ArticlePDF Available

Abstract and Figures

Structure-from-motion (SfM) algorithms greatly facilitate the generation of 3-D topographic models from photographs and can form a valuable component of hazard monitoring at active volcanic domes. However, model generation from visible imagery can be prevented due to poor lighting conditions or surface obscuration by degassing. Here, we show that thermal images can be used in a SfM workflow to mitigate these issues and provide more continuous time-series data than visible counterparts. We demonstrate our methodology by producing georeferenced photogrammetric models from 30 near-monthly overflights of the lava dome that formed at Volcán de Colima (Mexico) between 2013 and 2015. Comparison of thermal models with equivalents generated from visible-light photographs from a consumer digital single lens reflex (DSLR) camera suggests that, despite being less detailed than their DSLR counterparts, the thermal models are more than adequate reconstructions of dome geometry, giving volume estimates within 10% of those derived using the DSLR. Significantly, we were able to construct thermal models in situations where degassing and poor lighting prevented the construction of models from DSLR imagery, providing substantially better data continuity than would have otherwise been possible. We conclude that thermal photogrammetry provides a useful new tool for monitoring effusive volcanic activity and assessing associated volcanic risks.
Content may be subject to copyright.
Thermal Photogrammetric Imaging: A New Technique for Monitoring
Dome Eruptions
Samuel T. Thielea,b*, Nick Varleya & Mike R. Jamesc
aColima Intercambio e Investigación en Vulcanología, Universidad de Colima, av. Universidad 333, Las
Viboras C.P. 28040, Colima, México
bSchool of Earth, Atmosphere and Environment, Monash University, Clayton VIC 3800, Australia
cLancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
*Corresponding Author:
Structure-from-motion (SfM) algorithms greatly facilitate the generation of 3-D topographic models
from photographs and can form a valuable component of hazard monitoring at active volcanic domes.
However, model generation from visible imagery can be prevented due to poor lighting conditions or
surface obscuration by degassing. Here, we show that thermal images can be used in a SfM workflow
to mitigate these issues and provide more continuous time-series data than visible-light equivalents.
We demonstrate our methodology by producing georeferenced photogrammetric models from 30
near-monthly overflights of the lava dome that formed at Volcán de Colima (Mexico) between 2013
and 2015. Comparison of thermal models with equivalents generated from visible-light photographs
from a consumer digital single lens reflex (DSLR) camera suggests that, despite being less detailed than
their DSLR counterparts, the thermal models are more than adequate reconstructions of dome
geometry, giving volume estimates within 10% of those derived using the DSLR.
Significantly, we were able to construct thermal models in situations where degassing and poor
lighting prevented the construction of models from DSLR imagery, providing substantially better data
continuity than would have otherwise been possible. We conclude that thermal photogrammetry
provides a useful new tool for monitoring effusive volcanic activity and assessing associated volcanic
Key words: Lava Dome, Photogrammetry, Thermal Imaging, Volcán de Colima
1. Introduction
Lava domes are known to pose significant volcanic hazards, due to their tendency to generate collapse
related pyroclastic flows and their association with explosive eruptions (Fink and Anderson, 2000). For
example, successive dome collapses at Soufrière Hills on the island of Montserrat, starting in 1995,
caused the evacuation and eventual abandonment of the capital Plymouth and surrounding areas
(Wadge et al., 2014), while the 1994 collapse of Mount Merapi (Indonesia) resulted in 95 deaths and
damage to several villages (Abdurachman et al., 2000). A similar event at Volcán de Colima in 2015
generated pyroclastic flows that travelled ~10 km, fortunately causing only minor damage.
Monitoring of dome geometry (e.g. volume and height), growth rate and deformation is key to
forecasting such dome collapse events (Voight, 2000), and photogrammetry and structure from
motion (SfM) are increasingly being used for this purpose (e.g. Herd et al., 2005; Ryan et al., 2010;
Diefenbach et al., 2012; James and Varley, 2012; Diefenbach et al., 2013). Using these techniques,
morphological and geometric data can be safely and inexpensively acquired, and used to track
eruption progress, identify signs of instability or changes in effusion rate, and forecast changes in
volcanic risk. These methods, however, rely on clear viewing conditions and so are highly sensitive to
degassing, cloud and poor lighting conditions.
Thermal imaging techniques are also widely used for monitoring purposes (Spampinato et al., 2011),
as they allow quantitative evaluation of heat flux from volcanic vents (e.g. Harris and Stevenson, 1997;
Sahetapy-Engel et al., 2008), domes (e.g. Hutchison et al., 2013; Pallister et al., 2013), flows (e.g.
Calvari et al., 2003; James et al., 2006) and fumaroles (e.g. Stevenson and Varley, 2008; Harris et al.,
2009). Importantly, the spatial distribution of heat flux can reveal features that are difficult to detect
using reflected visible light, such as fumaroles, fractures and rock fall traces (Hutchison et al., 2013;
Mueller et al., 2013).
Changes in the distribution and intensity of thermal anomalies can also precede volcanic eruptions or
changes in eruptive style (Spampinato et al., 2011) and thus have potential for hazard forecasting.
However, to facilitate inter-survey comparisons, thermal data need to be spatially referenced, and
producing orthorectified thermal maps usually requires additional topographic data, knowledge of the
camera location and viewing direction (e.g. James et al., 2006; James et al., 2009; Lewis et al., 2015).
This study demonstrates a method for deriving topographic data and georeferenced thermal maps
directly from oblique thermal imagery using SfM techniques and imagery captured during an episode
of dome growth at Volcán de Colima (Mexico) between 2013 and 2015. We suggest that the resulting
three-dimensional thermal models provide intuitive and georeferenced representations of dome
surface temperature and valuable measurements of dome geometry. Furthermore, we demonstrate
that despite the lower spatial resolution of thermal images, dome volume estimates are comparable
to those estimated using SfM reconstructions deriving from visible-light digital single lens reflex (DSLR)
photographs, and that unlike the DSLR models, the thermal models can be constructed during periods
of poor lighting and extensive degassing.
Volcán de Colima is an andesitic and frequently erupting stratovolcano, located at the western limit
of the Trans-Mexican Volcanic Belt. During the most recent eruptive periods, six episodes of dome
growth have been observed at the volcano (19981999, 20012003, 2004, 20072011, 20132015
and an ongoing episode initiated in February 2016). This represents the most active period at the
volcano since its last catastrophic eruption in 1913. A range of effusion rates have been estimated,
with the longer-lived eruptions associated with rates as low as 0.01 m3 s-1. During the current eruption
the volcano has exhibited the continuous generation of small Vulcanian explosions with a frequency
of the order of hours. Larger magnitude explosions usually follow periods of dome emplacement,
which re-excavate the summit crater.
The episode of dome growth investigated in this study began in January 2013 when lava erupted into
the base of a ~150 m wide and ~50 m deep crater formed (by several large explosions that same
month) on top of a previous (2007 to 2011) lava dome. The new dome proceeded to fill this crater and
by April 2013 overflowed to form several lava flows and eventually fill the entire summit crater (~300
m across). Several partial collapses (accompanied by increased volcanic activity) resulted in dome
destruction on 10 11 July 2015; pyroclastic density currents generated by these collapses travelled
up to ~10.6 km along the ravine of Montegrande, threatening several ranches and the town of
Quesaría (pop. 8611 in 2010). This eruption was the largest (by volume) at Volcán de Colima since
2. Methods
2.1. Image capture and pre-processing
Images (Fig. 1) were acquired using a consumer DSLR (Nikon D90) and a thermal camera (Jenoptik
VarioCAM HiRes) from a light aircraft during 30 observation flights, conducted at intervals of
approximately one month. The DSLR had an 18105 mm zoom lens (most images were captured using
the 105 mm setting), while the thermal camera used a 75 mm fixed-focal lens. Thermal images had an
order of magnitude lower resolution than the DSLR images (640×480 pixels and 4288×2848 pixels
Observational flights involved 23 circuits around the crater at a slightly higher elevation than the
summit. Typical viewing distances varied between ~13 km, corresponding to ground sampling
distances of ~5-15 cm/pixel for the DSLR camera (at full zoom) and ~25-75 cm/pixel for the thermal
camera. Both cameras were operated by hand, with DSLR photographs captured every ~510 seconds
and the thermal camera programmed to take an image every 3.5 seconds.
Blurry and poorly exposed images were manually removed from the resulting image sets (of ~100
DSLR images and ~200400 thermal images) prior to photogrammetric processing. Normally, ~5075
DSLR images and ~100200 thermal images were considered usable, though this varied substantially
with viewing conditions.
The thermal images were converted from Jenoptic’s proprietary IRB format to JPEG (using a colour
scale selected to maximise the amount of detail visible on the dome and volcanic flanks) before
photogrammetric processing. A second set of JPEG images were additionally created from the thermal
images using a fixed colour scale, and later projected onto the photogrammetric model to create a
thermal texture map that can be compared between models.
Figure 1. Examples of typical DSLR (left) and thermal (right) images from two different observation
flights. Both views are looking to the north-west, and the summit region is ~300 m across.
2.2. Structure from Motion
Photogrammetric processing of both the DSLR and thermal datasets was performed using Agisoft
Photoscan Professional Edition (v1.2.3). Prior to 3D reconstruction, both photosets were masked to
remove degassing plumes, aircraft parts and unnecessary background, ensuring that only the edifice
region was reconstructed. SfM methods were applied to estimate camera locations, orientations and
internal parameters and produce a ‘sparse point cloud’ containing the location of tens of thousands
of automatically detected features. These data were then used to constrain a detailed reconstruction
of the volcanic edifice, producing a ‘dense point cloud’ typically containing 10 20 million points for
the DSLR models and ~0.5 million points for the thermal models.
Finally, a continuous triangulated surface model was derived from the dense point cloud for image
rendering. For practical reasons, we limited the model to 1 million triangles, prior to texturing by
projecting the original images onto its surface. For the thermal models, the photoset used to construct
the model was exchanged with the photoset with a consistent colour-scale prior to the texturing step.
2.3. Georeferencing and Alignment
Due to difficult access and high risk, ground control points were not available for any of the models.
Instead, similar to the approach used by James and Varley (2012), models generated from the DSLR
images were georeferenced (within Agisoft Photoscan) by minimising the distance between features
identified on the models and equivalent features located in Google Earth imagery. Here, we
additionally used 1-arc second SRTM (Shuttle Radar Topographic Mission) data from February 2000 to
derive elevations. As the morphology of the summit area changed substantially over the study period,
it was necessary to use Google Earth imagery from different dates for some models, causing relative
translations of the results (reflecting the georeferencing error within Google Earth; coordinates of
some static features changed by >20 meters between imagery from different dates).
To improve the registration between models and facilitate direct comparisons, the relative
georeferencing of each model was optimised by aligning to one reference model (from 11 January
2013) using the iterative closest point (ICP) alignment implementation in Cloud Compare (Girardeau-
Montaut, 2015). Model location, orientation and scale was allowed to vary during this step, during
which areas known to have changed (i.e. the dome and associated flows) were manually excluded.
Models constructed using thermal images could not generally be georeferenced from the Google
Earth imagery due to difficulties identifying corresponding features in the thermal data. Instead, they
were aligned to the DSLR model from the same flight (or from a previous flight if the DSLR model had
failed), using a manual 3-D point-matching approach in Meshlab (Cignoni et al., 2008) to achieve an
initial alignment that was then optimised using ICP.
Where possible, the similarity (and alignment) of the DSLR and thermal models was assessed by
comparison with DSLR models generated from the same flight. As the ICP alignment algorithm only
applies a scaling and rigid body transformation, similarities between the DSLR and thermal models
suggest that the photogrammetric reconstructions converge on a consistent surface shape, adding
confidence to the results. Note that while this assessment provides an indication of uncertainty in the
overall model shapes, it cannot evaluate the full geospatial uncertainty because the thermal models
are not independently georeferenced.
2.4. Volume Calculation
Dome volume was estimated by determining the difference between each photogrammetric model
and the pre-dome reference model created photogrammetrically using data from a flight on 11
January 2013. The difference calculations (performed using a Java implementation of the signed
tetrahedral method; Zhang and Chen, 2001) determined the volume between the surfaces in up to
four ‘regions of interest’ (ROI; Fig. 2). In this instance, a ROI containing the lava dome was defined for
each of the photogrammetric models (both DSLR and thermal), and the volume of the dome estimated
by comparison with a reference surface representing the pre-dome topography. Where the dome
overflowed the crater (and transitioned into a lava flow), a consistent (but visually estimated) ‘dome
boundary’ was defined (the boundary between regions a and b in Fig. 2), and the volume of the upper
portion of a lava flow was also determined.
In order to better evaluate the uncertainty of the volume estimates, change within two stable
reference areas on the flanks of the volcano was also calculated; because these areas should not vary,
detecting volume change within them suggests greater uncertainty in the topographic models or their
relative registration. These changes were expressed as mean vertical offsets that could then be used
to estimate the dome volume (positive or negative) that likely resulted from alignment errors. Note
however, that these reference areas were always located on the eastern flanks of the volcano, as the
western flanks changed substantially over the study period (due to lava flows), and hence are not
equally sensitive to all types of alignment error (e.g. translations or rotations) in dome area.
Figure 2: Oblique view of the ‘regions of interest’ defined for the 27/4/13 photogrammetric model.
Region (a) contains the growing lava dome, and (b) the incipient lava flow. Regions (c) and (d) are the
reference areas. The colour map represents the vertical distance between the comparison and
reference surfaces. The dome region (a) is ~140 m across.
3. Results and Discussion
The 30 survey flights allowed the construction of 19 usable models from visible imagery and 22 models
from the thermal imagery, although thermal data was only available for 23 flights. These datasets
provide a reconstruction of the summit lava dome geometry at ~monthly intervals for the entire
dome-forming eruption.
3.1. Comparison of Thermal and DSLR models
Both sets of photogrammetric models (thermal and DSLR) reconstructed the crater and dome complex
on Volcán de Colima with varying degrees of completeness, detail and accuracy (Fig. 3). It is clear that,
in general, models constructed using the thermal images were substantially less detailed than DSLR
equivalents. This will be due to a combination of the thermal images having a lower spatial resolution
than the DSLR images and a lack of high-frequency image texture, due to low thermal contrast on the
volcano flanks.
Figure 3. Selected DSLR and thermal photogrammetric models illustrated by hillshade (top and middle),
and associated thermal orthomosaics (bottom). Grid cells are 50×50 m and oriented north-south and
east-west. The model shown in (a) was captured before lava dome growth and was used as the
reference model in volume calculations.
Nevertheless, 3D reconstruction using the thermal images was found to be far more robust to poor
photography conditions than the DSLR models. In particular, thermal models could be constructed in
situations where degassing made useful reconstruction from the DSLR images impossible. This is
because water droplets in the degassing plume cause near complete scattering of visible light (and
hence the plumes appear white), whilst the thermal infrared radiation (7.5-14 μm) is less affected (Fig.
4). Of all flights for which both thermal and DSLR data was available, ~30% of the DSLR surveys failed
to generate a model while only ~5% of the thermal models failed, even though image locations and
overlap were approximately the same. Hence, in addition to providing a useful map of estimated
temperature across the crater complex, the thermal models provide greater data continuity than the
models from the DSLR.
Figure 4. Thermal (a) and DSLR (b) images captured at approximately the same time and location
(looking towards the east), under strong degassing conditions. The dome is generally resolvable in the
thermal image, but is substantially obscured in the DSLR image. A photogrammetric model of the dome
was successfully reconstructed from the thermal images, and is of particular importance as it was
captured on 5/7/15, days before the major July 2015 eruption. A model was not attempted using the
DSLR data due to the degassing.
Shortest distance comparisons between associated DSLR and thermal models show generally good
agreement (Fig. 5a and b). As thermal models tend to be smoother than the DSLR models (Fig. 3),
differences tend to be focused around sharp topographic features such as the crater rim. However,
in a few cases, the thermal models did differ significantly from their DSLR counterparts (Table 1). The
largest dome volume difference was observed at the time when the dome area was largest (Fig. 5b),
but the second largest observed dome volume difference resulted from the thermal model locating
the dome surface ~5 m higher than the DSLR model (Fig. 5c). The reason for this difference is
unclear, but highlights our ability to identify uncertainty by comparing the different datasets. A few
of the thermal models also contained substantial error (±10 m; Fig. 5d), which was mostly apparent
in areas of low thermal contrast, where image alignments and surface reconstructions are likely to
be weakest. Although the active lava surfaces were not directly influenced by this effect, the noisy
surfaces did impair the ICP process and probably increased registration error.
Figure 5. The shortest distance between corresponding DSLR and thermal models. Regions where the
thermal model is above the DSLR model are yellow-red, while areas where the DSLR model is on top
are shaded green-blue. Histograms showing the distribution of the difference values are shown below
each map. Examples of typical models are shown in (a) and (b), with few large differences except along
sharp features (e.g. the crater rim) and towards model boundaries. Examples of models showing
greater differences are presented in (c) and (d), where reconstructed dome geometries do not match
well (c) or where substantial error is present (d).
Table 1: The five largest differences between the thermal and DSLR volume estimates. Volumes and
differences are in million m3. Percentages are relative to the DSLR volume estimate.
DSLR Volume
Thermal Volume
% Difference
Using consumer cameras, and in the absence of ground control points sufficient to help constrain
photogrammetric processing, SfM-based data have been previously shown to provide topographic
data with an overall precision of ~1/1000 of the viewing distance (James and Robson, 2012). Thus,
over viewing distances of ~1-3 km, the 1-5 m differences between models are in line with this rule of
thumb. These results are reasonable given the low resolution of the thermal camera and the relatively
narrow angular field of view of both cameras (12° for the DSLR camera at full zoom and 10° for the
thermal camera), which can cause difficulties for precise photogrammetric reconstruction. It is likely
that the orbital flight paths play a strong role in helping to reduce error by naturally providing
convergent imagery, which mitigates systematic model deformation effects when ground control
points cannot be incorporated into the photogrammetric processing (Wackrow and Chandler, 2008;
James and Robson, 2014).
3.2. Dome volume calculations
Dome volumes calculated independently using the DSLR and thermal models generally correspond
well (Fig. 6), and differ by <10%. Likewise, the volume difference within the reference areas tended to
be small, averaging 5% of the dome volume estimates.
While the volcanological significance and the implications of these results for understanding the 2013
2015 eruption are beyond the scope of this paper, it is clear that they provide valuable information
on phases of dome growth (and volume loss) at Volcán de Colima between 2013 and 2015 (Fig. 6).
Average effusion rates could also be estimated from the rate of dome volume change, although the
effect of volume loss through explosive activity and lava flows would need to be accounted for.
Finally, where both DSLR and thermal models were successful, the two independent reconstructions
also provide a valuable indication of uncertainty in model shape. Future studies could extend this
approach and use GPS devices to “geotag” image locations at the time of capture, allowing additional
evaluation of georeferencing uncertainty as the thermal models would no longer rely on ICP
registration against a similar visible-light model for their georeferencing. For high quality camera
position data, this ‘direct georeferencing’ approach has been shown capable of delivering decametric
accuracies (Nolan et al., 2015). Alternatively, where sufficient topographic features are recognisable
in the thermal models, a single georeferenced model or high resolution digital elevation model of
known accuracy could be used for georeferencing, avoiding the need for closely associated DSLR
Figure 6. Volume of the lava dome (dotted) and lava flow top (dashed) between initiation of dome
growth in January 2013 and dome collapse in July 2015. Where both DSLR (squares) and thermal
(circles) models were available, the lines represent an average estimate. It is clear that there is
generally good agreement between volumes calculated with the DSLR and thermal models. Reference
area volumes (which would be zero under error-free conditions) are shown in grey to give an indication
of relative accuracy.
4. Conclusions
We have successfully used SfM techniques and oblique thermal images to produce a time-series of
georeferenced, three-dimensional thermal models of an active lava dome at Volcán de Colima.
Comparisons between these models and equivalents derived from DSLR images suggest that, while
less detailed, the thermal models provide a valuable representation of dome geometry. Estimates of
the lava dome volume correspond well between the DSLR and thermal datasets.
The thermal models were found to be substantially more robust to the adverse effects of degassing
and poor lighting. Because degassing is common at Volcán de Colima (as at many other volcanoes)
thermal imaging provided important data continuity at times when DSLR image quality was restricted.
Where both DSLR and thermal models were available, the thermal models provided a useful
complementary geometry estimate, helping to identify uncertainty in the models, and a
georeferenced map of temperature distribution that allows identification of thermally active regions
on the dome surface.
The combined DSLR and thermal datasets provided detailed information about the evolution of the
dome on Volcán de Colima between 2013 and 2015. It is possible that, if employed as a monitoring
technique (rather than retrospectively), the rapid change in dome volume, morphology and
temperature distribution documented by the models in the months leading up to July 2015 may have
provided prior warning of the dome collapse.
The authors would like to acknowledge the multitude of past CIIV students who participated in data
collection for this study and helped to finance flights. Some flights were financed by NERC Urgency
Grant NE/L000741/1 (PI: Paul Cole). NV was supported by Universidad de Colima FRABA grants. Paul
Cole and an anonymous reviewer are thanked for their useful feedback during the review process.
Abdurachman, E., Bourdier, J.-L., Voight, B., 2000. Nuées ardentes of 22 November 1994 at Merapi
volcano, Java, Indonesia. Journal of Volcanology and Geothermal Research 100, 345-361.
Calvari, S., Neri, M., Pinkerton, H., 2003. Effusion rate estimations during the 1999 summit eruption
on Mount Etna, and growth of two distinct lava flow fields. Journal of Volcanology and Geothermal
Research 119, 107-123.
Cignoni, P., Corsini, M., Ranzuglia, G., 2008. Meshlab: an open-source 3d mesh processing system.
Ercim news 73, 45-46.
Diefenbach, A.K., Bull, K.F., Wessels, R.L., McGimsey, R.G., 2013. Photogrammetric monitoring of lava
dome growth during the 2009 eruption of Redoubt Volcano. Journal of Volcanology and Geothermal
Research 259, 308-316.
Diefenbach, A.K., Crider, J.G., Schilling, S.P., Dzurisin, D., 2012. Rapid, low-cost photogrammetry to
monitor volcanic eruptions: an example from Mount St. Helens, Washington, USA. Bull Volcanol 74,
Fink, J.H., Anderson, S.W., 2000. Lava domes and coulees. Encyclopedia of volcanoes, 307-319.
Girardeau-Montaut, D., 2015. Cloud Compare3D Point Cloud and Mesh Processing Software. Open
Source Project.
Harris, A.J., Lodato, L., Dehn, J., Spampinato, L., 2009. Thermal characterization of the Vulcano
fumarole field. Bull Volcanol 71, 441-458.
Harris, A.J.L., Stevenson, D.S., 1997. Thermal observations of degassing open conduits and fumaroles
at Stromboli and Vulcano using remotely sensed data. Journal of Volcanology and Geothermal
Research 76, 175-198.
Herd, R.A., Edmonds, M., Bass, V.A., 2005. Catastrophic lava dome failure at Soufrière Hills volcano,
Montserrat, 1213 July 2003. Journal of Volcanology and Geothermal Research 148, 234-252.
Hutchison, W., Varley, N., Pyle, D.M., Mather, T.A., Stevenson, J.A., 2013. Airborne thermal remote
sensing of the Volcán de Colima (Mexico) lava dome from 2007 to 2010. Geological Society, London,
Special Publications 380, 203-228.
James, M.R., Pinkerton, H., Applegarth, L.J., 2009. Detecting the development of active lava flow fields
with a very‐long‐range terrestrial laser scanner and thermal imagery. Geophysical Research Letters
36. 10.1029/2009GL040701.
James, M.R., Robson, S., 2012. Straightforward reconstruction of 3D surfaces and topography with a
camera: Accuracy and geoscience application. Journal of Geophysical Research 117.
James, M.R., Robson, S., 2014. Mitigating systematic error in topographic models derived from UAV
and ground‐based image networks. Earth Surface Processes and Landforms 39, 1413-1420.
James, M.R., Robson, S., Pinkerton, H., Ball, M., 2006. Oblique photogrammetry with visible and
thermal images of active lava flows. Bull Volcanol 69, 105-108. 10.1007/s00445-006-0062-9.
James, M.R., Varley, N., 2012. Identification of structural controls in an active lava dome with high
resolution DEMs: Volcán de Colima, Mexico. Geophysical Research Letters 39. 10.1029/2012gl054245.
Lewis, A., Hilley, G.E., Lewicki, J.L., 2015. Integrated thermal infrared imaging and structure-from-
motion photogrammetry to map apparent temperature and radiant hydrothermal heat flux at
Mammoth Mountain, CA, USA. Journal of Volcanology and Geothermal Research 303, 16-24.
Mueller, S., Varley, N., Kueppers, U., Lesage, P., Davila, G.Á.R., Dingwell, D.B., 2013. Quantification of
magma ascent rate through rockfall monitoring at the growing/collapsing lava dome of Volcán de
Colima, Mexico. Solid Earth 4, 201.
Nolan, M., Larsen, C., Sturm, M., 2015. Mapping snow depth from manned aircraft on landscape scales
at centimeter resolution using structure-from-motion photogrammetry. The Cryosphere 9, 1445-
Pallister, J.S., Diefenbach, A.K., Burton, W.C., Muñoz, J., Griswold, J.P., Lara, L.E., Lowenstern, J.B.,
Valenzuela, C.E., 2013. The Chaitén rhyolite lava dome: Eruption sequence, lava dome volumes, rapid
effusion rates and source of the rhyolite magma. Andean Geology 40, 277-294.
Ryan, G., Loughlin, S., James, M., Jones, L., Calder, E., Christopher, T., Strutt, M., Wadge, G., 2010.
Growth of the lava dome and extrusion rates at Soufrière Hills Volcano, Montserrat, West Indies:
20052008. Geophysical Research Letters 37.
Sahetapy-Engel, S.T., Harris, A.J., Marchetti, E., 2008. Thermal, seismic and infrasound observations of
persistent explosive activity and conduit dynamics at Santiaguito lava dome, Guatemala. Journal of
Volcanology and Geothermal Research 173, 1-14.
Spampinato, L., Calvari, S., Oppenheimer, C., Boschi, E., 2011. Volcano surveillance using infrared
cameras. Earth-Science Reviews 106, 63-91.
Stevenson, J.A., Varley, N., 2008. Fumarole monitoring with a handheld infrared camera: Volcán de
Colima, Mexico, 20062007. Journal of Volcanology and Geothermal Research 177, 911-924.
Voight, B., 2000. Structural stability of andesite volcanoes and lava domes. Philosophical Transactions
of the Royal Society of London A: Mathematical, Physical and Engineering Sciences 358, 1663-1703.
Wackrow, R., Chandler, J.H., 2008. A convergent image configuration for DEM extraction that
minimises the systematic effects caused by an inaccurate lens model. The Photogrammetric Record
23, 6-18.
Wadge, G., Voight, B., Sparks, R., Cole, P., Loughlin, S., Robertson, R., 2014. An overview of the
eruption of Soufriere Hills Volcano, Montserrat from 2000 to 2010. Geological Society, London,
Memoirs 39, 1-40.
Zhang, C., Chen, T., 2001. Efficient feature extraction for 2D/3D objects in mesh representation, Image
Processing, 2001. Proceedings. 2001 International Conference on. IEEE, pp. 935-938.
... collect geospatial information about their environment and are remotely controlled from a ground control station [5]. From this station, the operator can plan and supervise the evolution of the mission. ...
... Drones have also been used to map volcanoes' terrain and to detect volcanic activity. Thiele et al. [5] used drones equipped with thermal cameras, gas sensors, and other instruments to measure temperature, gas concentrations, and other indicators of volcanic activity. This information can be used to predict eruptions, to elaborate rescue operations, for photogrammetry and infrastructure monitoring, or even for delivery services. ...
... UAVs can also be used to study the geology of a volcano and its surrounding area, providing valuable information for volcano research. The use of UAVs in this field can greatly improve the efficiency, accuracy, and safety of operations, as well as decrease costs by reducing the need for human intervention in dangerous areas [5]. However, it implies several challenges related to communication services, such the range, security system, and communication architecture [18]. ...
Full-text available
Uncrewed aerial vehicles (UAVs), also known as drones, are ubiquitous and their use cases extend today from governmental applications to civil applications such as the agricultural, medical, and transport sectors, etc. In accordance with the requirements in terms of demand, it is possible to carry out various missions involving several types of UAVs as well as various onboard sensors. According to the complexity of the mission, some configurations are required both in terms of hardware and software. This task becomes even more complex when the system is composed of autonomous UAVs that collaborate with each other without the assistance of an operator. Several factors must be considered, such as the complexity of the mission, the types of UAVs, the communication architecture, the routing protocol, the coordination of tasks, and many other factors related to the environment. Unfortunately, although there are many research works that address the use cases of multi-UAV systems, there is a gap in the literature regarding the difficulties involved with the implementation of these systems from scratch. This review article seeks to examine and understand the communication issues related to the implementation from scratch of autonomous multi-UAV systems for collaborative decisions. The manuscript will also provide a formal definition of the ecosystem of a multi-UAV system, as well as a comparative study of UAV types and related works that highlight the use cases of multi-UAV systems. In addition to the mathematical modeling of the collaborative target detection problem in distributed environments, this article establishes a comparative study of communication architectures and routing protocols in a UAV network. After reading this review paper, readers will benefit from the multicriteria decision-making roadmaps to choose the right architectures and routing protocols adapted for specific missions. The open challenges and future directions described in this manuscript can be used to understand the current limitations and how to overcome them to effectively exploit autonomous swarms in future trends.
... Airborne instruments have been successfully used to produce DEMs of hazardous lava domes: examples include helicopter kinematic laser on the Soufrière Hills dome, Montserrat (Sparks et al., 1998), low-cost helicopter cameras above Mount St Helens, USA (Diefenbach et al., 2012), UAVs optical images on the Merapi dome in (Darmawan et al., 2018, or thermal infrared imagery of the Volcán de Colima dome, Mexico (Thiele et al., 2017;Salzer et al., 2017). Thermal infrared imagery can also be used to infer the effusion rate using equations linking temperature, heat loss, and crystallization of lava. ...
... If we compare our study with other dome volume and effusion rate estimates (Table 2), the volume of 0.64 Mm 3 is of the same amplitude as other low volume domes for equivalent sizes estimated from optical imagery. It is similar, for example, to the size of the dome emplaced at Nevados de Chillan, Chile (Moussallam et al., 2021) or at Colima volcano, Mexico either in 2011 (Walter et al., 2013a(Thiele et al., 2017. However, as mentioned previously, the Merapi 2018-2019 dome stands at the lower end of domes: if we look at Redoubt (Diefenbach et al., 2012), the dome has a width of 500 m for an average thickness of 200 m and a volume of 72 Mm 3 with a high effusion rate of at least 2.2 m 3 /s, or the Soufriere Hills Montserrat (Wadge et al., 2011) with 1 km long dome lobes for a volume of 40-50 Mm 3 . ...
... Ground-based Herd et al., 2005;Ryan et al., 2010) and aerial flights (Zorn et al., 2020;Moussallam et al., 2021) have the advantage of providing better resolute views of a dome, but require specific campaigns that are costly in time and can only cover smaller areas. The limitations of optical imagery often lead to use this method jointly with other tools: thermal imagery (Thiele et al., 2017) or SAR amplitudes (Ordoñez et al., 2022). One reason explaining the limited number of studies using Pléiades is data availability. ...
... Thermal data can be provided at low-spatial (1 to 4 km) but high-temporal (30 min to 3 day) resolution by the advanced very-high-resolution radiometer, the along-track scanning radiometer and the geostationary operational environmental satellite or at high-spatial (30 to 120 m) but lowtemporal resolution (16 days) by the Landsat 7 enhanced thematic mapper plus (Harris et al. 1997(Harris et al. , 1999(Harris et al. , 2000(Harris et al. and 2001. Data from aerial vehicles have been traditionally used for volcanological monitoring and mapping, also applying the structure from motion processing method (Baldi et al. 2000;Harris et al. 2007;Marsella et al. 2009;Marsella et al. 2014;De Beni et al. 2015;Dvigalo et al. 2016;Neri et al. 2017;Thiele et al. 2017). UASs have been used extensively to derive topographic data for mapping volcanic areas, supporting lava hazard analyses, estimating lava flow and dome volumes and performing high-resolution morphometric analysis (e.g. ...
Full-text available
At active volcanoes recurring eruptive events, erosive processes and collapses modify the edifice morphology and impact monitoring and hazard mitigation. At Etna volcano (Italy) between February and October 2021, 57 paroxysmal events occurred from the South-East Crater (SEC), which is currently its most active summit crater. Strombolian activity and high lava fountains (up to 4 km) fed lava flows towards the east, south and south-west, and caused fallout of ballistics (greater than 1 m in diameter) within 1–2 km from the SEC. The impacted area does not include permanent infrastructure, but it is visited by thousands of tourists. Hence, we rapidly mapped each lava flow before deposits became covered by the next event, for hazard mitigation. The high frequency of the SEC paroxysms necessitated integration of data from three remote sensing platforms with different spatial resolutions. Satellite (Sentinel-2 MultiSpectral Instrument, PlanetScope, Skysat and Landsat-8 Operational Land Imager) and drone images (visible and thermal) were processed and integrated to extract digital surface models and orthomosaics. Thermal images acquired by a permanent network of cameras of the Istituto Nazionale di Geofisica e Vulcanologia were orthorectified using the latest available digital surface model. This multi-sensor analysis allowed compilation of a geodatabase reporting the main geometrical parameters for each lava flow. A posteriori analysis allowed quantification of bulk volumes for the lava flows and the SEC changes and of the dense rock equivalent volume of erupted magma. The analysis of drone-derived digital surface models enabled assessment of the ballistics’ distribution. The developed methodology enabled rapidly and accurate characterisation of frequently occurring effusive events for near real-time risk assessment and hazard communication.
... Furthermore, in urbanised areas, detailed post-eruption topography is important for land recovery actions. Volcano morphologies can be quantified using different techniques [1][2][3][4][5][6][7][8][9] . Recently, the increased capability of UASs and their applications for aerial observation 10,11 , together with the parallel development of Structure-from-Motion (SfM) process 12 , brought important and valuable advantages compared to the classical ground-based, satellite, and crewed aircraft surveys. ...
Full-text available
Identifying accurate topographic variations associated with volcanic eruptions plays a key role in obtaining information on eruptive parameters, volcano structure, input data for volcano processes modelling, and civil protection and recovery actions. The 2021 eruption of Cumbre Vieja volcano is the largest eruptive event in the recorded history for La Palma Island. Over the course of almost 3 months, the volcano produced profound morphological changes in the landscape affecting both the natural and the anthropic environment over an area of tens of km 2. We present the results of a UAS (Unoccupied Aircraft System) survey consisting of >12,000 photographs coupled with Structure-from-Motion photogrammetry that allowed us to produce a very-high-resolution (0.2 m/pixel) Digital Surface Model (DSM). We characterised the surface topography of the newly formed volcanic landforms and produced an elevation difference map by differencing our survey and a pre-event surface, identifying morphological changes in detail. The present DSM, the first one with such a high resolution to our knowledge, represents a relevant contribution to both the scientific community and the local authorities.
... Camera positions and scene geometries are simultaneously solved, and a sparse 3D point cloud is generated (Westoby et al., 2012). Prior research using SfM processing with TIR imagery has focused on active volcanoes (Thiele et al., 2017), measuring the relative temperature distribution of a building envelope structure , and modeling forest canopies (Webster et al., 2018). However, we are not aware of past research that focused on identifying wildlife in 3D models generated with UAS-TIR imagery and SfM approaches. ...
Full-text available
An important component of wildlife management and conservation is monitoring the health and population size of wildlife species. Monitoring the population size of an animal group can inform researchers of habitat use, potential changes in habitat and resulting behavioral adaptations, individual health, and the effectiveness of conservation efforts. Arboreal monkeys are difficult to monitor as their habitat is often poorly accessible and most monkey species have some degree of camouflage, making them hard to observe in and below the tree canopy. Surveys conducted using uninhabited aerial vehicles (UAVs) equipped with thermal infrared (TIR) cameras can help overcome these limitations by flying above the canopy and using the contrast between the warm body temperature of the monkeys and the cooler background vegetation, reducing issues with impassable terrain and animal camouflage. We evaluated the technical and procedural elements associated with conducting UAV-TIR surveys for arboreal and terrestrial macaque species. Primary imaging missions and analyses were conducted over a monkey park housing approximately 160 semi-free-ranging Japanese macaques (Macaca fuscata). We demonstrate Repeat Station Imaging (RSI) procedures using co-registered TIR image pairs facilitate the use of image differencing to detect targets that were moving during rapid sequence imaging passes. We also show that 3D point clouds may be generated from highly overlapping UAV-TIR image sets in a forested setting using structure from motion (SfM) image processing techniques. A point cloud showing area-wide elevation values was generated from TIR imagery, but it lacked sufficient point density to reliably determine the 3D locations of monkeys.
... Structure-from-motion photogrammetry has emerged over the past decade as an increasingly powerful and reliable means to survey and analyze lava dome growth (James and Varley, 2012;Thiele et al., 2017;Carr et al., 2019a;James et al., 2020b;Zorn et al., 2020;Andaru et al., 2021;Kelfoun et al., 2021;Moussallam et al., 2021). Our results based on differencing of DEMs created using SfM photogrammetry with images from UAS surveys serve to further constrain the erupted volume and effusion rates at Sinabung when compared to previous estimates using ground- based SfM photogrammetry (Carr et al., 2019a), laser distance measurements , and satellite images (Yulianto et al., 2016;Nakada et al., 2019;Pallister et al., 2019;Kriswati and Solikhin, 2020). ...
Full-text available
Lava domes form by the effusive eruption of high-viscosity lava and are inherently unstable and prone to collapse, representing a significant volcanic hazard. Many processes contribute to instability in lava domes and can generally be grouped into two categories: active and passive. Active collapses are driven directly by lava effusion. In contrast, passive collapses are not correlated with effusion rate, and thus represent a hazard that is more difficult to assess and forecast. We demonstrate a new workflow for assessing and forecasting passive dome collapse by examining a case study at Sinabung Volcano (North Sumatra, Indonesia). We captured visual images from the ground in 2014 and from unoccupied aerial systems (UAS) in 2018 and used structure-from-motion photogrammetry to generate digital elevation models (DEMs) of Sinabung’s evolving lava dome. By comparing our DEMs to a pre-eruption DEM, we estimate volume changes associated with the eruption. As of June 2018, the total erupted volume since the eruption began is 162 × 10 ⁶ m ³ . Between 2014 and 2018, 10 × 10 ⁶ m ³ of material collapsed from the lava flow due to passive processes. We evaluate lava dome stability using the Scoops3D numerical model and the DEMs. We assess the passive collapse hazard and analyze the effect of lava material properties on dome stability. Scoops3D is able to hindcast the location and volume of passive collapses at Sinabung that occurred during 2014 and 2015, and we use the same material properties to demonstrate that significant portions of the erupted lava potentially remain unstable and prone to collapse as of late 2018, despite a pause in effusive activity earlier that year. This workflow offers a means of quantitatively assessing passive collapse hazards at active or recently active volcanoes.
... Drones have recently made significant advances in the field of geology in general, providing a great opportunity to reach remote outcrops that would otherwise be inaccessible or extremely dangerous for direct study or reconnaissance. Drones in geology have been used for both practical/industrial and pure research applications in the fields of mining (e.g., McLeod et al. 2013;Lee and Choi 2016;Dunnington and Nakagawa 2017;Kirsch et al. 2018), volcanology (e.g., Amici et al. 2013;Harvey et al. 2016;Thiele et al. 2017;Di Felice et al. 2018;Patrick et al. 2019;Walter et al. 2020), karst research (McFarlane et al. 2013, study of post-earthquake land changes (Gong et al. 2012), analysis and mapping of river systems (e.g., Flener et al. 2013;Casado et al. 2015;Langhammer et al. 2017), glaciology (e.g., Westoby et al. 2015;Bhardwaj et al. 2016;De Michele et al. 2016), landslides and rockfall analysis and mapping (e.g., Danzi et al. 2013;Giordan et al. 2015;Turner et al. 2015;Lindner et al. 2016;Mateos et al. 2017;Gupta and Shukla 2018;Devoto et al. 2020;Francioni et al. 2020;Godone et al. 2020), sedimentology and 3D facies modelling (e.g., Chesley et al. 2017;Hayes et al. 2017;Nieminski and Graham 2017;Cabello et al. 2018;Rubi et al. 2018;Behrman et al. 2019), structural geology (e.g., Bemis et al. 2014;Deffontaines et al. 2017;Giletycz et al. 2017;Trippanera et al. 2019) and geothermy (e.g., Nishar et al. 2016), and other reasons as discussed below. ...
Unmanned aerial vehicles (UAVs), have seen tremendous development in the last decade, with numerous applications in civil and research fields. Drones' success, particularly in the field of research, is due to a number of factors, including rapid technological advancement, tool versatility, and prices that are becoming increasingly affordable even for small research groups or individuals. Given the versatility and ongoing development of micro drones, we tested the use of micro-drones in vertebrate palaeontology to reconstruct mounted skeletons using the photogrammetry method. The experiment was carried out on a massive specimen of Mammuthus meridionalis (Nesti 1825) from Madonna della Strada, which is on display at the east bastion of the Spanish Fortress in L'Aquila (Abruzzo, Central Italy), comparing the results with those obtained using the traditional method using a digital camera. Even though both the traditional digital camera and the drone methods produced a high-resolution 3D model of the skeleton, the results obtained, indeed, lead us to consider the use of micro-drones in museum structures as a very interesting and promising new field of application. Drones provide a simple, fast, and non-invasive system for the study, monitoring, and enhancement of cultural heritage in all of its possible manifestations.
... The lack of GCPs on 3D model uncertainties could be also mitigated by the use of GNSS-RTK-enabled survey devices. Moreover, as successfully demonstrated by Thiele et al. [5], thermal images could be used in an SfM workflow to mitigate the adverse effects of degassing and poor visibility and provide more continuous time-series data than the visible-light equivalents. ...
Full-text available
In July and August 2019, two paroxysmal eruptions dramatically changed the morphology of the crater terrace that hosts the active vents of Stromboli volcano (Italy). Here, we document these morphological changes, by using 2259 UAS-derived photographs from eight surveys and Structure-from-Motion (SfM) photogrammetric techniques, resulting in 3D point clouds, orthomosaics, and digital surface models (DSMs) with resolution ranging from 8.1 to 12.4 cm/pixel. We focus on the morphological evolution of volcanic features and volume changes in the crater terrace and the upper part of the underlying slope (Sciara del Fuoco). We identify both crater terrace and lava field variations, with vents shifting up to 47 m and the accumulation of tephra deposits. The maximum elevation changes related to the two paroxysmal eruptions (in between May and September 2019) range from +41.4 to −26.4 m at the lava field and N crater area, respectively. Throughout September 2018–June 2020, the total volume change in the surveyed area was +447,335 m3. Despite Stromboli being one of the best-studied volcanoes worldwide, the UAS-based photogrammetry products of this study provide unprecedented high spatiotemporal resolution observations of its entire summit area, in a period when volcanic activity made the classic field inspections and helicopter overflights too risky. Routinely applied UAS operations represent an effective and evolving tool for volcanic hazard assessment and to support decision-makers involved in volcanic surveillance and civil protection operations.
Designed as a pragmatic approach that anticipates change to cultural heritage, this chapter discusses responses that encompass records for tangible cultural heritage (monuments, sites and landscapes) and the narratives that see the impact upon them. The Curious Travellers project provides a mechanism for digitally documenting heritage sites that have been destroyed or are under immediate threat from unsympathetic development, neglect, natural disasters, conflict and cultural vandalism. The project created and tested data-mining and crowd-sourced workflows that enable the accurate digital documentation and 3D visualisation of buildings, archaeological sites, monuments and heritage at risk. When combined with donated content, image data are used to recreate 3D models of endangered and lost monuments and heritage sites using a combination of open-source and proprietary methods. These models are queried against contextual information, helping to place and interrogate structures with relevant site and landscape data for the surrounding environment. Geospatial records such as aerial imagery and 3D mobile mapping laser scan data serve as a framework for adding new content and testing accuracy. In preserving time-event records, image metadata offers important information on visitor habits and conservation pressures, which can be used to inform measures for site management.KeywordsUNESCOHeritage conservationSfM photogrammetryMulti-view stereo
Technological developments in the last few decades allow generation of increasingly high-resolution digital elevation models (DEMs), useful in many fields of Earth and environmental science, and especially for tectonic geomorphic studies. Combined with falling costs and the improved accuracy of geo-referencing using satellite geodetic tools based on Global Navigation Satellite Systems (GNSS), such as Global Positioning System (GPS), these developments have moved DEMs from the realm of computer equivalents of a topographic map to sophisticated tools for process understanding. Four techniques for the production of high-resolution DEMs are notable: light detection and ranging (LIDAR), interferometric synthetic aperture radar (InSAR), terrestrial radar interferometry (TRI), and structure from motion (SfM) photogrammetry. With the exception of TRI, restricted to ground-mounted platforms, the instrumentation can be hosted on satellites, piloted aircraft, or Unoccupied Aerial Vehicles (UAVs). Calibration with GNSS enables merging, or comparison of data sets acquired by different techniques, as well as change detection at the centimeter level.
Full-text available
The most recent eruptive phase of Volcán de Colima, Mexico, started in 1998 and was characterized by episodic dome growth with a variable effusion rate, interrupted intermittently by explosive eruptions. Between November 2009 and June 2011, growth at the dome was limited to a lobe on the western side where it had previously started overflowing the crater rim, leading to the generation of rockfall events. This meant that no significant increase in dome volume was perceivable and the rate of magma ascent, a crucial parameter for volcano monitoring and hazard assessment, could no longer be quantified via measurements of the dome's dimensions. Here, we present alternative approaches to quantify the magma ascent rate. We estimate the volume of individual rockfalls through the detailed analysis of sets of photographs (before and after individual rockfall events). The relationship between volume and infrared images of the freshly exposed dome surface and the seismic signals related to the rockfall events was then investigated. Larger events exhibited a correlation between the previously estimated volume of a rockfall and the surface temperature of the freshly exposed dome surface as well as the mean temperature of rockfall masses distributed over the slope. We showed that for larger events, the volume of the rockfall correlates with the maximum temperature at the newly formed cliff as well as the seismic energy. By calibrating the seismic signals using the volumes estimated from photographs, the count of rockfalls over a certain period was used to estimate the magma extrusion flux for the period investigated. Over the course of the measurement period, significant changes were observed in number of rockfalls, rockfall volume and hence averaged extrusion rate. The extrusion rate was not constant: it increased from 0.008 m3 s−1 to 0.02 m3 s−1 during 2010 and dropped down to 0.008 m3 s−1 again in March 2011. In June 2011, magma extrusion had come to a halt. The methodology presented represents a reliable tool to constrain the growth rate of domes that are repeatedly affected by partial collapses. There is a good correlation between thermal and seismic energies and rockfall volume. Thus it is possible to calibrate the seismic records associated with the rockfalls (a continuous monitoring tool) to improve both volcano monitoring at volcanoes with active dome growth and hazard management associated with rockfalls specifically.
Full-text available
Airborne photogrammetry is undergoing a renaissance: lower-cost equipment, more powerful software, and simplified methods have significantly lowered the barriers-to-entry and now allow repeat-mapping of cryospheric dynamics at spatial resolutions and temporal frequencies that were previously too expensive to consider. Here we apply these techniques to the measurement of snow depth from manned aircraft. The main airborne hardware consists of a consumer-grade digital camera coupled to a dual-frequency GPS. The photogrammetric processing is done using a commercially-available implementation of the Structure from Motion (SfM) algorithm. The system hardware and software, exclusive of aircraft, costs less than USD 30 000. The technique creates directly-georeferenced maps without ground control, further reducing costs. To map snow depth, we made digital elevation models (DEMs) during snow-free and snow-covered conditions, then subtracted these to create difference DEMs (dDEMs). We assessed the accuracy (geolocation) and precision (repeatability) of our DEMs through comparisons to ground control points and to time-series of our own DEMs. We validated these assessments through comparisons to DEMs made by airborne lidar and by another photogrammetric system. We empirically determined an accuracy of ± 30 cm and a precision of ± 8 cm (both 95% confidence) for our methods. We then validated our dDEMs against more than 6000 hand-probed snow depth measurements at 3 test areas in Alaska covering a wide-variety of terrain and snow types. These areas ranged from 5 to 40 km2 and had ground sample distances of 6 to 20 cm. We found that depths produced from the dDEMs matched probe depths with a 10 cm standard deviation, and these depth distributions were statistically identical at 95% confidence. Due to the precision of this technique, other real changes on the ground such as frost heave, vegetative compaction by snow, and even footprints become sources of error in the measurement of thin snow packs (< 20 cm). The ability to directly measure such small changes over entire landscapes eliminates the need to extrapolate isolated field measurements. The fact that this mapping can be done at substantially lower costs than current methods may transform the way we approach studying change in the cryosphere.
Full-text available
The 1995–present eruption of Soufrière Hills Volcano on Montserrat has produced over a cubic kilometre of andesitic magma, creating a series of lava domes that were successively destroyed, with much of their mass deposited in the sea. There have been five phases of lava extrusion to form these lava domes: November 1995–March 1998; November 1999–July 2003; August 2005–April 2007; July 2008–January 2009; and October 2009–February 2010. It has been one of the most intensively studied volcanoes in the world during this time, and there are long instrumental and observational datasets. From these have sprung major new insights concerning: the cyclicity of magma transport; low-frequency earthquakes associated with conduit magma flow; the dynamics of lateral blasts and Vulcanian explosions; the role that basalt–andesite magma mingling in the mid-crust has in powering the eruption; identification using seismic tomography of the uppermost magma reservoir at a depth of 5.5 > 7.5 km; and many others. Parallel to the research effort, there has been a consistent programme of quantitative risk assessment since 1997 that has both pioneered new methods and provided a solid evidential source for the civil authority to use in mitigating the risks to the people of Montserrat.
Full-text available
High resolution digital elevation models (DEMs) are increasingly produced from photographs acquired with consumer cameras, both from the ground and from unmanned aerial vehicles (UAVs). However, although such DEMs may achieve centimetric detail, they can also display systematic broad-scale error that restricts their wider use. Such errors which, in typical UAV data are expressed as a vertical ‘doming’ of the surface, result from a combination of near-parallel imaging directions and inaccurate correction of radial lens distortion. Using simulations of multi-image networks with near-parallel viewing directions, we show that enabling camera self-calibration as part of the bundle adjustment process inherently leads to erroneous radial distortion estimates and associated DEM error. This effect is relevant whether a traditional photogrammetric or newer structure-from-motion (SfM) approach is used, but errors are expected to be more pronounced in SfM-based DEMs, for which use of control and check point measurements are typically more limited. Systematic DEM error can be significantly reduced by the additional capture and inclusion of oblique images in the image network; we provide practical flight plan solutions for fixed wing or rotor-based UAVs that, in the absence of control points, can reduce DEM error by up to two orders of magnitude. The magnitude of doming error shows a linear relationship with radial distortion and we show how characterisation of this relationship allows an improved distortion estimate and, hence, existing datasets to be optimally reprocessed. Although focussed on UAV surveying, our results are also relevant to ground-based image capture. This article is protected by copyright. All rights reserved.
Full-text available
We investigate high-resolution digital photographs and infrared images of the lava dome eruption at Volcán de Colima, from 2007 to 2010. Qualitative observations provide insight into active volcanic processes (e.g. rockfalls and fracturing) and show that, as the dome advances a substantial cooled talus apron develops, which stabilizes the structure. Progressive collapse of the talus apron as it reaches the crater rim corresponds with the development of a lava lobe, extruding hot lava from deeper within the dome. Quantitative dome surface temperature timeseries show that the highest temperature hotspots migrate from the dome sides (250-380 °C) to the top (150-300 °C) and finally to the lava lobe (220-400 °C) as the structurally unstable areas expose fresh material. Net surface heat loss from the dome ranges from 5 to 30 MW, comparable to other dome forming systems. Heat budget calculations confirm that the lava dome retained a hot viscous core throughout the period 2007-2010. We propose that the mechanical stability of the Volcán de Colima dome arises from the shear strength of flanking talus which stabilizes the hot viscous core.
Full-text available
The most recent eruptive phase of Volc´ an de Colima, Mexico, started in 1998 and was characterized by dome growth with a variable effusion rate, interrupted intermittently by explosive eruptions. Between November 2009 and June 2011, activity at the dome was mostly limited to a lobe on the western side where it had previously started overflowing the crater rim, leading to the generation of rockfall events. As a consequence of this, no significant increase in dome volume was perceivable and the rate of magma ascent, a crucial parameter for volcano monitoring and hazard assessment could no longer be quantified via measurements of the dome’s dimensions. Here, we present alternative approaches to quantify the magma ascent rate. We estimate the volume of individual rockfalls through the detailed analysis of sets of photographs (before and after individual rockfall events). The relationship between volume and infrared images of the freshly exposed dome surface and the seismic signals related to the rockfall events were then investigated. Larger rockfall events exhibited a correlation between its previously estimated volume and the surface temperature of the freshly exposed dome surface, as well as the mean temperature of rockfall mass distributed over the slope. We showed that for larger events, the volume of the rockfall correlates with the maximum temperature of the newly exposed lava dome as well as a proxy for seismic energy. It was therefore possible to calibrate the seismic signals using the volumes estimated from photographs and the count of rockfalls over a certain period was used to estimate the magma extrusion flux for the period investigated. Over the course of the measurement period, significant changes were observed in number of rockfalls, rockfall volume and hence averaged extrusion rate. The extrusion rate was not constant: it increased from 0.008 ±0.003 to 0.02 ± 0.007 m3 s-1 during 2010 and dropped down to 0.008 ± 0.003 m 3 s-1 again in March 2011. In June 2011, magma extrusion had come to a halt. The methodology presented represents a reliable tool to constrain the growth rate of domes that are repeatedly affected by partial collapses. There is a good correlation between thermal and seismic energies and rockfall volume. Thus it is possible to calibrate the seismic records associated with the rockfalls (a continuous monitoring tool) to improve volcano monitoring at volcanoes with active dome growth.
Full-text available
Topographic measurements for detailed studies of processes such as erosion or mass movement are usually acquired by expensive laser scanners or rigorous photogrammetry. Here, we test and use an alternative technique based on freely available computer vision software which allows general geoscientists to easily create accurate 3D models from field photographs taken with a consumer-grade camera. The approach integrates structure-from-motion (SfM) and multi-view-stereo (MVS) algorithms and, in contrast to traditional photogrammetry techniques, it requires little expertise and few control measurements, and processing is automated. To assess the precision of the results, we compare SfM-MVS models spanning spatial scales of centimeters (a hand sample) to kilometers (the summit craters of Piton de la Fournaise volcano) with data acquired from laser scanning and formal close-range photogrammetry. The relative precision ratio achieved by SfM-MVS (measurement precision : observation distance) is limited by the straightforward camera calibration model used in the software, but generally exceeds 1:1000 (i.e. centimeter-level precision over measurement distances of 10s of meters). We apply SfM-MVS at an intermediate scale, to determine erosion rates along a ~50-m-long coastal cliff. Seven surveys carried out over a year indicate an average retreat rate of 0.70±0.05 m a-1. Sequential erosion maps (at ~0.05 m grid resolution) highlight the spatio-temporal variability in the retreat, with semivariogram analysis indicating a correlation between volume loss and length scale. Compared with a laser scanner survey of the same site, SfM-MVS produced comparable data and reduced data collection time by ~80%.
Full-text available
Slope failures resulting from structural instability of andesitic volcanic edifices can generate mobile debris avalanche that travel long distances down or beyond the flanks of volcanoes. More than 20 major slope failures have occurred worldwid over the past 500 years, a rate exceeding that of caldera collapse. Hazards derive from the debris avalanches themselves from associated explosive activity that ranges from vertical eruptions (often accompanied by pyroclastic currents) to devastatin directed blasts, from associated lahars, and from tsunamis. Collapses of growing lava domes are more frequent, are similar in many ways, to edifice collapse, and can directly generate devastating pyroclastic currents. This paper examines some aspects of current understanding of edifice and lavadome instability. The primary focus of the presentatio is on mechanisms and factors associated with collapse, the geometric factors, augmented loading by magma, localized strengt reduction by physical and chemical changes (the latter commonly associated with hydrothermal processes), strain weakening pore-fluid (water or gas) pressure enhancement, retrogressive failure, time-dependent failure, and seismic shaking. Some aspect of material property evaluation, analysis procedures, and implications on monitoring are also discussed. Case examples discusse include edifice instability at Mt St Helens, USA, and Soufriere Hills volcano, Montserrat, the stability of lava spines a Mont Pelee, Martinique, and Lamington, Papua New Guinea, and lavadome stability at Soufriere Hills. The topics bear on understandin hazardous edifice and dome failures, and the measures to anticipate such failures.
This work presents a method to create high-resolution (cm-scale) orthorectified and georeferenced maps of apparent surface temperature and radiant hydrothermal heat flux and estimate the radiant hydrothermal heat emission rate from a study area. A ground-based thermal infrared (TIR) camera was used to collect (1) a set of overlapping and offset visible imagery around the study area during the daytime and (2) time series of co-located visible and TIR imagery at one or more sites within the study area from pre-dawn to daytime. Daytime visible imagery was processed using the structure-from-motion photogrammetric method to create a digital elevation model onto which pre-dawn TIR imagery was orthorectified and georeferenced. Three-dimensional maps of apparent surface temperature and radiant hydrothermal heat flux were then visualized and analyzed from various computer platforms (e.g., Google Earth, ArcGIS). We demonstrate this method at the Mammoth Mountain fumarole area on Mammoth Mountain, CA. Time-averaged apparent surface temperatures and radiant hydrothermal heat fluxes were observed up to 73.7 °C and 450 W m− 2, respectively, while the estimated radiant hydrothermal heat emission rate from the area was 1.54 kW. Results should provide a basis for monitoring potential volcanic unrest and mitigating hydrothermal heat-related hazards on the volcano.
The 2009 eruption of Redoubt Volcano, Alaska, began with a phreatic explosion on 15 March followed by a series of at least 19 explosive events and growth and destruction of at least two, and likely three, lava domes between 22 March and 4 April. On 4 April explosive activity gave way to continuous lava effusion within the summit crater. We present an analysis of post-4 April lava dome growth using an oblique photogrammetry approach that provides a safe, rapid, and accurate means of measuring dome growth. Photogrammetric analyses of oblique digital images acquired during helicopter observation flights and fixed-wing volcanic gas surveys produced a series of digital elevation models (DEMs) of the lava dome from 16 April to 23 September. The DEMs were used to calculate estimates of volume and time-averaged extrusion rates and to quantify morphological changes during dome growth.