Picking Up Penguins From Space

Danger Islands, off Antarctica. Landsat-8 image acquired on 7th December 2017. Image courtesy of NASA/USGS.

World Wildlife Day is the 3rd March, and so fittingly this blog is looking at how satellite imagery and remote sensing techniques were used to recently discover an unknown colony of 1.5 million Adélie penguins on the Danger Islands off the Antarctica Peninsula in the north-western Weddell Sea. Adélie penguins only live along the Antarctic coast, and they grow to a height of around 70cm and weigh between three and six kilograms.

The paper by ‘Multi-modal survey of Adélie penguin mega-colonies reveals the Danger Islands as a seabird hotspot by Borowicz et al was published in Scientific Reports on the 2nd March 2018. It is interestingly not only because of the discovery of unknown penguins but also because the research combines historic aerial imagery, satellite imagery, drone footage and remote sensing techniques.

The research has its roots in an earlier paper by Lynch and Schwaller from 2014, entitled ‘Mapping the Abundance and Distribution of Adélie Penguins Using Landsat-7: First Steps towards an Integrated Multi-Sensor Pipeline for Tracking Populations at the Continental Scale.’ It describes the development of an algorithm to analyse Landsat and high resolution imagery from WorldView-2 to estimate the size of penguin colonies based on the extent of the guana area. A classification approach was developed from a training dataset of 473 Landsat-7 pixels covering existing Adeline colonies, supported by over 10,000 pixels relating to features such as rock, soil and vegetation.

In the recently published paper, of which Heather Lynch was also a co-author, the team combined a range of imagery alongside some in-situ data to achieve their results. Different types of imagery were used:

  • High Resolution Imagery: Areas of guano staining on the Danger Islands were identified manually from WorldView-2 scenes.
  • Historical aerial photographs: Images taken by Falkland Islands Dependencies Aerial Survey Expedition (FIDASE) on the 31st January 1957 were digitally scanned and geo-referenced to the WorldView-2 data. They were then divided into polygons and analysed using manual classification processing using the open source QGIS software.
  • Landsat: The algorithm previously developed by Lynch and Schwaller was enhanced to work with data from Landsat-4, 7 and 8 by calculating the mean difference of similar bands from Landsat-4 and 8 compared to Landsat-7, and then adjusting based on the mean differences in each spectral band. The enhanced algorithm was then used to classify the penguin colony areas.
  • Drone data: Using a 1.2 megapixel camera flown at height of between 25 m and 45 m, captured footage was processed to produce georeferenced orthomosaics of the Danger Islands. Machine learning techniques were then applied using a deep neural network to locate and identify potential penguins. A training dataset of 160 images with 1237 penguins, followed by a validation dataset of 93 images with 673 penguins was used to teach the network. Once fully trained it analysed all the islands, and the results were validated with a number of manual counts. The scientists worked on an accuracy of plus or minus ten percent for the automated counts, although the variation with the in-situ counts was only 0.6 percent.

The outcome of this research was an identification of 751,527 pairs of previously unknown Adélie penguins on the Danger Islands. More surprisingly is that this increases the world estimates of this type of penguin by almost 50%, when it had been thought that the population had been declining for the last 40 years. The historical aerial imagery has led scientists to speculate that this new colony has remained constant for around the last 60 years in contrast to other known colonies.

This work is a great example of not only how much can be achieved with free-to-access imagery, but also how satellite imagery is helping us discover new things about our planet.

Four Key Earth Observation Trends For 2018

Blue Marble image of the Earth taken by the crew of Apollo 17 on Dec. 7 1972.
Image Credit: NASA

This week we’re looking at this year’s key trends in Earth Observation (EO) that you need to know.

Rise of the Data Buckets!
EO data is big! Anyone who has tried to process EO data knows the issues of downloading and storing large files, and as more and more data becomes available these challenges will grow. Amazon recognised this issue and set up Amazon Web Services which automatically downloads all freely available data such as Copernicus and Landsat, offering people who want to process data a platform where they don’t have to download the data – for a price!

The European Commission also picked up on this and awarded four commercial contracts at the end of last year to establish Copernicus Data and Information Access Services (DIAS) which will offer scalable processing platforms for the development of value-added products and services.

The four successful DIAS consortiums are led by Serco Europe, Creotech Instruments, ATOS Integration & Airbus Defence and Space respectively, and a fifth DIAS is planned to be established by EUMETSAT. It’s hoped this will kick-start the greater use and exploitation of Copernicus data.

Continued Growth of Data
There are some exciting EO launches planned this year continuing to increase the amount of data available. Earlier this week China launched the last two satellites of the high resolution optical SuperView constellation. In addition, some of the key larger satellites going into orbit this year include:

  • ESA’s Sentinel-3B and its Aeolus wind mission.
  • NASA’s Gravity Recovery and Climate Experiment Follow-on (GRACE-FO) and the Ice, Cloud and land Elevation Satellite (ICESat-2).
  • Japan’s Advanced Satellite with New system Architecture for Observation (ASNARO 2) which is x-band SAR radar satellite with a 1 m ground resolution.
  • NOAA’s GOES-S is the second of four upgraded weather observatories.

In addition, as we described last week, cubesats will continue to have regular launches. We are still a long way from the high watershed of EO data!

SaaS Will Become The Norm
The rise of the data buckets will encourage the Software-as-a-service (SaaS) approach to EO to become the norm. Companies will develop products and services and offer them to customers on a platform via the internet, rather than the historic bespoke application approach. For companies this will be a more effective way of using their resources and will allow them to better leverage products and services. For the customers, it will enable them greater use EO and geospatial data without the need for expert knowledge.

Pixalytics is due to launch its own Product Portal at the Data.Space 2018 conference at the end of this month.

Artificial Intelligence (AI)
AI is becoming more and more important to EO. Part of this is the natural development of AI, however certain EO tasks are far more suited to AI. For example, change detection, identification of new artefacts in imagery, etc. These aspects have a base image and looking for differences, computers can do this much quicker than any human researcher. Although, it’s also true that humans can see artefacts much more easily than you can program a computer to identify them. Therefore, these AI applications are strongly dependent on training datasets created by humans.

However, things are now moving beyond these simple AI tasks and it’s becoming an integral part of EO products and services. For example, last year Microsoft launched their AI for Earth programme, support by a $50 m investment, which will deploy their cloud computing, AI and other technology to researchers around the world to help develop new solutions for the agriculture, biodiversity, climate change, and water challenges on the planet.

Summary
These are a snapshot of our view of the key trends. What do you think? Have we missed anything? Let us know.

Merry Christmas!

UK at night. November 2017 monthly composite from the Visible Infrared Imaging Radiometer Suite,(Day/Night Band). Image and Data processing courtesy of Earth Observation Group, NOAA/NCEI.

MERRY CHRISTMAS

AND BEST WISHES FOR 2018 

from everyone at Pixalytics

Unintended Consequences of Energy Saving

Black Marble 2016: Composite global map created from data acquired by VIIRS in 2016. Image courtesy of NASA/NASA’s Earth Observatory.

Last month a report in Science Advances got a lot of publicity as it described the increase in global light pollution following research using satellite data. Even more interesting was the fact that one of the key drivers, although not the only one, was the switch to LED lights which have mainly being bought in due to their increased energy efficiency.

Recently there has been a lot of night-time imagery released as photographs taken from the International Space Station, and we’ve used them in our blogs. However, night time imagery has also been collected from the uncalibrated Operational Linescan System (OLS) on the Defense Meteorological Satellite Program (DMSP) satellites for a number of years. This was followed by the Suomi National Polar-orbiting Partnership (Suomi NPP) research mission in 2011 that carries the Visible Infrared Imaging Radiometer Suite (VIIRS) which had a planned life expectancy of around five years, however it is still in orbit and continues to collect data. Much more recently, on the 18th November 2017, a second VIIRS instrument was launched aboard the NOAA-20 satellite (previously called JPSS-1).

The role of LED lights in the increase in light pollution was described in detail in the paper ‘Artificially lit surface of Earth at night increasing in radiance and extent’ by Kyba et al which was published on the 22nd November 2017. The paper was based on satellite data collected between 2012 and 2016 from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite and one of the key drivers behind the new research is that VIIRS offered the first calibrated and georeferenced night time radiance global dataset. Within the 22 spectral bands the instrument measures is a day/night panchromatic band (DNB). This band has a 750 m spatial resolution and operates on a whiskbroom approach with a swath of approximately 3,000 km which means it provides global coverage twice a day, visiting every location at 1:30 pm and 1:30 am (local time).

The team from the GFZ German Research Centre for Geosciences who did the research concluded that outdoor light pollution has increased by 11% over 5 years. However, for us, the really interesting part was that new LED lights are linked to this increase in light pollution.

Over the last decade within the UK, a lot of local Councils have switched to using LED streetlights mainly due to the energy, and associated cost, savings. However, there was also a message that this would reduce light pollution as they would direct light downwards and reduce nightglow. This is coupled with the fact that businesses and consumers have also been pushed to move towards this type of light for the same reasons. This was brought home to us recently as a firm opposite our home installed new outside LED lights. It has made a significant different to the amount of light in our room and even in the middle of the night it is never completely black.

What the research team found by comparing VIIRS images from 2012 and 2016 was that:

  • The lower cost of LED lights has actually led to more lights going up, mainly on the outskirts of towns and cities. A 2010 paper by Tsao et al published in Physics Today indicated that we tend to purchase as much artificial light as possible for around 0.7% of GDP and so as lighting becomes cheaper, the quantity increases.
  • Flat composite global map created from data acquired by VIIRS in 2016. Image courtesy of NASA/NASA’s Earth Observatory.

    There has been a shift in the spectra of artificial light within cities from the yellow/orange of the old streetlights to the white of LED’s.

  • The majority of countries of the world had seen an increase in light pollution. Although, perhaps surprisingly some of the world’s brightest nations such the US, UK, Germany, Netherlands, Spain and Italy had stayed stable; which may suggest there is a point of saturation of outdoor lighting. The only countries that had less light pollution were areas of conflict or whether there was issue with the data, such as Australia where there were significant wildfires when the first data was collected.

Light pollution has a negative impact on flora and fauna, particularly nocturnal wildlife, and there is increasing evidence that it is also negative for humans. This is an example of why we have to be so careful with the concept of cause and effect. Decisions made for improved energy efficiency look to have had unintended consequences for light pollution.

To TEDx Speaking and Beyond!

Back in April I received an invitation to speak at the ‘One Step Beyond’ TEDx event organised at the National Space Centre in Leicester, with my focus on the Blue Economy and Earth Observation (EO).

We’ve been to a few TEDx events in the past and they’ve always been great, and so I was excited to have the opportunity to join this community. Normally, I’m pretty relaxed about public speaking. I spend a lot of time thinking about what I’m going to say, but don’t assemble my slides until a couple of days beforehand. This approach has developed in part because I used to lecture – where I got used to talking for a while with a few slides – but also because I always like to take some inspiration from the overall mood of the event I’m talking at. This can be through hearing other speakers, attending workshops or even just walking around the local area.

TEDx, however, was different. There was a need to have the talk ready early for previewing and feedback, alongside producing stunning visuals and having a key single message. So, for a change, I started with a storyboard.

My key idea was to get across the sense of wonder I and many other scientists share in observing the oceans from space, whilst also emphasising that anyone can get involved in protecting this natural resource. I echoed the event title by calling my talk “Beyond the blue ocean” as many people think of the ocean as just a blue waterbody. However, especially from space, we can see the beauty, and complexity, of colour variations influenced by the microscopic life and substances dissolved and suspended within it.

I began with an with an image called the ‘Pale Blue Dot’ that was taken by Voyager 1 at a distance of more than 4 billion miles from Earth, and then went with well-known ‘Blue Marble’ image before zooming into what we see from more conventional EO satellites. I also wanted to take the audience beyond just optical wavelengths and so displayed microwave imagery from Sentinel-1 that’s at a similar spatial resolution to my processed 15 m resolution Sentinel-2 data that was also shown.

Dr Samantha Lavender speaking at the One Step Beyond TEDx event in Leicester. Photo courtesy of TEDxLeicester

The satellite imagery included features such as wind farms, boats and phytoplankton blooms I intended to discuss. However, this didn’t quite to go to plan on my practice run through! The talk was in the planetarium at the National Space Centre, which meant the screen was absolutely huge – as you can see in the image to the right. However, with the lights on in the room the detail in the images was really difficult to see. The solution for the talk itself was to have the planetarium in darkness and myself picked out by two large spotlights, meaning that the image details were visible to the audience but I couldn’t see the audience myself.

The evening itself took place on the 21st September, and with almost two hundred in the audience I was up first. I was very happy with how it went and the people who spoke to me afterwards said they were inspired by what they’d seen. You can see for yourself, as the talk can be found here on the TEDx library. Let me know what you think!

I was followed by two other fantastic speakers who gave inspiring presentations and these are also up on the TEDx Library. Firstly, Dr Emily Shuckburgh, Deputy Head of Polar Oceans team at British Antarctic Survey discussed “How to conduct a planetary health check”; and she was followed by Corentin Guillo, CEO and Founder of Bird.i, who spoke about “Space entrepreneurship, when thinking outside the box is not enough”.

The whole event was hugely enjoyable and the team at TEDx Leicester did an amazing job of organising it. It was good to talk to people after the event, and it was fantastic that seventy percent of the audience were aged between 16 and 18. We need to do much more of this type of outreach activities to educate and inspire the next generation of scientists. Of course, for me, the day also means that I can now add TEDx Speaker to my biography!

5 Signs You Work In Earth Observation

Sentinel-2A image of UK south east coastline, acquired on 4th September 2017. Data courtesy of ESA/Copernicus.

Do you recognise yourself in any these five signs? if so, you’re definitely working in the Earth observation industry.

  1. You have a favourite satellite or instrument, or image search tool.
  2. When a satellite image appears on television, you tell everyone in the room which satellite/sensor it came from.
  3. You’ve got an irrational hatred for clouds (unless you’re working on clouds or using radar images).
  4. Anything space related happens and your family asks whether you’re involved with it, and thinks you know everyone who works at NASA or ESA.
  5. Your first reaction to seeing an interesting location isn’t that you should plan to go there. Instead, you wonder whether it would make a good satellite image.

We tick all of these signs at Pixalytics! Last week we suffered from number five when we saw a snippet from the season finale of the UK TV programme ‘Liar’. It wasn’t a programme we’d watched, but as we caught an atmospheric panning shot of the location, and only one thought when through our minds, ‘That would make a great satellite image!’

It was a stunning shot of a marshland with water interwoven between islands. Without knowing anything about the programme, we were expecting it to have been filmed in a far flung Nordic location. Following a bit of impromptu googling we were surprised to discover it was actually Tollesbury on the Essex coast in the UK. It also turns out that we were late to the party on the discovery of the programme and the location.

Sentinel-2A image of Mersea Island and surrounding area, acquired on 4th September 2017. Data courtesy of ESA/Copernicus.

The image on the right shows Mersea Island, which has brown saltmarshes above it within the adjacent inlets of the Blackwater Estuary. To the left of the island is the village of Tollesbury and the Tollesbury marina, which is located within the saltmarshes. This area is the largest of the saltmarshes of Essex, but only the fifth largest of the UK. They play a key role in flood protection and can reduce the height of damaging waves in storm surge conditions by 20%. However, they are disappearing due to sea erosion that’s caused a sixty percent reduction in the last 20 years.

The image itself is a zoomed in pseudo-true-colour composite at 10 m spatial resolution using data acquired by Sentinel-2A on the 4th September 2017 – a surprisingly cloud free day for the UK. The full Sentinel-2 image can be seen at the top of the blog.

As often happens when we look in detail at satellite images, something catches our eye. This time it was the three bluish looking strips just above Mersea island. These are the 82,944 solar panels which make up Langenhoe Solar Farm, and have the capacity to generate 21.15 MW of solar power.

So how many of you recognise our signs of working in Earth observation? Any you think we’ve missed? Get in touch, let us know!

Evolution of the Earth Observation Market

Artist's rendition of a satellite - 3dsculptor/123RF Stock Photo

Artist’s rendition of a satellite – 3dsculptor/123RF Stock Photo

The changing Earth Observation (EO) market has been a topic of office conversation this week at Pixalytics. We’re currently in the final stage of developing our own product portal, and it was interesting to see that some of our thoughts were echoed by reports from last week’s World Satellite Business Week event in Paris.

Unsurprisingly, speakers at the event agreed that the EO sector has huge growth potential. This is something we regularly see highlighted in various emails and press releases. For example, in the last few weeks we’ve had:

At a few thousand dollars for access to each report, we’ve said before that one of the products we should develop is an annual report on the EO market!

As we’ve been working towards our portal, one of issues we’ve identified is how difficult some portals are to navigate, particularly if you are not an EO expert. This was also recognised at the Paris event, with an acknowledgement that EO companies need to understand what customers want and then provide a user friendly experience to deliver those needs.

As reported by Tereza Pultarova in Space News, there was also discussion on the need to move away from simply selling data, and instead provide answers to the practical questions about the planet that businesses and consumers have. It is only through this transformation that new sectors and markets for EO will open which will be the key for the aforementioned future growth. The Paris event also highlighted some of the key trends that will be the backbone of this transformation:

  • Providing as close as possible to near real time data.
  • Increased data analytics, particularly through machine learning and artificial intelligence platforms to analyse data and highlight anomalies and changes faster.
  • Bringing satellite data together with social media information to rapidly enable context to be added to images.
  • Vertical integration within the industry within satellite firms acquiring with data processing and analytics companies; for example, Digital Globe acquired The Radiant Group earlier this year.
  • Processing data onboard satellites, so users download the information they want, rather than reams of data.

There was a really interesting analogy with the navigation industry given by Wade Larson, president and CEO of Urthecast. He said “Navigation became kind of embedded infrastructure in a much larger industry called location-based services. We think that this is happening with geoanalytics.”

This is the direction of travel for the industry, and some players are moving faster than others. Last week Airbus confirmed their four satellite very high-resolution-imaging constellation, Pléiades Neo, is on schedule for launch in 2020. This will have 30 cm spatial resolution and will utilise the Space Data Highway, also known as the European Data Relay System (EDRS), to stream the images into an online platform. The ERDS uses lasers to transfer up to 40 terabytes a day at a speed of up to 1.8 Gbits per second, meaning users will have access to data in near real time.

This evolution of the EO market needs to be recognised by every company in the industry from the Airbus down to the small company’s trying to launch their own product portal. If you don’t move with the changing market, you won’t get any of the market.

Supporting Soil Fertility From Space

Sentinel-2 pseudo-true colour composite from 2016 with a Kompsat-3 Normalized Difference Vegetation Index (NDVI) product from 2015 inset. Sentinel data courtesy of ESA/Copernicus.

Last Tuesday I was at the academic launch event for the Tru-Nject project at Cranfield University. Despite the event’s title, it was in fact an end of project meeting. Pixalytics has been involved in the project since July 2015, when we agreed to source and process high resolution satellite Earth Observation (EO) imagery for them.

The Tru-Nject project is funded via Innovate UK. It’s official title is ‘Tru-Nject: Proximal soil sensing based variable rate application of subsurface fertiliser injection in vegetable/ combinable crops’. The focus is on modelling soil fertility within fields, to enable fertiliser to be applied in varying amounts using point-source injection technology which reduces the nitrogen loss to the atmosphere when compared with spreading fertiliser on the soil surface.

To do this the project created soil fertility maps from a combination of EO products, physical sampling and proximal soil sensing – where approximately 15 000 georeferenced hyperspectral spectra are collected using an instrument connected to a tractor. These fertility maps are then interpreted by an agronomist, who decides on the relative application of fertiliser.

Initial results have shown that applying increased fertiliser to areas of low fertility improves overall yield when compared to applying an equal amount of fertiliser everywhere, or applying more fertiliser to high yield areas.

Pixalytics involvement in the work focussed on acquiring and processing, historical, and new, sub 5 metre optical satellite imagery for two fields, near Hull and York. We have primarily acquired data from the Kompsat satellites operated by the Korea Aerospace Research Institute (KARI), supplemented with WorldView data from DigitalGlobe. Once we’d acquired the imagery, we processed it to:

  • remove the effects of the atmosphere, termed atmospheric correction, and then
  • converted them to maps of vegetation greenness

The new imagery needed to coincide with a particular stage of crop growth, which meant the satellite data acquisition period was narrow. This led to a pleasant surprise for Dave George, Tru-Nject Project Manager, who said, “I never believed I’d get to tell a satellite what to do.’ To ensure that we collected data on specific days we did task the Kompsat satellites each year.

Whilst we were quite successful with the tasking the combination of this being the UK, and the fact that the fields were relatively small, meant that some of the images were partly affected by cloud. Where this occurred we gap-filled with Copernicus Sentinel-2 data, it has coarser spatial resolution (15m), but more regular acquisitions.

In addition, we also needed to undertake vicarious adjustment to ensure that we produced consistent products over time whilst the data came from different sensors with different specifications. As we cannot go to the satellite to measure its calibration, vicarious adjustment is a technique which uses ground measurements and algorithms to not only cross-calibrate the data, but also adjusts for errors in the atmospheric correction.

An example of the work is at the top, which shows a Sentinel-2 pseudo-true colour composite from 2016 with a Kompsat-3 Normalized Difference Vegetation Index (NDVI) product from 2015 inset. The greener the NDVI product the more green the vegetation is, although the two datasets were collected in different years so the planting within the field varies.

We’ve really enjoyed working with Stockbridge Technology Centre Ltd (STC), Manterra Ltd, and Cranfield University, who were the partners in the project. Up until last week all the work was done via telephone and email, and so it was great to finally meet them in-person, hear about the successful project and discuss ideas for the future.

Landsat Turns 45!

False colour image of Dallas, Texas. The first fully operational Landsat image taken on July 25, 1972, Image courtesy: NASA’s Earth Observatory

Landsat has celebrated forty-five years of Earth observation this week. The first Landsat mission was Earth Resources Technology Satellite 1 (ERTS-1), which was launched into a sun-synchronous near polar orbit on the 23 July 1972. It wasn’t renamed Landsat-1 until 1975. It had an anticipated life of 1 year and carried two instruments: the Multi Spectral Scanner (MSS) and the Return-Beam Vidicon (RBV).

The Landsat missions have data continuity at their heart, which has given a forty-five year archive of Earth observation imagery. However, as technological capabilities have developed the instruments on consecutive missions have improved. To demonstrate and celebrate this, NASA has produced a great video showing the changing coastal wetlands in Atchafalaya Bay, Louisiana, through the eyes of the different Landsat missions.

In total there have been eight further Landsat missions, but Landsat 6 failed to reach its designated orbit and never collected any data. The missions have been:

  • Landsat 1 launched on 23 July 1972.
  • Landsat 2 launched on 22 January 1975.
  • Landsat 3 was launched on 5 March 1978.
  • Landsat 4 launched on 16 July 1982.
  • Landsat 5 launched on 1 March 1984.
  • Landsat 7 launched on 15 April 1999, and is still active.
  • Landsat 8 launched on 11 February 2013, and is still active.

Landsat 9 is planned to be launched at the end 2020 and Landsat 10 is already being discussed.

Some of the key successes of the Landsat mission include:

  • Over 7 million scenes of the Earth’s surface.
  • Over 22 million scenes had been downloaded through the USGS-EROS website since 2008, when the data was made free-to-access, with the rate continuing to increase (Campbell 2015).
  • Economic value of just one year of Landsat data far exceeds the multi-year total cost of building, launching, and managing Landsat satellites and sensors.
  • Landsat 5 officially set a new Guinness World Records title for the ‘Longest-operating Earth observation satellite’ with its 28 years and 10 months of operation when it was decommissioned in December 2012.
  • ESA provides Landsat data downlinked via their own data receiving stations; the ESA dataset includes data collected over the open ocean, whereas USGS does not, and the data is processed using ESA’s own processor.

The journey hasn’t always been smooth. Although established by NASA, Landsat was transferred to the private sector under the management of NOAA in the early 1980’s, before returning to US Government control in 1992. There have also been technical issues, the failure of Landsat 6 described above; and Landsat 7 suffering a Scan Line Corrector failure on the 31st May 2003 which means that instead of mapping in straight lines, a zigzag ground track is followed. This causes parts of the edge of the image not to be mapped, giving a black stripe effect within these images; although the centre of the images is unaffected the data overall can still be used.

Landsat was certainly a game changer in the remote sensing and Earth observation industries, both in terms of the data continuity approach and the decision to make the data free to access. It has provided an unrivalled archive of the changing planet which has been invaluable to scientists, researchers, book-writers and businesses like Pixalytics.

We salute Landsat and wish it many more years!

If no-one is there when an iceberg is born, does anyone see it?

Larsen C ice Shelf including A68 iceberg. Image acquired by MODIS Aqua satellite on 12th July 2017. Image courtesy of NASA.

The titular paraphrasing of the famous falling tree in the forest riddle was well and truly answered this week, and shows just how far satellite remote sensing has come in recent years.

Last week sometime between Monday 10th July and Wednesday 12th July 2017, a huge iceberg was created by splitting off the Larsen C Ice Shelf in Antarctica. It is one of the biggest icebergs every recorded according to scientists from Project MIDAS, a UK-based Antarctic research project, who estimate its area of be 5,800 sq km and to have a weight of more a trillion tonnes. It has reduced the Larsen C ice Shelf by more than twelve percent.

The iceberg has been named A68, which is a pretty boring name for such a huge iceberg. However, icebergs are named by the US National Ice Centre and the letter comes from where the iceberg was originally sited – in this case the A represents area zero degrees to ninety degrees west covering the Bellingshausen and Weddell Seas. The number is simply the order that they are discovered, which I assume means there have been 67 previous icebergs!

After satisfying my curiosity on the iceberg names, the other element that caught our interest was the host of Earth observation satellites that captured images of either the creation, or the newly birthed, iceberg. The ones we’ve spotted so far, although there may be others, are:

  • ESA’s Sentinel-1 has been monitoring the area for the last year as an iceberg splitting from Larsen C was expected. Sentinel-1’s SAR imagery has been crucial to this monitoring as the winter clouds and polar darkness would have made optical imagery difficult to regularly collect.
  • Whilst Sentinel-1 was monitoring the area, it was actually NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Aqua satellite which confirmed the ‘birth’ on the 12th July with a false colour image at 1 km spatial resolution using band 31 which measures infrared signals. This image is at the top of the blog and the dark blue shows where the surface is warmest and lighter blue indicates a cooler surface. The new iceberg can be seen in the centre of the image.
  • Longwave infrared imagery was also captured by the NOAA/NASA Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite on July 13th.
  • Similarly, NASA also reported that Landsat 8 captured a false-colour image from its Thermal Infrared Sensor on the 12th July showing the relative warmth or coolness of the Larsen C ice shelf – with the area around the new iceberg being the warmest giving an indication of the energy involved in its creation.
  • Finally, Sentinel-3A has also got in on the thermal infrared measurement using the bands of its Sea and Land Surface Temperature Radiometer (SLSTR).
  • ESA’s Cryosat has been used to calculate the size of iceberg by using its Synthetic Aperture Interferometric Radar Altimeter (SIRAL) which measured height of the iceberg out of the water. Using this data, it has been estimated that the iceberg contains around 1.155 cubic km of ice.
  • The only optical imagery we’ve seen so far is from the DEMIOS1 satellite which is owned by Deimos Imaging, an UrtheCast company. This is from the 14th July and revealed that the giant iceberg was already breaking up into smaller pieces.

It’s clear this is a huge iceberg, so huge in fact that most news agencies don’t think that readers can comprehend its vastness, and to help they give a comparison. Some of the ones I came across to explain its vastness were:

  • Size of the US State of Delaware
  • Twice the size of Luxembourg
  • Four times the size of greater London
  • Quarter of the size of Wales – UK people will know that Wales is almost an unofficial unit of size measurement in this country!
  • Has the volume of Lake Michigan
  • Has the twice the volume of Lake Erie
  • Has the volume of the 463 million Olympic-sized swimming pools; and
  • My favourite compares its size to the A68 road in the UK, which runs from Darlington to Edinburgh.

This event shows how satellites are monitoring the planet, and the different ways we can see the world changing.