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!

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.

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.

Sentinel To Be Launched

Sentinel-2 Image of Plymouth from 2016. Data courtesy of Copernicus/ESA.

Sentinel-2B was launched at 01:49 GMT on the 7th March from Europe’s Spaceport in French Guiana. It’s the second of a constellation of optical satellites which are part of the European Commission’s Copernicus Programme.

Its partner Sentinel-2A was launched on the 23rd June 2015, and has been providing some stunning imagery over the last eighteen months like the picture of Plymouth above. We’ve also used the data within our own work. Sentinel-2B carries an identical Multispectral Imager (MSI) instrument to its twin with 13 spectral bands:

  • 4 visible and near infrared spectral bands with a spatial resolution of 10 m
  • 6 short wave infrared spectral bands with a spatial resolution of 20 m
  • 3 atmospheric correction bands with a spatial resolution of 60 m

With a swath width of 290 km the constellation will acquire data in a band of latitude extending from 56° South around Isla Hornos, Cape Horn, South America to 83° North above Greenland, together with observations over specific calibration sites, such as Dome-C in Antarctica. Its focus will be on continental land surfaces, all European islands, islands bigger than 100 square kilometres, land locked seas and coastal waters.

The satellites will orbit 180 degrees apart at an altitude of 786 km, which means that together they will revisit the same point on Earth every five days at the equator, and it may be faster for parts of southern Europe. In comparison, Landsat takes sixteen days to revisit the same point.

With all Copernicus data being made freely available to anyone, the short revisit time offers opportunities small and micro Earth Observation businesses to establish monitoring products and services without the need for significant investment in satellite data paving the way for innovative new solutions to the way in which certain aspects of the environment are managed. Clearly, five day revisits are not ‘real-time’ and the spatial resolution of Sentinel data won’t be suitable for every problem.There is joint work between the US and Europe, to have complementarity with Landsat-8, which has thermal bands, and allows a further opportunity for cloud-free data acquisitions. Also, commercial operators provide higher spatial resolution data.

At Pixalytics we’re supporters of open source in both software and imagery. Our first point of call with any client is to ask whether the solution can be delivered through free to access imagery, as this can make a significant cost saving and allow large archives to be accessed. Of course, for a variety of reasons, it becomes necessary to purchase imagery to ensure the client gets the best solution for their needs. Of course, applications often include a combination of free to access and paid for data.

Next’s week launch offers new opportunities for downstream developers and we’ll be interested to see how we can exploit this new resource to develop our products and services.

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.

Earth Observation Looking Good in 2017!

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

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

2017 is looking like an exciting one for Earth Observation (EO), judging by the number of significant satellites planned for launch this year.

We thought it would be interesting to give an overview of some of the key EO launches we’ve got to look forward to in the next twelve months.

The European Space Agency (ESA) has planned launches of:

  • Sentinel-2B in March, Sentinel-5p in June and Sentinel-3B in August – all of which we discussed last week.
  • ADM-Aeolus satellite is intended to be launched by the end of the year carrying an Atmospheric Laser Doppler Instrument. This is essentially a lidar instrument which will provide global measurements of wind profiles from ground up to the stratosphere with 0.5 to 2 km vertical resolution.

From the US, both NASA and NOAA have important satellite launches:

  • NASA’s Ionospheric Connection Explorer (ICON) Mission is planned for June, and will provide observations of Earth’s ionosphere and thermosphere; exploring the boundary between Earth and space.
  • NASA’s ICESat-2 in November that will measure ice sheet elevation, ice sheet thickness changes and the Earth’s vegetation biomass.
  • In June NOAA will be launching the first of its Joint Polar Satellite System (JPSS) missions, a series of next-generation polar-orbiting weather observatories.
  • Gravity Recovery And Climate Experiment – Follow-On (GRACE_FO) are a pair of twin satellites to extend measurements from the GRACE satellite, maintaining data continuity. These satellites use microwaves to measure the changes in the Earth’s gravity fields to help map changes in the oceans, ice sheets and land masses. It is planned for launch right at the end of 2017, and is a partnership between NASA and the German Research Centre for Geosciences.

Some of the other launches planned include:

  • Kanopus-V-IK is a small Russian remote sensing satellite with an infrared capability to be used for forest fire detection. It has a 5 m by 5 m spatial resolution over a 2000 km swath, and is planned to be launched next month.
  • Vegetation and Environment monitoring on a New MicroSatellite (VENµS), which is partnership between France and Israel has a planned launch of August. As its name suggests it will be monitoring ecosytems, global carbon cycles, land use and land change.
  • KhalifaSat is the third EO satellite of United Arab Emirates Institution for Advanced Science and Technology (EIAST). It is an optical satellite with a spatial resolution of 0.75 m for the visible and near infrared bands.

Finally, one of the most intriguing launches involves three satellites that form the next part of India’s CartoSat mission. These satellites will carry both high resolution multi- spectral imagers and a panchromatic camera, and the mission’s focus is cartography. It’s not these three satellites that make this launch intriguing, it is the one hundred other satellites that will accompany them!

The Indian Space Research Organisation’s Polar Satellite Launch Vehicle, PSLV-C37, will aim to launch a record 103 satellites in one go. Given that the current record for satellites launched in one go is 37, and that over the last few years we’ve only had around two hundred and twenty satellites launched in an entire year; this will be a hugely significant achievement.

So there you go. Not a fully comprehensive list, as I know there will be others, but hopefully it gives you a flavour of what to expect.

It certainly shows that the EO is not slowing down, and the amount of data available is continuing to grow. This of course gives everyone working in the industry more challenges in terms of storage and processing power – but they are good problems to have. Exciting year ahead!

High Noon for ESA Funding

Sentinel-2 Image of Plymouth from 2016. Data courtesy of Copernicus/ESA.

Sentinel-2 Image of Plymouth from 2016. Data courtesy of Copernicus/ESA.

The future direction of the space industry in Europe is set to be debated at the European Space Agency (ESA) Ministerial Council taking place at the start of December. It will look at the Space Strategy for Europe which we reviewed last week, and crucially will set ESA’s budget for the few next years.

The Council is the governing body of ESA and each of the 22 member states is represented, plus Canada. The Council is chaired by ESA’s Director General Jan Woerner, and he gave a press briefing in Paris earlier this week in advance of the meeting.

Sadly, I was unable to go to France for the meeting; but luckily Peter B de Selding from Space News was there and produced an excellent article which highlighted the key points including:

  • ESA is seeking an €11 billion settlement
  • Concern over the Norway’s proposed 75% contribution reduction
  • The ExoMars Programme, which hit the headlines earlier this year when the Schiaparelli lander crashed on its descend to the Mars surface, has a funding gap of €400 million.
  • €800 million is being sought to continue the collaboration with NASA on the International Space Station until 2024

The headline message on money is clearly the requested €11 billion settlement. In 2016 the ESA budget was €5.25 billion, of which almost 30% was income from the European Union (EU), Eumetsat and other programmes. The remaining 70% came from the contributions of each member state and Canada, and it is these future contributions that will be discussed at the Ministerial. This year the biggest contributor was Germany (€872.6 m), followed by France (€844.5 m) and Italy (€512 m) – between them these three accounted for almost 60% of the ESA member state budget.

For us, Pixalytics and the UK, there were a couple of interesting points. Firstly, ESA’s Earth Observation Envelope Programmes (EOEP-5) has had a 12.5% funding cut reducing their budget down to €1.4 bn for the period 2017 – 2025. It’s not currently clear what impact this reduction will, or will not, have on existing and planned activities.

Secondly, and for the second week running the blog has had to mention the B word. We’ve previously written about the fact that ESA and the EU are different organisations, and that Brexit does not directly impact our involvement with ESA – a point reinforced by the Director General at the briefing.

Indirectly though, Brexit impacts, if not dominates, the political and financial landscape of the country and as such will have affected the discussions surrounding our ESA contribution commitment. For example:

  • Dropping Value Of Sterling: The pound has dropped by over 13% since the EU Referendum, significantly increasing the cost to the UK of our ESA contribution which was €13.2 m in 2016.
  • Budget Pressures: In addition to the drop in the pound, the UK Space Agency has to compete with every other Government Department for funding. Given the current austerity financial approach, coupled with the additional costs of dealing with Brexit, money is tight.
  • Space Industry Profile: Every industry is currently fighting to get their agenda’s onto Government Minister’s desk to ensure they get then ‘best deal from Brexit’. Space is no different. We may not have the London centre of the financial sector or the emotional impact of the farmers and fisherman, but we are a strong and important part of the economy.

We need Ministers to understand our industry, and to ensure that they support us as much as possible. This means, as we said last week, that we need to give a positive commitment to our ongoing involvement with ESA and a strong financial contribution at the Ministerial in Lucerne on the 1st and 2nd of December.

We await the outcome with interest!

Remote Sensing: Learning, Learned & Rewritten

Image of Yemen acquired by Sentinel-2 in August 2015. Data courtesy of ESA.

Image of Yemen acquired by Sentinel-2 in August 2015. Data courtesy of ESA.

This blog post is about what I did and what thoughts came to mind on my three-month long ERASMUS+ internship at Pixalytics which began in July and ends this week.

During my first week at Pixalytics, after being introduced to the Plymouth Science Park buildings and the office, my first task was to get a basic understanding of what remote sensing is actually about. With the help of Sam and Andy’s book, Practical Handbook of Remote Sensing, that was pretty straightforward.

As the words suggest, remote sensing is the acquisition of data and information on an object without the need of being on the site. It is then possible to perform a variety of analysis and processing on this data to better understand and study physical, chemical and biological phenomena that affect the environment.

Examples of programming languages: C, Python & IDL

Examples of programming languages: C, Python & IDL

I soon realized that quite a lot of programming was involved in the analysis of satellite data. In my point of view, though, some of the scripts, written in IDL (Interactive Data Language), were not as fast and efficient as they could be, sometimes not at all. With that in mind, I decided to rewrite one of the scripts, turning it into a C program. This allowed me to get a deeper understanding of satellite datasets formats (e.g. HDF, Hierarchical Data Format) and improve my overall knowledge of remote sensing.

While IDL, a historic highly scientific language for remote sensing, provides a quick way of writing code, it has a number of glaring downsides. Poor memory management and complete lack of strictness often lead to scripts that will easily break. Also, it’s quite easy to write not-so-pretty and confusing spaghetti code, i.e., twisted and tangled code.

Writing C code, on the other hand, can get overly complicated and tedious for some tasks that would require just a few lines in IDL. While it gives the programmer almost full control of what’s going on, some times it’s just not worth the time and effort.

Instead, I chose to rewrite the scripts in Python which I found to be quite a good compromise. Indentation can sometimes be a bit annoying, and coming from other languages the syntax might seem unusual, but its great community and the large availability of modules to achieve your goals in just a few lines really make up for it.

It was soon time to switch to a bigger and more complex task, which has been, to this day, what I would call my “main task” during my time at Pixalytics: building an automated online processing website. The website aspect was relatively easy with a combination of the usual HTML, Javascript, PHP and CSS, it was rewriting and integrated the remote sensing scripts that was difficult. Finally all of those little, and sometimes not quite so little, scripts and programs were available from a convenient web interface, bringing much satisfaction and pride for all those hours of heavy thinking and brainstorming. Hopefully, you will read more about this development in the future from Pixalytics, as it will form the back-end of their product suite to be launched in the near future.

During my internship there was also time for events inside the Science Park such as the Hog Roast, and events outside as well when I participated at the South-West England QGIS User Group meeting in Dartmoor National Park. While it is not exactly about remote sensing, but more on the Geographic Information System (GIS) topic it made me realize how much I had learned on remote sensing in my short time at Pixalytics, I was able to exchange my opinions and points of view with other people that were keen on the subject.

A side project I’ve been working on in my final weeks was looking at the world to find stunning, interesting (and possibly both) places on Earth to make postcards from – such as one at the top of the blog. At times, programming and scientific research reads can get challenging and/or frustrating, and it’s so relaxing to just look at and enjoy the beauty of our planet.

It is something that anyone can do as it takes little knowledge about remote sensing. Free satellite imagery is available through a variety of sources; what I found to be quite easy to access and use was imagery from USGS/NASA Landsat-8 and ESA Sentinel-2. It is definitely something I would recommend.

Finally, I want to say “thank you” to Sam and Andy, without whom I would have never had the opportunity to get the most out of this experience, in a field in which I’ve always been interested into, but had never had the chance to actually get my hands on.

Blog written by Davide Mainas on an ERASMUS+ internship with Pixalytics via the Tellus Group.

Differences Between Optical & Radar Satellite Data

Ankgor Wat, Cambodia. Sentinel-2A image courtesy of ESA.

Ankgor Wat, Cambodia. Sentinel-2A image courtesy of ESA.

The two main types of satellite data are optical and radar used in remote sensing. We’re going to take a closer look at each type using the Ankgor Wat site in Cambodia, which was the location of the competition we ran on last week’s blog as part of World Space Week. We had lots of entries, and thanks to everyone who took part!

Constructed in the 12th Century, Ankgor Wat is a temple complex and the largest religious monument in the world. It lies 5.5 kilometres north of the modern town of Siem Reap and is popular with the remote sensing community due to its distinctive features. The site is surrounded by a 190m-wide moat, forming a 1.5km by 1.3km border around the temples and forested areas.

Optical Image
The picture at the top, which was used for the competition, is an optical image taken by a Multi-Spectral Imager (MSI) carried aboard ESA’s Sentinel-2A satellite. Optical data includes the visible wavebands and therefore can produce images, like this one, which is similar to how the human eye sees the world.

The green square in the centre of the image is the moat surrounding the temple complex; on the east side is Ta Kou Entrance, and the west side is the sandstone causeway which leads to the Angkor Wat gateway. The temples can be clearly seen in the centre of the moat, together with some of the paths through the forest within the complex.

To the south-east are the outskirts of Siem Reap, and the square moat of Angkor Thom can be seen just above the site. To the right are large forested areas and to the left are a variety of fields.
In addition to the three visible bands at 10 m resolution, Sentinel-2A also has:

  • A near-infrared band at 10 m resolution,
  • Six shortwave-infrared bands at 20 m resolution, and
  • Three atmospheric correction bands at 60 m resolution.

Radar Image
As a comparison we’ve produced this image from the twin Sentinel-1 satellites using the C-Band Synthetic Aperture Radar (SAR) instrument they carry aboard. This has a spatial resolution of 20 m, and so we’ve not zoomed as much as with the optical data; in addition, radar data is noisy which can be distracting.

Angkor Wat, Cambodia. SAR image from Sentinel-1 courtesy of ESA.

Angkor Wat, Cambodia. SAR image from Sentinel-1 courtesy of ESA.

The biggest advantage of radar data over optical data is that it is not affected by weather conditions and can see through clouds, and to some degree vegetation. This coloured Sentinel-1 SAR image is produced by showing the two polarisations (VV and VH i.e. vertical polarisation send for the radar signal and vertical or horizontal receive) alongside a ratio of them as red, green and blue.

Angkor Wat is shown just below centre, with its wide moat, and other archaeological structures surrounding it to the west, north and east. The variety of different landscape features around Angkor Wat show up more clearly in this image. The light pink to the south is the Cambodian city of Siem Reap with roads appearing as lines and an airport visible below the West Baray reservoir, which also dates from the Khmer civilization. The flatter ground that includes fields are purple, and the land with significant tree cover is shown as pale green.

Conclusion
The different types of satellite data have different uses, and different drawbacks. Optical imagery is great if you want to see the world as the human eye does, but radar imagery offers better options when the site can be cloudy and where you want an emphasis on the roughness of the surfaces.