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.

Flip-Sides of Soil Moisture

Soil Moisture changes between 19th and 25th August around Houston, Texas due to rainfall from Hurricane Harvey. Courtesy of NASA Earth Observatory image by Joshua Stevens, using soil moisture data courtesy of JPL and the SMAP science team.

Soil moisture is an interesting measurement as it can be used to monitor two diametrically opposed conditions, namely floods and droughts. This was highlighted last week by maps produced from satellite data for the USA and Italy respectively. These caught our attention because soil moisture gets discussed on a daily basis in the office, due to its involvement in a project we’re working on in Uganda.

Soil moisture can have a variety of meanings depending on the context. For this blog we’re using soil moisture to describe the amount of water held in spaces between the soil in the top few centimetres of the ground. Data is collected by radar satellites which measure microwaves reflected or emitted by the Earth’s surface. The intensity of the signal depends on the amount of water in the soil, enabling a soil moisture content to be calculated.

You can’t have failed to notice the devastating floods that have occurred recently in South Asia – particularly India, Nepal and Bangladesh – and in the USA. The South Asia floods were caused by monsoon rains, whilst the floods in Texas emanated from Hurricane Harvey.

Soil moisture measurements can be used to show the change in soil saturation. NASA Earth Observatory produced the map at the top of the blogs shows the change in soil moisture between the 19th and 25th August around Houston, Texas. The data is based on measurements acquired by the Soil Moisture Active Passive (SMAP) satellite, which uses a radiometer to measure soil moisture in the top 5 centimetres of the ground with a spatial resolution of around 9 km. On the map itself the size of each of the hexagons shows how much the level of soil moisture changed and the colour represents how saturated the soil is.

These readings have identified that soil moisture levels got as high as 60% in the immediate aftermath of the rainfall, partly due to the ferocity of the rain, which prevented the water from seeping down into the soil and so it instead remained at the surface.

Soil moisture in Italy during early August 2017. The data were compiled by ESA’s Soil Moisture CCI project. Data couresy of ESA. Copyright: C3S/ECMWF/TU Wien/VanderSat/EODC/AWST/Soil Moisture CCI

By contrast, Italy has been suffering a summer of drought and hot days. This year parts of the country have not seen rain for months and the temperature has regularly topped one hundred degrees Fahrenheit – Rome, which has seventy percent less rainfall than normal, is planning to reduce water pressure at night for conservation efforts.

This has obviously caused an impact on the ground, and again a soil moisture map has been produced which demonstrates this. This time the data was come from the ESA’s Soil Moisture Climate Change Initiative project using soil moisture data from a variety of satellite instruments. The dataset was developed by the Vienna University of Technology with the Dutch company VanderSat B.V.

The map shows the soil moisture levels in Italy from the early part of last month, with the more red the areas, the lower the soil moisture content.

Soil moisture is a fascinating measurement that can provide insights into ground conditions whether the rain is falling a little or a lot.

It plays an important role in the development of weather patterns and the production of precipitation, and is crucial to understanding both the water and carbon cycles that impact our weather and climate.

Optical Imagery is Eclipsed!

Solar eclipse across the USA captured by Suomi NPP VIIRS satellite on 21st August. Image courtesy of NASA/ NASA’s Earth Observatory.

Last week’s eclipse gave an excellent demonstration of the sun’s role in optical remote sensing. The image to the left was acquired on the 21st August by the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the NOAA/NASA Suomi NPP satellite, and the moon’s shadow can be clearly seen in the centre of the image.

Optical remote sensing images are the type most familiar to people as they use the visible spectrum and essentially show the world in a similar way to how the human eye sees it. The system works by a sensor aboard the satellite detecting sunlight reflected off the land or water – this process of light being scattered back towards the sensor by an object is known as reflectance.

Optical instruments collect data across a variety of spectral wavebands including those beyond human vision. However, the most common form of optical image is what is known as a pseudo true-colour composite which combines the red, green and blue wavelengths to produce an image which effectively matches human vision; i.e., in these images vegetation tends to be green, water blue and buildings grey. These are also referred to as RGB images.

These images are often enhanced by adjustments to the colour pallets of each of the individual wavelengths that allow the colours to stand out more, so the vegetation is greener and the ocean bluer than in the original data captured by the satellite. The VIIRS image above is an enhanced pseudo true-colour composite and the difference between the land and the ocean is clearly visible as are the white clouds.

As we noted above, optical remote sensing works by taking the sunlight reflected from the land and water. Therefore during the eclipse the moon’s shadow means no sunlight reaches the Earth beneath, causing the circle of no reflectance (black) in the centre of the USA. This is also the reason why no optical imagery is produced at night.

This also explains why the nemesis of optical imagery is clouds! In cloudy conditions, the sunlight is reflected back to the sensor by the clouds and does not reach the land or water. In this case the satellite images simply show swirls of white!

Mosaic composite image of solar eclipse over the USA on the 21st August 2017 acquired by MODIS. .Image courtesy of NASA Earth Observatory images by Joshua Stevens and Jesse Allen, using MODIS data from the Land Atmosphere Near real-time Capability for EOS (LANCE) and EOSDIS/Rapid Response

A second eclipse image was produced from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite. Shown on the left this is a mosaic image from the 21st August, where:

  • The right third of the image shows the eastern United States at about 12:10 p.m. Eastern Time, before the eclipse had begun.
  • The middle part was captured at about 12:50 p.m. Central Time during the eclipse.
  • The left third of the image was collected at about 12:30 p.m. Pacific Time, after the eclipse had ended.

Again, the moon’s shadow is obvious from the black area on the image.

Hopefully, this gives you a bit of an insight into how optical imagery works and why you can’t get optical images at night, under cloudy conditions or during an eclipse!

Silver Anniversary for Ocean Altimetry Space Mission

Artist rendering of Jason-3 satellite over the Amazon.
Image Courtesy NASA/JPL-Caltech.

August 10th 1992 marked the launch of the TOPEX/Poseidon satellite, the first major oceanographic focussed mission. Twenty five years, and three successor satellites, later the dataset begun by TOPEX/Poseidon is going strong providing sea surface height measurements.

TOPEX/Poseidon was a joint mission between NASA and France’s CNES space agency, with the aim of mapping ocean surface topography to improve our understanding of ocean currents and global climate forecasting. It measured ninety five percent of the world’s ice free oceans within each ten day revisit cycle. The satellite carried two instruments: a single-frequency Ku-band solid-state altimeter and a dual-frequency C- and Ku-band altimeter sending out pulses at 13.6 GHz and 5.3 GHz respectively. The two bands were selected due to atmospheric sensitivity, as the difference between them provides estimates of the ionospheric delay caused by the charged particles in the upper atmosphere that can delay the returned signal. The altimeter sends radio pulses towards the earth and measures the characteristics of the returned echo.

When TOPEX/Poseidon altimetry data is combined with other information from the satellite, it was able to calculate sea surface heights to an accuracy of 4.2 cm. In addition, the strength and shape of the return signal also allow the determination of wave height and wind speed. Despite TOPEX/Poseidon being planned as a three year mission, it was actually active for thirteen years, until January 2006.

The value in the sea level height measurements resulted in a succeeding mission, Jason-1, launched on December 7th 2001. It was put into a co-ordinated orbit with TOPEX/Poseidon and they both took measurements for three years, which allowed both increased data frequency and the opportunity for cross calibration of the instruments. Jason-1 carried a CNES Poseidon-2 Altimeter using the same C- and Ku-bands, and following the same methodology it had the ability to measure sea-surface height to an improved accuracy of 3.3 cm. It made observations for 12 years, and was also overlapped by its successor Jason-2.

Jason-2 was launched on the 20 June 2008. This satellite carried a CNES Poseidon-3 Altimeter with C- and Ku-bands with the intention of measuring sea height to within 2.5cm. With Jason-2, National Oceanic and Atmospheric Administration (NOAA) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) took over the management of the data. The satellite is still active, however due to suspected radiation damage its orbit was lowered by 27 km, enabling it to produce an improved, high-resolution estimate of Earth’s average sea surface height, which in turn will help improve the quality of maps of the ocean floor.

Following the established pattern, Jason-3 was launched on the 17th January 2016. It’s carrying a Poseidon-3B radar altimeter, again using the same C and Ku bands and on a ten day revisit cycle.

Together these missions have provided a 25 year dataset on sea surface height, which has been used for applications such as:

  • El Niño and La Niña forecasting
  • Extreme weather forecasting for hurricanes, floods and droughts
  • Ocean circulation modelling for seasons and how this affects climate through by moving heat around the globe
  • Tidal forecasting and showing how this energy plays an important role in mixing water within the oceans
  • Measurement of inland water levels – at Pixalytics we have a product that we have used to measure river levels in the Congo and is part of the work we are doing on our International Partnership Programme work in Uganda.

In the future, the dataset will be taken forward by the Jason Continuity of Service (Jason-CS) on the Sentinel-6 ocean mission which is expected to be launched in 2020.

Overall, altimetry data from this series of missions is a fantastic resource for operational oceanography and inland water applications, and we look forward to its next twenty five years!

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.

Locusts & Monkeys

Soil moisture data from the SMOS satellite and the MODIS instrument acquired between July and October 2016 were used by isardSAT and CIRAD to create this map showing areas with favourable locust swarming conditions (in red) during the November 2016 outbreak. Data courtesy of ESA. Copyright : CIRAD, SMELLS consortium.

Spatial resolution is a key characteristic in remote sensing, as we’ve previously discussed. Often the view is that you need an object to be significantly larger than the resolution to be able to see it on an image. However, this is not always the case as often satellites can identify indicators of objects that are much smaller.

We’ve previously written about satellites identifying phytoplankton in algal blooms, and recently two interesting reports have described how satellites are being used to determine the presence of locusts and monkeys!


Desert locusts are a type of grasshopper, and whilst individually they are harmless as a swarm they can cause huge damage to populations in their paths. Between 2003 and 2005 a swarm in West Africa affected eight million people, with reported losses of 100% for cereals, 90% for legumes and 85% for pasture.

Swarms occur when certain conditions are present; namely a drought, followed by rain and vegetation growth. ESA and the UN Food and Agriculture Organization (FAO) have being working together to determine if data from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to forecast these conditions. SMOS carries a Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) instrument – a 2D interferometric L-band radiometer with 69 antenna receivers distributed on a Y-shaped deployable antenna array. It observes the ‘brightness temperature’ of the Earth, which indicates the radiation emitted from planet’s surface. It has a temporal resolution of three days and a spatial resolution of around 50 km.

By combining the SMOS soil moisture observations with data from NASA’s MODIS instrument, the team were able to downscale SMOS to 1km spatial resolution and then use this data to create maps. This approach then predicted favourable locust swarming conditions approximately 70 days ahead of the November 2016 outbreak in Mauritania, giving the potential for an early warning system.

This is interesting for us as we’re currently using soil moisture data in a project to provide an early warning system for droughts and floods.


Earlier this month the paper, ‘Connecting Earth Observation to High-Throughput Biodiversity Data’, was published in the journal Nature Ecology and Evolution. It describes the work of scientists from the Universities of Leicester and East Anglia who have used satellite data to help identify monkey populations that have declined through hunting.

The team have used a variety of technologies and techniques to pull together indicators of monkey distribution, including:

  • Earth observation data to map roads and human settlements.
  • Automated recordings of animal sounds to determine what species are in the area.
  • Mosquitos have been caught and analysed to determine what they have been feeding on.

Combining these various datasets provides a huge amount of information, and can be used to identify areas where monkey populations are vulnerable.

These projects demonstrate an interesting capability of satellites, which is not always recognised and understood. By using satellites to monitor certain aspects of the planet, the data can be used to infer things happening on a much smaller scale than individual pixels.

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!

Monitoring Fires From Space

Monitoring fires from space has significant advantages when compared to on-ground activity. Not only are wider areas easier to monitor, but there are obvious safety benefits too. The different ways this can be done have been highlighted through a number of reports over the last few weeks.

VIIRS Image from 25 April 2017, of the Yucatán Peninsula showing where thermal bands have picked-up increased temperatures. Data Courtesy of NASA, NASA image by Jeff Schmaltz, LANCE/EOSDIS Rapid Response.

Firstly, NASA have released images from different instruments, on different satellites, that illustrate two ways of how satellites can monitor fires.

Acquired on the 25 April 2017, an image from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite showed widespread fire activity across the Yucatán Peninsula in South America. The image to the right is a natural colour image and each of the red dots represents a point where the instrument’s thermal band detected temperatures higher than normal.

False colour image of the West Mims fire on Florida/Georgia boundary acquired by MODIS on 02 May 2017. Data courtesy of NASA. NASA image by Jeff Schmaltz, LANCE/EOSDIS Rapid Response.

Compare this to a wildfire on Florida-Georgia border acquired from NASA’s Aqua satellite on the 02 May 2017 using the Moderate Resolution Imaging Spectroradiometer (MODIS). On the natural colour image the fires could only be seen as smoke plumes, but on the left is the false colour image which combines infrared, near-infrared and green wavelengths. The burnt areas can be clearly seen in brown, whilst the fire itself is shown as orange.

This week it was reported that the Punjab Remote Sensing Centre in India, has been combining remote sensing, geographical information systems and Global Positioning System (GPS) data to identify the burning of crop stubble in fields; it appears that the MODIS fire products are part of contributing the satellite data. During April, 788 illegal field fires were identified through this technique and with the GPS data the authorities have been able to identify, and fine, 226 farmers for undertaking this practice.

Imaged by Sentinel-2, burnt areas, shown in shades of red and purple, in the Marantaceae forests in the north of the Republic of Congo.
Data courtesy of Copernicus/ESA. Contains modified Copernicus Sentinel data (2016), processed by ESA.

Finally, a report at the end of April from the European Space Agency described how images from Sentinel-1 and Senintel-2 have been combined to assess the amount of forest that was burnt last year in the Republic of Congo in Africa – the majority of which was in Marantaceae forests. As this area has frequent cloud cover, the optical images from Sentinel-2 were combined with the Synthetic Aperture Radar (SAR) images from Sentinel-1 that are unaffected by the weather to offer an enhanced solution.

Sentinel-1 and Sentinel-2 data detect and monitor forest fires at a finer temporal and spatial resolution than previously possible, namely 10 days and 10 m, although the temporal resolution will increase to 5 days later this year when Sentinel-2B becomes fully operational.  Through this work, it was estimated that 36 000 hectares of forest were burnt in 2016.

Given the danger presented by forest fires and wildfires, greater monitoring from space should improve fire identification and emergency responses which should potentially help save lives. This is another example of the societal benefit of satellite remote sensing.

Supporting Chimpanzee Conservation from Space

Gombe National Park, Tanzania. Acquired by Sentinel-2 in December 2016. Image courtesy of ESA.

Being able to visualise the changing face of the planet over time is one of the greatest strengths of satellite remote sensing. Our previous blog showed how Dubai’s coastline has evolved over a decade, and last week NASA described interesting work they’re doing on monitoring habitat loss for chimpanzees in conjunction with the Jane Goodall Institute.

Jane Goodall has spent over fifty years working to protect and conserve chimpanzees from the Gombe National Park in Tanzania, and formed the Jane Goodall Institute in 1977. The Institute works with local communities to provide sustainable conservation programmes.

A hundred years ago more than one million chimpanzees lived in Africa, today the World Wildlife Fund estimate the population may only be around 150,000 to 250,000. The decline is stark. For example, the Ivory Coast populations have declined by 90% within the last twenty years.

One of the key factors contributing to this decline is habitat loss, mostly through deforestation; although other factors such as hunting, disease and illegal capture also contributed.

Forests cover around 31% of the planet, and deforestation occurs when trees are removed and the land has another use instead of being a forest. In chimpanzee habitats, the deforestation is mostly due to logging, mining and drilling for oil. This change in land use can be monitored from space using remote sensing. Satellites produce regular images which can be used to monitor changes in the natural environment, in turn giving valuable information to conservation charities and other organisations.

In 2000 Lilian Pintea, from the Jane Goodall Institute, was shown Landsat images comparing the area around the Gombe National Park in 1972 and 1999. The latter image showed huge deforestation outside the park’s boundary. The Institute have continued to use Landsat imagery to monitor what is happening around the National Park. In 2009 they began a citizen science project with local communities giving them smartphones to report their observations. Combining these with ongoing satellite data from NASA has helped develop and implement local plans for land use and protection of the forests. Further visualisation of this work can be found here. The image at the top was acquired Sentinel-2 in December 2016 and shows the Gombe National Park, although it is under a little haze.

The satellite data supplied by NASA comes from the Landsat missions, which currently have an archive of almost forty-five years of satellite data, which is freely available to anyone. We also used Landsat for data in our Dubai animation last week. Landsat captures optical data, which means it operates in a similar manner to the human eye – although the instruments also have infrared capabilities. However, one drawback of optical instruments is that they cannot see through clouds. Therefore, whilst Landsat is great for monitoring land use when there are clear skies, it can be combined with synthetic aperture radar (SAR), from the microwave spectrum, as it can see through both clouds and smoke. This combination enables land use and land change to monitored anywhere in the world. Using the freely available Landsat and Sentinel-1 SAR data you could monitor what is happening to the forests in your neighbourhoods.

Satellite data is powerful tool for monitoring changes in the environment, and with the archive of data available offers a unique opportunity to see what has happened over the last four decades.