVIS was flown over Mt. Etna to acquire high-resolution images of the eruption. The MIVIS airborne campaign was planned simultaneously with TERRA, EO-1 and Landsat 7 satellite acquisitions, in order to compare hyperspectral and multispectral data referred to active lavas. This work focuses on the thermal mapping of lava flows, taking advantage of MIVIS sensor high technical performances. The MIVIS high spatial resolution allows a detailed analysis of the lava flow topographic distribution. Its 12 bit dynamic range consents an estimate of the temperature even for the «hottest» pixels. The main target of this work is the evaluation of the energy flux by means of remote-sensing techniques. Surface temperature analysis was performed on distinct lava flows using the dualband technique. These quantities were compared with the integrated temperatures retrieved using the MIVIS thermal infrared bands. The influence of topography was also considered in the flux calculation using a Digital Elevation Model (DEM) of Mt. Etna.

Olympus Mons, Mars: Inferred changes in late Amazonian aged effusive activity from lava flow mapping of Mars Express High Resolution Stereo Camera data

Lava flow mapping was conducted on a north‐south transect of Olympus Mons using the European Space Agency's Mars Express High Resolution Stereo Camera (HRSC) image H0037. The HRSC image was coregistered to Mars Orbiter Laser Altimeter, Thermal Emission Imaging System, and Mars Orbiter Camera data, enabling lava flow structures to be differentiated and mapped consistently across the shield. Because different structures develop as a result of different effusive conditions, their abundance and distribution provide insight into the eruptive history of a shield volcano. Results show that lava channels are the dominant flow structure, whereas tabular sheets are most common beyond the basal scarp. A hummocky unit dominates the summit area and likely represents a combination of (1) volcanic lava flows, (2) pyroclastic deposits, (3) a dust mantle, and (4) frozen volatiles, all of which have been suggested to exist on Olympus Mons in the past. Lava fans are typically associated with lava tubes, indicating that they represent tube outbreaks as was previously suggested as one possible formation mechanism. No vents were identified, suggesting that major rift zones have not developed on the north or south flank. Younger channel‐fed flows typically embay older tube‐related flows, which they outnumber by a ratio of 5:1. Therefore Olympus Mons likely experienced a change in eruptive style from longer‐lived, stable, tube‐forming eruptions to shorter‐lived, less stable, channel‐forming eruptions in the late Amazonian. A similar trend exists for the Hawaiian volcanoes in which a decrease in the magma production rate drives a change to dominantly channel forming eruptions associated with increased shield age.

Deformation between 1989 and 1997 at Piton de la Fournaise volcano retrieved from correlation of panchromatic airborne images

We processed two panchromatic airborne images in the attempt to measure deformation on Piton de la Fournaise volcano between 1989 and 1997. Piton de la Fournaise erupted three times during 1989-1997 with fissures opening near Dolomieu summit crater. During this period no Synthetic Aperture Radar Interferometry data were available and only few geodetic points surveyed the summit crater. We therefore, apply for the first time the subpixel image-correlation technique on airborne images for monitoring ground deformation on Piton de la Fournaise volcano. Correlogram analysis reveals cumulative deformation in the summit area. We observe ESE spreading of the summit caused by the inflation-deflation cycle during 1989-1997. We calculated relative ground displacement along both sides of the main eruptive fissures, finding a maximum of 1.8 (±0.42) m opening. Direct comparison between deformation retrieved by correlation and available geodetic data at four locations shows qualitative agreement. We demonstrate the potential of subpixel image correlation technique, using panchromatic airborne images, for deformation monitoring on volcanoes. We also illustrate the capability of this technique for remote lava flow mapping.

Mapping of lava flows through SPOT images an example of the Sabancaya volcano (Peru)

SPOT XS and Panchromatic images are used jointly in order to map the lava flows of the Nevado Sabancaya volcano (southern Peru). This mapping is achieved through two types of processing: the unsupervised multispectral clustering applied to the XS image, and some specific methods of image analysis (mathematical morphology, convolution filtering) applied to the Panchromatic image. The resulting images allowed us to identify flows and the two main morphological features of the flow areas: lava reliefs and flow lines. Therefore, our experience shows that image analysis can be a tool for thematic mapping which displays more capabilities than photointerpretation.

Relative dating of Hawaiian lava flows using multispectral thermal infrared images: A new tool for geologic mapping of young volcanic terranes

The weathering of Hawaiian basalts in arid and semiarid environments is accompanied by change in their thermal infrared emittance spectra. The spectral differences can be measured and mapped with multispectral imaging systems. The differences appear to be related to the degree of development, preservation, and alteration of glassy crusts; the oxidation of iron; and the accretion of silica‐rich surface veneers. Because the measurements are quantitative and in image format, they are useful for estimating relative ages in geologic mapping of lava flows. In Hawaii this technique is most diagnostic for distinguishing among sparsely vegetated flows less than 1.5 ka in age.