Using meltwater plumes to infer subglacial hydrology at tidewater glaciers

PhD update: January 2017. Meltwater plumes are the upwelling of fresh water in front of a tidewater glacier. These are known to influence submarine melt rates, which are suggested to have a significant impact on the calving rate of glaciers that terminate in sea water. Recent work has suggested that meltwater plumes can also be used to infer the subglacial hydrology at the front of a glacier.

At land-terminating glaciers, water is evacuated via flow outlets which form large rivers on the adjacent land. It is therefore relatively straightforward to measure the amount of water leaving the glacial system. Things are a bit more complicated at glaciers which terminate in water (i.e. a fjord, sea, or ocean). Fresh water exits from the glacier at depth and interacts with the salty seawater. The fresh water moves upwards due to the density difference between freshwater and saltwater, forming a turbulent column of mixing water. This is a meltwater plume (and can also be referred to as a ‘submarine plume’, or simply just a ‘plume’).

An example of a meltwater plume at Tunabreen, a tidewater glacier in Svalbard

An example of a surfacing meltwater plume at Tunabreen, a tidewater glacier in Svalbard. Note the distinctive shape and the dark colour (indicating sediment content) of the surface expression.

The freshwater in a meltwater plume will continue to flow up through the water column and entrain surrounding saltwater until it is thoroughly mixed (i.e. there is no difference in the density between the plume and the surrounding water). At this point, a meltwater plume will reach its neutral buoyancy and the water will cease flowing upwards and flow horizontally away from the glacier front.

A meltwater plume can reach the sea surface if the neutral buoyancy exceeds the depth of the fjord. The surface expression of a meltwater plume is normally very distinctive, distinguished by its sediment-laden colour and turbulent flow away from the glacier. We have lovely images of meltwater plume activity at Tunabreen, a tidewater glacier in Svalbard, showing a surfacing plume which has entrained very rich red/brown sediment.

The neutral buoyancy point of a meltwater plume is influenced by a number of factors:

  1. The temperature/density difference between the freshwater in the plume and the surrounding saltwater
  2. The geometry of the fjord, such as how deep it is
  3. The stratification of the surrounding saltwater
  4. The rate at which meltwater is exiting the glacier (also referred to as discharge)

The first three of these listed influences undergo relatively little change compared to discharge over short time-scales (e.g. a summer season). Assuming this, the activity of a meltwater plume can be used as a signal for the rate at which meltwater is exiting a glacier over the course of a melt season.

Meltwater typically exits into a fjord/sea/ocean at the bed of a glacier. The meltwater can either be directed through a given number of big channels or a series of intricate, small cavities. Channels can typically accommodate large volumes of meltwater, hence they are known as an efficient drainage system. Linked cavities are not as effective at transporting meltwater and tend to hold water at the bed for much longer durations, so they are aptly referred to as an inefficient drainage system.

Kronebreen (centre) viewed from the west. Kronebreen shares its southern (right) margin with Kongsvegen, a slow-moving surge-type glacier that has been fairly inactive for the past couple of years. The glacier adjacent to Kronebreen, separated by the mountain Collethøgda (left), is called Kongsbreen. Kongsbreen has been retreating from the fjord onto land since approximately 2014 (September 2016)

A meltwater plume at the front of Kronebreen, a fast-flowing tidewater glacier in Svalbard. The surfacing plume  is situated on the north side of the plume (left side of the terminus in this image). This plume entrains sediment which gives it a red/brown colour. A plume also surfaced intermittently on the south side of the terminus during the melt season of 2014 (not pictured here). Photo taken: September 2016.

Timeline of surfacing plume activity at Kronebreen, Svalbard, monitored from time-lapse imagery. Plumes P1, P2 and P3 were present at the north side of the terminus, with P1 being active for the entire monitoring period (gaps are where there was no visibility in the images). Plume P4 surfaced at the south side of the terminus, showing intermittent activity throughout the melt season.

Timeline of surfacing plume activity at Kronebreen, Svalbard, monitored from time-lapse imagery. Activity began on the 23 June and continued through till the end of September. Plumes P1, P2 and P3 were present at the north side of the terminus. P1 (pictured in the above image) was active for the entire monitoring period (gaps are where there was no visibility in the time-lapse imagery). Plume P4 surfaced at the south side of the terminus, showing intermittent activity throughout the melt season.

An efficient drainage system can quickly channel a large volume of meltwater into the adjacent sea water. It is therefore likely that the neutral buoyancy of a meltwater plume from an efficient drainage system can exceed the depth of the fjord, so the plume will surface and will be visible. An inefficient drainage system is much more limited in the rate at which it can deliver meltwater into the adjacent sea water. It is therefore likely that the neutral buoyancy of a meltwater plume from an inefficient drainage system will be at depth, so the plume will not surface and will not be visible. We can thus infer what type of drainage system is present at the front of a glacier by monitoring meltwater plume activity over short durations.

We have been monitoring meltwater plume activity at the front of Kronebreen, a fast-flowing tidewater glacier in Svalbard. Two sets of plumes were present over the 2014 melt season, on the north and south side of the terminus. It is assumed here that a meltwater plume is likely to surface in the fjord if a channel is active based on the known fjord depth (∼80 m) and modelled runoff outputs. The set of plumes on the north side of the terminus persistently surfaced throughout the melt season, whereas the plume on the south side only surfaced intermittently.

A plume may not be able to consistently surface because meltwater is not leaving the glacier through a stable efficient drainage system. This could suggest that two different drainage systems preside at the north and south side of the glacier – a stable efficient drainage system on the north side, and an unstable system that switches between efficient and inefficient drainage on the south side.

Velocity map of Kronebreen over an 11-day period in April 2014 (Luckman et al., 2015)

A velocity map of Kronebreen over an 11-day period in April 2014 (Luckman et al., 2015). These velocities are derived from feature tracking between image pairs, and these images are TerraSAR-X satellite images. Higher surface velocities are present at the central/south side of the terminus compared to the north side. This is possibly related to a difference in subglacial drainage beneath these two regions. Source: UNIS.

In this situation, you would expect to see other differences between the north and south side of the terminus such as surface velocity. A large amount of subglacial meltwater is in contact with the bed in an inefficient drainage system, which enhances lubrication at the bed and promotes ice sliding. In an efficient drainage system, the water is channelled through a discrete area of the glacier and thus there is less basal lubrication as a smaller amount is in contact with the bed.

Surface velocities over the 2014 melt season show a distinct difference between the north and south side of the glacier terminus – the south is much faster flowing than the north, with the south exceeding velocities of 4 metres per day whilst the north remains relatively slow (see an example velocity map above). It is likely that a difference in drainage efficiency could facilitate this difference in surface velocities. The presence of an inefficient drainage system at the south side of the glacier tongue may be promoting faster velocities.

This idea is being further explored with additional datasets to better understand glacier hydrology and dynamics. The main take-home message from this post is that meltwater plume activity could be a reliable signal for meltwater outflow. This activity can be effectively monitored using time-lapse photography. Observations of plume activity can help us to diagnose the nature of subglacial drainage beneath tidewater glaciers, which is not accessible for direct measurements at this time. Kronebreen appears to have two different drainage systems active near the glacier terminus, as reflected in the differing plume activity, and this could be facilitating fast velocities in discrete areas of the glacier.


Further reading

Slater et al., 2017 – A newly-published study looked at meltwater plume activity at Kangiata Nunata Sermia (KNS) in Southwest Greenland using an in-situ time-lapse camera. They predicted from model simulations that a meltwater plume from a single channel should be able to surface in the adjacent fjord water, knowing the rate of discharge through the drainage system. However, the time-lapse imagery showed that the meltwater plume was only visible for brief periods throughout a melt season (May to September 2009). They argued that a plume was not consistently surfacing because meltwater may not leaving the glacier through a stable efficient drainage system. An efficient drainage system may not be able to persist at the front of KNS because it could be repeatedly disrupted by basal deformation, which is facilitated by the fast-flowing nature of the glacier. This paper has been neatly summarised by ice2ice.

Time-lapse sequences from Kronebreen. Note the visible plume activity seen from cameras 1 and 2 through the melt season.

Advertisements

PhD Update: October 2016

It is known that supraglacial lakes on the surface of a glacier fill and drain over the course of a summer melt season. Lake observations from time-lapse photography at Kronebreen glacier in Svalbard show possible links between their drainage and changes at the glacier bed. This month I have been further investigating these lakes using satellite imagery and other data to find that these lakes have formed and drained in similar positions for at least 30 years, indicating that the subglacial environment is relatively consistent year-on-year.

Time-lapse images at Kronebreen show lake drainage at the end of June in both 2014 and 2015. These lakes have a maximum surface area of 18,000 sq m and appear to fill and drain simultaneously, sometimes appearing to be a brown, sediment-heavy colour suggesting that they are directly connected to the glacier bed.

Supraglacial lakes filling and draining in the upper section of Kronebreen glacier, Svalbard. The sequence covers June to July 2015, one image per day.

Supraglacial lakes filling and draining in the upper section of Kronebreen glacier, Svalbard. The sequence covers June to July 2015, one image per day.

These lakes were tracked through time based on pixel intensity and then geo-rectified using the camera position, a three-dimensional representation of the landscape (DEM) and ground control points (GCPs) to map them in real world coordinates. For more on the details of how this method works, see an earlier post here. The three sets of lakes tracked from the 2014 sequence have an upglacier pattern of drainage – the lower lakes fill and drain first, followed by the upper glacier lakes. As it is likely that these lakes are connected to the glacier bed, it is possible that their pattern of drainage show an upglacier-propagating flushing event at the bed. A trigger causes subglacial meltwater near the glacier front to drain which subsequently draws down meltwater from further upglacier, draining the lower surface lakes before the upglacier lakes.

Surface lakes on Kronebreen in the 2014 summer melt season

Surface lakes on Kronebreen in the 2014 summer melt season (the red line indicates the 2014 terminus position). These lakes were mapped from time-lapse imagery acquired from two camera positioned on Collethogda and Garwoodtoppen, the two outcrops to the north and south of the glacier tongue. The lakes are automatically detected based on the pixel intensity in the image and mapped in the image plane. Then the shapes are geo-rectified to place them in real world coordinates. Base map supplied freely by Norsk Polarinstitutt.

Surface lake area tracked through the Kronebreen time-lapse image sequence from 2014.

Surface lake area tracked through the Kronebreen time-lapse image sequence from summer 2014. Here, automatically detected lakes are determined from images every half hour (apart from images with poor illumination or cloud cover). There is slight flickering at the beginning of the sequence when the lakes are at their largest due to changing illumination conditions, but generally the automated detection shows the rapid drainage. After the drainage, the lakes appear to shift upwards (i.e. perpendicular to the ice flow from right to left). This signifies that a significant surface lowering event has taken place, with the lowering appearing as movement towards the time-lapse camera. This supports the idea of a upglacier progression of drainage, with the glacier surface lowering as the system is no longer hydraulically jacked.

As we only have images of these lakes from 2014 and 2015, I had a look at archived Landsat satellite imagery of the area to see if these lakes appear in similar places in earlier years. Overall, I found that lakes consistently appear year-on-year around the same time in the same places, at least back to 1986, which is 30 years ago. From here, we are working on acquiring more satellite imagery  to further investigate whether these lakes are consistent and also whether there are additional lakes in other areas on the glacier tongue. Initial assessment shows that there are other lakes nearer to the terminus that appear infrequently, suggesting that the subglacial system is dynamic and not as consistently configured as we first thought.

Landsat image of Kronebreen from 23rd July 1990, showing surface lakes that appear in a similar region year-on-year.

Landsat image of Kronebreen from 23rd July 1990, showing surface lakes that appear in a similar region year-on-year. Landsat imagery from 2011, 2001, 2000, 1990 and 1986 (i.e. all years without cloud cover or poor imagery) all showed lake formation and drainage in the same area. Landsat imagery freely accessed from the USGS LandsatLook Viewer.

I presented this work at the International Glaciological Society (IGS) Nordic Branch Meeting at the end of this month, which was held at the Norsk Polarinstitutt in Tromsø. Generally the presentation went really well, probably one of the best presentations I have ever done! There were a number of people at the conference working on Kronebreen, so it was especially helpful to see what they were doing and have input from them. We also had a lot of discussions more generally about Kronebreen and the techniques that we are using to acquire data from time-lapse imagery. The conference was very well organised and a great success so I would like to say thank you to those involved in making it happen.

Photography and Snowflakes

It is generally believed that no snowflake is the same because of one man and his obsession with looking at snow crystals: Wilson Bentley. Over the course of his life, Bentley photographed over 5000 snowflakes which were collected from around his home in Vermont over his lifetime (1865-1931). This impressive collection sparked curiosity among the scientific community into how snowflakes form and cemented Bentley’s place as the most dedicated observer of snow in history. I came across Bentley’s work whilst reading a book about snow, and his photographs and story have captivated me.

A snowflake will have one of a specific number of structures – such as dinner plates, branch networks, columns and ‘flower’ patterns – but with different detailing that makes it unique to any other. Up close, these internal symmetries and dendrites appear intricate and beautiful and is what captured the attention of Wilson Bentley as a fifteen year old boy when he first put a snowflake under a microscope.

Wilson Bentley's pictures of a series of plate snowflakes, circa 1902. Source: The Guardian

‘Under the microscope, I found that snowflakes were miracles of beauty and it seemed a shame that this beauty should not be seen and appreciated by others’. A series of plate snowflakes captured by Wilson Bentley. Source: The Guardian

Wilson Bentley lived all of his life in Mill Brook Valley, a small place in Vermont (New Hampshire, USA) which lies adjacent to the Green Mountains of Vermont and commonly receives high snowfall in the year. On receiving a microscope as a birthday present from his parents, Bentley became obsessed with looking at snow crystals gathered from around the town. A couple of years later he attached a bellows camera to his microscope and began photographing snow crystals. Microscope photography is now referred to as photomicrography, and Bentley was the first person in the world to perfect this technique.

Bentley’s set-up consisted of the bellows camera on top of the microscope, with a series of  attached pulleys and strings that controlled the focal length and focus of the camera. He would take a three-inch plate and create the luminous white shape of a snowflake on a field of black by scratching off the black emulsion from the photograph negative. Over a period of 50 years, he photographed more than 5000 snow crystals and eventually published a selection of these in ‘Snow Crystals’ in 1931 which propelled him to fame and attention from the scientific community.

Wilson Bentley in action with his set-up for photographing snowflakes (source: The Guardian)

Wilson Bentley in action with his set-up for photographing snowflakes (source: The Guardian)

Even when he was beginning to be acknowledged for his work in the 1920s, many people in the town thought he was mad for isolating himself in his garden shed obsessively studying snowflakes, including his father and his brother. At this point, he had been published in news outlets such as the New York Tribune and the Boston Herald, and was even featured in a short film called ‘Mysteries of the Snow’. He didn’t massively profit from this success, instead being content in doing the thing he loved. Shortly after his book ‘Snow Crystals’ was released, he died of pneumonia after insisting on walking back to his home through a blizzard.

Future studies showed that Bentley had only scratched the surface on snow crystal structures, partly because he exclusively studied snowflakes from Vermont. After his death, the scientific community became interested in exploring snow crystal structures, growing snow crystals in laboratory condition. This was largely led by Japanese nuclear physicist Ukichiro Nakaya, who could fine-tune temperature, pressure and moisture content in a controlled chamber to grow different snow crystal structures. Bentley’s six-sided stars and plates are just a few of the many varieties of structures that exist – prisms, columns, needles, triangular crystals, twelve-branched stars and irregular shapes are just some of the structures that can be grown under specific environmental conditions and are also found all over the world. This probably wouldn’t be known if it wasn’t for the work of Wilson Bentley.

'Every crystal was a masterpiece of design and no design was ever repeated'. A photograph of one of Wilson Bentley's snowflakes. Source: The Guardian.

‘Every crystal was a masterpiece of design and no design was ever repeated’. A photograph of one of Wilson Bentley’s snowflakes. Source: The Guardian

Today in Mill Brook Valley there is a small museum dedicated to Bentley and his work, with walls lined with his photography and his original contraption for taking these photographs. I would love to see this one day. What really captivated me about Bentley and his work was his unrelenting curiosity and his drive to share the beauty of snow crystal  structures that would eventually be scientifically translated. This is why, for similar reasons, I like using time-lapse photography to capture the dynamics of glaciers – images are not only scientifically valuable, but also resonate with everyone regardless of their knowledge of snow and ice.


Further reading

This article and this article from the Guardian on Bentley’s photography

The Snow Tourist by Charlie English which contains a detailed chapter on Bentley’s life work and also more generally on studies of snowflakes. I plan on writing a review when I have finished the book – it’s very good so far!

PhD Update: September 2016

I have been in Svalbard (again) for most of September, collecting images from our 14 time-lapse cameras that we have based in Kongsfjorden and Tempelfjorden. We haven’t seen these cameras since May 2016 (Kongsfjorden cameras) and August 2015 (Tempelfjorden cameras) so it was quite nerve-racking to go back and see if everything had worked. We had a couple of disappointments but generally the retrieval was a success, with approximately 130,000 photos collected in total.

Ten time-lapse cameras were deployed in Kongsfjorden last May (click here for more info on the deployment). Eight of these were installed on Collethøgda, overlooking Kronebreen, a fast-flowing marine-terminating glacier at the end of the fjord.  It is hoped that the close array of images from these cameras can be used to generate three-dimensional time-lapse sequences using a technique called Structure-from-Motion (SfM) which uses images from multiple angles to generate 3D point clouds of a target.

The other two cameras were installed by Kongsbreen and Kongsvegen, the two glaciers adjacent to Kronebreen. The data from these cameras form part of a longer-term project to monitor glaciers in the Kongsfjorden area. It was of particular importance to the influence of submarine melting on glacial retreat in this area.

Our camera at Kongsbreen... survived and still working! (September 2016)

Our camera at Kongsbreen… survived and still working! When were first started installing cameras in Svalbard, we would bolt them into the bedrock and use guide wires to stabilise them. Over time we have learnt that building cairns around the tripod legs is just as effective and takes much less time. We had a particularly long time around this camera site in May to build a large cairn… and do some sunbathing.

Due to bad weather, it proved difficult to access the camera sites and were limited to only two days of helicopter time to retrieve data. We had hoped to have enough time to survey and maintain each of the cameras so that they could run over the winter season, but alas! that is the beauty of fieldwork – you have to work with the weather you have. We managed to retrieve all of the memory cards from the cameras in the end, but couldn’t complete the camera surveying.

Previously we had deployed 7 time-lapse cameras in 2014 and 8 cameras in 2015, so we knew we were being ambitious with 10. In total, 6 worked through the entire season collecting images either every 10 minutes or every 30 minutes. We have had better success in the past (5/7 in 2014 and 6/8 in 2015) so we were a little disappointed that we weren’t able to beat our personal best! All of the problems were related to the power supply – temperamental solar controllers did not recharge the batteries from the solar panels, and there were poor connections in the camera boxes that had developed over the duration in the field.

Overall, 48 000 images were collected from the cameras at Kongsfjorden – we have a good sequence from Kongsbreen showing multiple submarine plumes creating inlets in the ice front, good coverage over the front of Kronebreen to look at calving activity and surface velocities over the summer season, and a good sample dataset to begin looking at constructing 3D SfM time-lapse sequences.

As the weather was so limiting on our helicopter time, we also accessed the shoreline next to Kronebreen by boat, where we set up our 4K video camera (left over from the CalvingSEIS project last month) to record calving activity. We recorded an 11-hour 4K video sequence which provides some awesome close-ups on isolated calving events such as the one in the video below.

This work is so important to ensure the safety of tourists and scientists alike. Currently the minimum safe distance from a calving front is 200 metres, but accidents do still happen. The distance that ice can be thrown from a calving event is thought to be controlled by the height of the calving origin and the impact with the water. With this in mind, the minimum safe distance should be different for each calving glacier front in Svalbard. We hope that we can track projectiles from such calving events in this sequence to re-assess the distance that boats should be from calving  glacier fronts in Svalbard. It is likely that glacier calving fronts require different categories of risk based on calving activity (frequency and volume), ice cliff height and ocean temperature.

Preparing for our helicopter ride over to Tunabreen (September 2016)

Preparing for our helicopter ride over to Tunabreen. Mats (pilot, left) is ‘composing himself for the flight’ whilst Harold (technician, centre) is doing routine checks on the helicopter. Chris Borstad (UNIS, right) joined us on this trip to check the time-lapse cameras and survey the glacier surface using a laser scanner to look at crevasse propagation rates in the upper section of the glacier tongue.

After finishing in Kongsfjorden, we flew back from Ny Ålesund to Longyearbyen and got a lucky opportunity to fly to Tunabreen and collect data from 4 time-lapse cameras that have been there for over a year now (see here for information on the installations and other work in this area). They were meant to be collected in September 2015, but the plan had to be abandoned due to poor weather. We also planned to retrieve them at the beginning of this year, but the warm winter had left Tempelfjorden first without sea ice for snow scooter transport and then with too much sea ice for the boat season.

After some manic negotiations with the Sysselmannen (Governor of Svalbard), we got permission for two helicopter landings on Ultunafjell, where the time-lapse cameras were installed. When flying over, it was impressive to see how much the calving front has changed, even over the past couple of months. Normally there is one consistent submarine plume at the west side of the calving front (near to the camera in the image below) that is active throughout the melt season, creating an inlet in the calving front. This year though, it appears that a second strong plume at the east side of the calving front  has created a marked inlet (see far inlet in the image below). The upper section of the glacier tongue has also changed, with the crevasse field extending much further up-glacier than in previous years. Both the growth of the crevasse field and the change in submarine plume activity could indicate a change in the subglacial conditions at Tunabreen.

The calving front of Tunabreen (September 2016)

The calving front of Tunabreen. The muddy water in front of the glacier is where the submarine plume has been strong enough to entrain sediment from the sea bed to the surface through turbulent mixing of freshwater and seawater. This promotes melting of the ice below the waterline, which has created two inlets in the calving front this year – the first is closest to the camera with a very visible plume adjacent, the second is the marked bay on the far side.

Three of the cameras on Ultunafjell were entrained on the calving front and lower section of Tunabreen, all of which had captured images till now. Unfortunately, due to unknown circumstances, two of the cameras were taking images that were out of focus when they came back on in the spring (after hibernating over the winter). It is likely that either someone has been up there, taken a look at the cameras and accidentally knocked the focusing ring on the lenses; or that high winds caused vibrations in the camera box that gradually shifted the focusing ring.

It’s a new set of circumstances for us anyway! From now on, we will fix the focusing ring in position by taping each lens. Luckily, one camera did not experience focus drift so we have three sets of images from August till November 2015, and one set of images from May to September 2016. This is plenty to work with and will give us a nice dataset to extract velocities and calving rate from.

The fourth camera is positioned further up the ridge, looking at the upper section of the glacier tongue where crevasses are begin to form and propagate. It was installed to monitor an array of strain meters that were set out on the glacier surface, measuring the rate at which crevasses were opening and the rate of longitudinal stretching. The relative distance between each strain meter in the images can be used to ensure that the strain meters are accurately measuring changes at the glacier surface. This camera has captured images every 10 minutes from August 2015 till September 2016, which is a great success. The camera has been surveyed and will now continue to take photos through the rest of 2016 into 2017, providing a complimentary dataset for Chris Borstad and the University Centre in Svalbard (UNIS) to use with other on-glacier instruments.

sampleimg

Sample image from the time-lapse sequence at the upper section of Tunabreen. These images monitor an area that is 497.6 m x 331.7 m. The strain meters are difficult to find in this image, with each strain meter box only represented as a 2 x 2 pixel square!

sampleimg_closeup

A close-up of the strain meters. The people in the image are myself and Doug Benn, part of the team that installed the seven strain meters on Tunabreen in August 2015.

So, in total, we have collected approximately 130,000 images in this month, providing us with a third consecutive year of time-lapse data at Kronebreen, and new insights into processes at Tunabreen and Kongsbreen. From these images, we should be able to extract a record of surface velocities, calving rate, submarine plume activity and crevasse propagation from each glacier. I am now back from Svalbard for this rest of this year to begin processing this data and enjoy Edinburgh in the autumn/winter season.

A tame ptarmigan at Tunabreen (September 2016)

A ptarmigan at Tunabreen. This little guy was walking along with me to visit our third time-lapse camera. Ptarmigans often nest around our cameras at both Tunabreen and Kronebreen – this makes for lovely images, but is a hinderance for photogrammetry processing!


With thanks to the following for making this fieldwork possible: Richard Delf (University of Edinburgh), Jack Kohler (NP), Chris Borstad (UNIS), our helicopter pilots Mats Larsen and Harold Edorsen, our skipper Wojtek Moskal,  and all in the NP Sverdrup station in Ny Ålesund.

PhD Update: August 2016

The month started with troubleshooting ongoing uncertainties with projection of measurements from the two-dimensional image coordinates to real-world positions. This is a crucial step in photogrammetry for gaining measurements from images.

The CalvingSEIS group camp set-up besides Kronebreen glacier. The two tents contain valuable equipment - mainly the radar systems and the lidar system which were being used to scan the calving front of the glacier (August 2016)

The CalvingSEIS group camp set-up besides Kronebreen glacier. The two tents contain valuable equipment – mainly the radar systems and the lidar system which were being used to scan the calving front of the glacier (August 2016)

Our software (called PyTrx) is currently projecting points slightly off from their actual position. We have been looking at determining the position of the glacier front and comparing this to LandSat satellite imagery to better understand why this offset is occurring. Knowing the terminus position through time at high-frequency intervals is also useful in determining where calving rates are highest in relation to the upglacier surface velocities.

The second half of August saw us begin the transition from time-lapse photography to videography, with our first attempt to capture calving activity at Kronebreen glacier (Svalbard) using video cameras as part of the CalvingSEIS project. The main aim of CalvingSEIS is to better understand calving activity at ocean-terminating glacier fronts using a variety of high-precision, high-frequency techniques – seismic detection, radar scanning, lidar scanning, submarine acoustic monitoring and echo-sounding, and time-lapse photogrammetry/videography. The fieldwork involved setting a base camp on the shore next to Kronebreen and having all instruments running simultaneously each day to capture calving activity. It was very intense but I am so pleased to have been a part of it and working with such a great group of people. I hope to do a separate post fully outlining the aims, the fieldwork and the outcomes of the CalvingSEIS project.

PiM (Pierre-Marie Lefeuvre, UiO) and I setting up one of the time-lapse cameras high up on the moraine to capture calving events at Kronebreen glacier. These cameras were capturing images every three seconds (August 2016)

PiM (Pierre-Marie Lefeuvre, UiO) and I setting up one of the time-lapse cameras high up on the moraine to capture calving events at Kronebreen glacier. These cameras were capturing images every three seconds (August 2016)

Next month I have to go back to Svalbard yet again to download data from our cameras which have been monitoring glaciers in the Kongsfjorden area since May 2016. I feel like the fieldwork is never going to end… and I really hope it doesn’t!

PhD Update: July 2016

The majority of July has been focused on widening the applications of the Area class in PyTrx, which is being developed to determine real world areal data from oblique photography. Specifically I have been working on detecting visible plume extent. Unlike surface lake extent, plume detection has proved difficult to automate due to poor contrast. However, I have made an alternative set of functions to manually distinguish plume extent which look promising for yielding high-frequency, high-resolution areal data.

A submarine plume is an upwelling of freshwater from an ocean-terminating glacier terminus. A sediment-rich, ‘muddy’ area of water forms in cases where this upwelling reaches the ocean surface. This upwelling is largely caused by the density difference between fresh water and salt water, creating a column of turbulent water that promotes melting of the glacier front in its immediate vicinity. This submarine melting is considered to be one of the main controls on ice calving in tidewater settings. Plumes also provide significant feeding grounds for birds, seals and other local wildlife in the area – small organisms (which survive in saltwater) are stunned when they come into contact with freshwater from the glacier and are transported to the surface via the upwelling plume column. Birds feed off these stunned organisms at the surface whilst seals and other sea life feed from organisms entrained in the upwelling plume column.

tuna_plume

A submarine plume emerging at the ocean surface in front of Tunabreen glacier in Svalbard (August 2015)

Monitoring the areal extent of plumes is thus vital to understanding current and future glacier dynamics and wildlife feeding tendencies. Building on the automated detection of surface lakes (for more information, click here), I first attempted to automate the detection of plume extent from oblique time-lapse images based on pixel intensity (i.e. the RBG signature that denotes the ‘colour’ of a pixel). Unlike the detection of lakes, the contrast between the plume and surrounding fjord water is often quite poor. Sunlight glare off the water surface can also create false extents and obscure the plume (see example in the GIF sequence below).

A submarine plume at Kronebreen, with one image taken every hour.

A sample of our time-lapse images from Kronebreen glacier, Svalbard. This sequence covers twelve hours (real-time) from 9am-9pm during the peak summer melt season, with one image taken every hour. A submarine plume can be seen in the foreground growing and shrinking through the course of the day.

In most instances the plume extent needed to be manually defined, hence I created a collection of functions within PyTrx* for manual extent definition. The extent is defined by manually plotting points onto the image that denote the plume’s boundary. The first GIF below shows those points plotted on to each image, forming polygons that show the plume’s extent over a twelve hour period (9am – 9pm, July 2015).  The plume extent grows and subsides over the course of a day during the summer melt season.

These points are projected from the image plane to the real-world scene using a process called georectification, for which the following parameters need to be known:

  1. Camera location
  2. Camera pose (represented as the camera’s yaw, pitch and roll)
  3. Discrepancies between the image plane and the real-world scene created by assymetry in the camera lens and misalignment between the camera lens and camera sensor (called the radial and tangential distortions)
  4. Known geographical points in the landscape, such as peaks and geographical features
  5. Digitial Elevation Model (DEM) of the landscape.

These parameters are used to mathematically represent the translation between the image environment and the real-world environment. The real world coordinates of the points can then be used to calculate the actual area of the plume extent, simply by forming polygons from the set of coordinates.

plumeextentgif

plumepolygif

Plume detection in the image scene and projection to the real-world environment (polygon overlaid onto a scene from Landsat). Note: the projection is slightly wrong as you can see the plume origin is slightly off-centre from the ice embayment. We are still trying to diagnose why this is happening. It is likely to be an unknown anomaly in the projection, or a mismatch between the polygon and Landsat datums.

This short twelve-hour sequence shows promising results and the method will next be implemented on larger image sequences to observe longer-term variations in plume extent. It is expected that the plume extent is controlled by melt volume, the rate at which melt is transferred to the glacier front, fjord temperature/salinity and prevailing wind direction. Over the twelve hour period studied here, it is likely that the plume extent is controlled by changes in melt volume, which is understood to increase and decrease on a daily basis. There are few longer-term observations of plume dynamics at such a high temporal resolution, so it will be interesting to see exactly how a plume evolves over a summer melt season.

Graph showing plume extent over the course of a twelve-hour period in the summer melt season at Kronebreen glacier, Svalbard.

Graph showing plume extent over the course of a twelve-hour period in the summer melt season at Kronebreen glacier, Svalbard. These areas have been calculated using PyTrx and the set of functions for manual extent detection and projection.

 

* PyTrx is a set of photogrammetry tools specifically designed to obtain measurements (length, area and velocity) from oblique photography in glacial environments. PyTrx is programmed in Python and largely uses functions from the OpenCV toolbox. The first version of PyTrx will be made freely available at some point in the near future. 

 

PhD update: June 2016

I have spent this month focused on developing PyTrx, our analysis software for oblique time-lapse image sequences. In particular, I have been working on a set of functions that will automatically detect areal features in glacial environments, such as surface lakes and submarine plumes, and transform pixel regions to real world areas. I have been testing this on an image sequence from Kronebreen glacier in Svalbard, where we captured several surface lakes filling and draining over a summer melt season.

June kicked off to bad start when I agitated an old knee injury whilst at the gym. I’ve had bad knees for a large part of my life and thought most of the problem had been sorted after surgery in 2008. Unfortunately I am now looking at intensive physiotherapy and perhaps another round of surgery after rupturing a ligament… so I have been off my feet for a lot of this month.

But, turning a negative into a positive, it has meant that I have been able to concentrate on developing an additional module to PyTrx. PyTrx is the software that I have been developing as part of my PhD to obtain measurements from oblique time-lapse imagery – ‘Py’ signifying that it is coded in Python, an open access computing language; and ‘Trx’ to indicate that the software can be used to track measurements through sequential images in time. This was initially implemented to obtain velocity measurements from a time-lapse images of a glacier in Svalbard. These time-lapse images also showed several lakes pooling at the surface of the glacier, which simultaneously drained. What is unknown is how the drainage of these lakes affect the velocity of the surrounding region. A separate set of functions was needed to measure the surface area of these lakes.

Supraglacial lakes filling and draining in the upper section of Kronebreen glacier, Svalbard. The sequence covers June to July 2015, one image per day.

Supraglacial lakes filling and draining in the upper section of Kronebreen glacier, Svalbard. The sequence covers June to July 2015, one image per day.

Lakes are distinguished in an image based on the intensity of each pixel, which is determined by the three colour channels – red, blue and green – also referred to as the RGB values. Given an RBG range of the ‘lightest’ and ‘darkest’ regions of the lakes, they can be automatically distinguished and masked. Knowing where the camera is located and its pose, the pixel location of the lakes in the image can be translated to their position in the real world. For their position in the real world, we can determine their surface area.

The lake extents, as seen in real world coordinates from above, filling and draining as they move downglacier (to the left of the image)

The lake extents, as seen in real world coordinates from above, filling and draining as they move down-glacier (to the left of the image).

The software effectively runs, showing the main lakes from the front of the time-lapse image sequence growing and connecting to cover a 100 m area (approximately). There are still two problems that need rectifying though:

1. The lake areas are quite noisy, with ‘false’ lakes detected in some of the images. The next step will be to apply a filter to exclude areas that are too small to be lakes

2. Part of this sensitivity is due to changes in illumination from image to image. The most apparent illumination differences can be seen, with spikes in the total surface lake area associated to detection of these ‘false’ lakes. Unfortunately it is very difficult to change this in the software as it relies on the RGB value of the pixels, which are affected by the change in illumination. The only options are to either select images with more consistent illumination or apply an averaging algorithm to smooth out irregular area data.

Plot showing the surface area of all the surface lakes from image to image (02/06 - 13/07/2016)

Plot showing the surface area of all the surface lakes from image to image (02/06 – 13/07/2016). The three spikes in the data show where ‘false’ lakes have been detected due to changes in image illumination.

There have also been a couple of issues with the translation from pixel areas to real world areas (which is done here using a process called georectification), which has been ongoing for a while now. This process is not only used to determine real world areas, but also other real world measurements such as distance and velocity. It is hoped that when these problems are solved then PyTrx will be made freely available for others to use. Despite these limitations, I’m quite happy with this part of PyTrx and hopefully next month it can be used to measure the area of other glacial features, such as submarine plume extent.

So. Broken knees, working code… and Brexit (I wrote a blog post on my thoughts regarding the EU referendum here). That sums up my month. It’s not been the greatest month but I’ve tried to make the most of it. Hopefully July will go a little better.