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.

Monitoring Water Quality from Space

Algal Blooms in Lake Erie, around Monroe, acquired by Sentinel-2 on 3rd August 2017. Data Courtesy of ESA/Copernicus.

Two projects using Earth Observation (EO) data to monitor water quality caught our eye recently. As we’re in process of developing two water quality products for our own online portal, we’re interested in what everyone else is doing!

At the end of January UNESCO’s International Hydrological Programme launched a tool to monitor global water quality. The International Initiative on Water Quality (IIWQ) World Water Quality Portal, built by EOMAP, provides:

  • turbidity and sedimentation distribution
  • chlorophyll-a concentration
  • Harmful Algal Blooms indicator
  • organic absorption
  • surface temperature

Based on optical data from Landsat and Sentinel-2 it can provide global surface water mosaics at 90 m spatial resolution, alongside 30 m resolution for seven pilot river basins.  The portal was launched in Paris at the “Water Quality Monitoring using Earth Observation and Satellite-based Information” meeting and was accompanied by an exhibition on “Water Quality from the Space – Mesmerizing Images of Earth Observation”.

The tool, which can be found here, focuses on providing colour visualizations of the data alongside data legends to help make it as easy as possible to use. It is hoped that this will help inform and educate policy makers, water professionals and the wider public about the value of using satellite data from monitoring water resources.

A second interesting project, albeit on a smaller scale, was announced last week which is going to use Sentinel-2 imagery to monitor water quality in Scottish Lochs. Dr Claire Neil, from the University of Stirling, is leading the project and will be working with Scottish Environment Protection Agency. It will use reflectance measures to estimate the chlorophyll-a concentrations to help identify algal blooms and other contaminants in the waters. The project will offer an alternative approach to the current water quality monitoring, which uses sampling close to the water’s edge.

An interesting feature of the project, particularly for us, is the intention to focus on developing this work into an operational capability for SEPA to enable them to improve their approach to assessing water quality.

This transition from a ‘good idea’ into an operational product that will be used, and therefore purchased, by end users is what all EO companies are looking for and we’re not different. Our Pixalytics Portal which we discussed a couple of weeks ago is one of the ways we are trying to move in that direction. We have two water quality monitoring products on it:

  • Open Ocean Water Quality product extracts time-series data from a variety of 4 km resolution satellite datasets from NASA, giving an overview what is happening in the water without the need to download a lot of data.
  • Planning for Coastal Airborne Lidar Surveys product provides an assessment of the penetration depth of a Lidar laser beam, from an airborne survey system, within coastal waters based on the turbidity of the water. This ensures that companies who plan overflights can have confidence in how far their Lidar will see.

We’re just at the starting point in productizing the services we offer, and so it is always good to see how others are approaching the similar problem!

Celebrating Landsat & the Winter Olympics

First Landsat image acquired in 2013 showing area around Fort Collins, Colorado. Data courtesy of NASA/USGS.

The Landsat programme achieved a couple of significant milestones over the last two weeks. Firstly, the 11th February marked the five year anniversary of the launch of Landsat 8 which took place at the Vandenberg Air Force Base, California, in 2013. The image to the right is the first one acquired by Landsat 8 and shows the area around Fort Collins, Colorado with the Horsetooth Reservoir very clear left of centre.

This anniversary is an interesting one because Landsat 8 was only designed for an operational life of five years. Obviously it has already exceeded this and these planned lifespans are very conservative. More often the amount of fuel on board is a more relevant assessment for lifespan and for Landsat 8 the initial assessment was a 10 year lifespan. However, even this tends to be a conservative estimate. As an example, nineteen years ago Landsat 7 was launched with similar planned operational lifespans. It is still working today, although there have been some degradation issues, and IT achieved its own significant milestone on the 1st February when it completed its 100,000th orbit of the Earth.

Landsat 8 is in a sun-synchronous orbit at an altitude of 705 km, circles the Earth every 98.9 minutes and in the last five years has undertaken over 26,500 orbits according to NASA who have produced a short celebratory video.

It has two main instruments, an Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS), which together measure eleven different spectral bands. The TIRS has two thermal bands which are used for sensing temperature, whereas the OLI measures nine spectral bands:

  • Three visible light bands that approximate red, green and blue
  • One near infrared band
  • Two shortwave infrared bands
  • Panchromatic band with a higher spatial resolution
  • The two final bands focus on coastal aerosols and cirrus clouds.

With the exception of the highest polar latitudes, Landsat 8 acquires images of the whole Earth every 16 days which has meant it has acquired over 1.1 million images of the Earth that accounts for 16 percent of all the data in the Landsat multi-mission archive.

Landsat 8 image of Pyeongchang, South Korea, which is hosting the 2018 Winter Olympics. Data acquired 11th February 2018. Data courtesy of NASA/USGS.

The image to the left is the Pyeongchang region of South Korea where the Winter Olympics are currently taking place acquired by Landsat on its five year anniversary on the 11th February. Pyeongchang is in the north west of South Korea in the TaeBaek Mountains just over one hundred miles from the capital, Seoul. The left area of the image shows the mountain range where the skiing, biathlon, ski jumping, bobsled, luge and skeleton events take place and to the right is the coastal city of Gangneung, where the ice hockey, curling, speed skating and figure skating are taking place.

With its forty-five year archive, Landsat offers the longest continuous dataset of Earth observations and is critical to researchers and scientists. Landsat 9 is planned to be launched in 2020 and Landsat 10 is already being discussed.

Congratulations to Landsat 7 and 8, and we look forward to many more milestones in the future.

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.

Have you read the top Pixalytics blogs of 2017?

World Cloud showing top 100 words from Pixalytics 2017 blogs

In our final blog of the year, we’re looking back at our most popular posts of the last twelve months. Have you read them all?

Of the top ten most read blogs, nine were actually written in previous years. These were:

You’ll notice that this list is dominated by our annual reviews of the number of satellites, and Earth observation satellites, orbiting the Earth. It often surprises us to see where these blogs are quoted and we’ve been included in articles on websites for Time Magazine, Fortune Magazine and the New Statesman to name a few!

So despite only being published in November this year coming in as the fourth most popular blog of the year was, unsurprisingly:

For posts published in 2017, the other nine most popular were:

2017 has been a really successful one for our website. The number of the views for the year is up by 75%, whilst the number of unique visitors has increased by 92%!

Whilst hard work, we do enjoy writing our weekly blog – although staring at a blank screen on a Wednesday morning without any idea of what we’ll publish a few hours later can be daunting!

We’re always delighted at meetings and conferences when people come up and say they read the blog. It’s nice to know that we’re read both within our community, as well as making a small contribution to informing and educating people outside the industry.

Thanks for reading this year, and we hope we can catch your eye again next year.

We’d like to wish everyone a Happy New Year, and a very successful 2018!

Big Data From Space

Last week I attended the 2017 Conference on Big Data from Space (BiDS’17) that was held in Toulouse, France. The conference was co-organised by the European Space Agency (ESA), the Joint Research Centre (JRC) of the European Commission (EC), and the European Union Satellite Centre (SatCen). It aimed to bring together people from multiple disciplines to stimulate the exploitation Earth Observation (EO) data collected in space.

The event started on Tuesday morning with keynotes from the various co-organising space organisations. Personally, I found the talk by Andreas Veispak, from the European Commission’s (EC) DG GROW department which is responsible for EU policy on the internal market, industry, entrepreneurship and SMEs, particularly interesting. Andreas has a key involvement in the Copernicus and Galileo programmes and described the Copernicus missions as the first building block for creating an ecosystem, which has positioned Europe as a global EO power through its “full, free and open” data policy.

The current Sentinel satellite missions will provide data continuity until at least 2035 with huge amounts of data generated, e.g., when all the Sentinel satellite missions are operational over 10 petabytes of data per year will be produced. Sentinel data has already been a huge success with current users exceeding what was expected by a factor of 10 or 20 and every product has been downloaded at least 10 times. Now, the key challenge is to support these users by providing useful information alongside the data.

The ESA presentation by Nicolaus Hanowski continued the user focus by highlighting that there are currently over 100 000 registered Copernicus data hub users. Nicolaus went on to describe that within ESA success is now being measured by use of the data for societal needs, e.g., the sustainable development goals, rather than just the production of scientific data. Therefore, one of the current aims is reduce the need for downloading by having a mutualised underpinning structure, i.e. the Copernicus Data and Information Access Services (DIAS) that will become operational in the second quarter of 2018, which will allow users to run their computer code on the data without the need for downloading. The hope is that this will allow users to focus on what they can do with the data, rather than worrying around storing it!

Charles Macmillan from JRC described their EO Data and Processing Platform (JEODPP) which is a front end based around the Jupyter Notebook that allows users to ask questions using visualisations and narrative text, instead of just though direct programming. He also noted that increasingly the data needed for policy and decision making is held by private organisations rather than government bodies.

The Tuesday afternoon was busy as I chaired the session on Information Generation at Scale. We had around 100 people who heard some great talks on varied subjects such as mass processing of Sentinel & Landsat data for mapping human settlements, 35 years of AVHRR data and large scale flood frequency maps using SAR data.

‘Application Of Earth Observation To A Ugandan Drought And Flood Mitigation Service’ poster

I presented a poster at the Wednesday evening session, titled “Application Of Earth Observation To A Ugandan Drought And Flood Mitigation Service”. We’re part of a consortium working on this project which is funded via the UK Space Agency’s International Partnership Programme. It’s focus is on providing underpinning infrastructure for the Ugandan government so that end users, such as farmers, can benefit from more timely and accurate information – delivered through a combination of EO, modelling and ground-based measurements.

It was interesting to hear Grega Milcinski from Sinergise discuss a similar approach to users from the lessons they learnt from building the Sentinel Hub. They separated the needs of science, business and end users. They’ve chosen not to target end users due to the challenges surrounding the localisation and customisation requirements of developing apps for end users around the world. Instead they’ve focussed on meeting the processing needs of scientific and business users to give them a solid foundation upon which they can then build end user applications. It was quite thought provoking to hear this, as we’re hoping to move towards targeting these end users in the near future!

There were some key technology themes that came of the presentations at the conference:

  • Jupyter notebooks were popular for frontend visualisation and data analytics, so users just need to know some basic python to handle large and complex datasets.
  • Making use of cloud computing using tools such as Docker and Apache Spark for running multiple instances of code with integrated parallel processing.
  • Raw data and processing on the fly: for both large datasets within browsers and by having the metadata stored so you can quickly query before committing to processing.
  • Analysis ready data in data cubes, i.e. the data has been processed to a level where remote sensing expertise isn’t so critical.

It was a great thought provoking conference. If you’d like to get more detail on what was presented then a book of extended abstracts is available here. The next event is planned for 19-21 February 2019 in Munich, Germany and I’d highly recommend it!

Inspiring the Next Generation of EO Scientists

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

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

Last week, whilst Europe’s Earth Observation (EO) community was focussed on the successful launch of Sentinel-5P, over in America Tuesday 10th October was Earth Observation Day!

This annual event is co-ordinated by AmericaView, a non-profit organisation, whose aim to advance the widespread use of remote sensing data and technology through education and outreach, workforce development, applied research, and technology transfer to the public and private sectors.

Earth Observation Day is a Science, Technology, Engineering, and Mathematics (STEM) event celebrating the Landsat mission and its forty-five year archive of imagery. Using satellite imagery provides valuable experience for children in maths and sciences, together with introducing subjects such as land cover, food production, hydrology, habitats, local climate and spatial thinking. The AmericaView website contains a wealth of EO materials available for teachers to use, from fun puzzles and games through to a variety of remote sensing tutorials. Even more impressive is that the event links schools to local scientists in remote sensing and geospatial technologies. These scientists provide support to teachers including giving talks, helping design lessons or being available to answer student’s questions.

This is a fantastic event by AmericaView, supporting by wonderful resources and remote sensing specialists. We first wrote about this three years ago, and thought the UK would benefit from something similar. We still do. The UK Space Agency recently had an opportunity for organisations interested in providing education and outreach activities to support EO, satellite launch programme or the James Webb Space Telescope. It will be interesting to see what the successful candidates come up with.

At Pixalytics we’re passionate about educating and inspiring the next generation of EO scientists. For example, we regularly support the Remote Sensing and Photogrammetry Society’s Wavelength conference for students and early career scientists; and sponsored the Best Early-Career Researcher prize at this year’s GISRUK Conference. We’re also involved with two exciting events at Plymouth’s Marine Biological Association, a Young Marine Biologists (YMB) Summit for 12-18 year olds at the end of this month and their 2018 Postgraduate conference.

Why is this important?
The space industry, and the EO sector, is continuing to grow. According to Euroconsult’s ‘Satellites to Be Built & Launched by 2026 – I know this is another of the expensive reports we highlighted recently – there will be around 3,000 satellites with a mass above 50 kg launched in the next decade – of which around half are anticipated as being used for EO or communication purposes. This almost doubles the number of satellites launched in the last ten years and doesn’t include the increasing number of nano and cubesats going up.

Alongside the number of satellites, technological developments mean that the amount of EO data available is increasing almost exponentially. For example, earlier this month World View successfully completed multi-day flight of its Stratollite™ service, which uses high-altitude balloons coupled with the ability to steer within stratospheric winds. They can carry a variety of sensors, a mega-pixel camera was on the recent flight, offering an alternative vehicle for collecting EO data.

Therefore, we need a future EO workforce who are excited, and inspired, by the possibilities and who will take this data and do fantastic things with it.

To find that workforce we need to shout about our exciting industry and make sure everyone knows about the career opportunities available.

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!

Blue Holes from Space

Andros Island in The Bahamas. Acquired by Landsat 8 in February 2017. Data courtesy of NASA.

Blue holes are deep marine caverns or sinkholes which are open at the surface, and they get their name from their apparent blue colour of their surface due to the scattering of the light within water. The often contain both seawater and freshwater, and in their depths the water is very clear which makes them very popular with divers.

The term ‘blue hole’ first appeared on sea charts from the Bahamas in 1843, although the concept of submarine caves had been described a century earlier (from Schwabe and Carew, 2006). There are a number of well-known blue holes in Belize, Egypt and Malta amongst others. The Dragon Hole in the South China Sea is believed to be the deepest blue hole with a depth of 300 metres.

The Andros Island in The Bahamas has the highest concentration of blue holes in the world, and last week we watched a television programme called River Monsters featuring this area. The presenter, Jeremy Wade, was investigating the mythical Lusca, a Caribbean sea creature which reportedly attacks swimmers and divers pulling them down to their lairs deep within of the blue holes. Jeremy fished and dived some blue holes, and spoke to people who had seen the creature. By the end he believed the myth of the Lusca was mostly likely based on a giant octopus. Whilst this was interesting, by the end of the programme we were far more interested in whether you could see blue holes from space.

The image at the top is Andros Island. Although, technically it’s an archipelago, it is considered as a single island. It’s the largest island of The Bahamas and at 2,300 square miles is the fifth largest in the Caribbean. There are a number of well known blue holes in Andros, both inland and off the coast, such as:

Blues in the Blue Hole National Park on the Andros Island in The Bahamas. Acquired by Landsat 8 in February 2017. Data courtesy of NASA.

  • Blue Holes National Park covers over 33,000 acres and includes a variety of blue holes, freshwater reservoirs and forests within its boundaries. The image to the right covers an area of the national park. In the centre, just above the green water there are five black circles  – despite the colour, these are blue holes.
  • Uncle Charlie’s Blue Hole, also called Little Frenchman Blue Hole, is just off Queen’s Highway in Nicholls Town and has a maximum depth of 127 metres.
  • Atlantis Blue Hole has a maximum depth of about 85 metres.
  • Stargate Blue Hole his blue hole is located about 500 miles inland from the east coast of South Andros on the west side of The Bluff village.
  • Guardian Blue Hole is in the ocean and is believed to have the second deepest cave in The Bahamas, with a maximum explored depth of 133 metres.

Blue hole in the south of Andros Island in The Bahamas. Acquired by Landsat 8 in February 2017. Data courtesy of NASA.

The image to the right is from the south of the island. Just off the centre, you can see a blue hole surrounded by forests and vegetation.

So we can confirm that the amazing natural features called blue holes can be seen from space, even if they don’t always appear blue!

Great Barrier Reef Coral Bleaching

Great Barrier Reef off the east coast of Australia where currents swirl in the water around corals. Image acquired by Landsat-8 on 23 August 2013. Image Courtesy of USGS/ESA.

Coral bleaching on the Great Barrier Reef in Australia was worse than expected last year, and a further decline is expected in 2017 according to the Great Barrier Reef Marine Park Authority. In a document issued this week they noted that, along with reefs across the world, the Great Barrier Reef has had widespread coral decline and habitat loss over the last two years.

We’ve written about coral bleaching before, as it’s a real barometer of climate change. To put the importance of the Great Barrier Reef into context:

  • It’s 2300 km long and covers an area of around 70 million football pitches;
  • Consists of 3000 coral reefs, which are made up from 650 different types of hard and soft coral; and
  • Is home to over 1500 types of fish and more than 100 varieties of sharks and rays.

Coral bleaching occurs when water stress causes coral to expel the photosynthetic algae, which give coral their colours, exposing the skeleton and turning them white. The stress is mostly due to higher seawater temperatures; although cold water stresses, run-off, pollution and high solar irradiance can also cause bleaching. Whilst bleaching does not kill coral immediately, it does put them at a greater risk of mortality from storms, poor water quality, disease and the crown-of-thorns starfish.

Last year the Great Barrier Reef suffered its worst bleaching on record, aerial and in-water surveys identified that 29% of shallow water coral reefs died in 2016; up from the original estimation of 22%. The most severe mortality was in an area to the north of Port Douglas where 70% of the shallow water corals died. This is hugely sad news to Sam and I, as we explored this area of the Great Barrier Reef ourselves about fifteen years ago.

Whilst hugely concerning, there is also a little hope! There was a strong recovery of coral in the south of the Great Barrier Reef, as bleaching and other impacts were less.

Images from the Copernicus Sentinel-2A satellite captured on 8 June 2016 and 23 February 2017 show coral turning bright white for Adelaide Reef, Central Great Barrier Reef. Data courtesy of Copernicus/ESA, and contains modified Copernicus Sentinel data (2016–17), processed by J. Hedley; conceptual model by C. Roelfsema

The coral bleaching event this year has also been captured by Sentinel-2. Scientists from ESA’s Sen2Coral project have used change detection techniques to determine bleaching. Images between January and April showed areas of coral turning bright white and then darkening, although it was unclear whether the darkening was due to coral recovery or dead coral being overgrown with algae. In-water surveys were undertaken, which confirmed the majority of the darkened areas were algal overgrowth.

This work has proved that coral bleaching can be seen from space, although it needs to be supported by in-situ work. ESA intends to develop a coral reef tool, which will be part of the open-source Sentinel Application Platform (SNAP) toolkit. This will enable anyone to monitor the health of coral reefs worldwide and hopefully, help protect these natural wonders.