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.

Remote Sensing Goes Cold

Average thickness of Arctic sea ice in spring as measured by CryoSat between 2010 and 2015. Image courtesy of ESA/CPOM

Remote sensing over the Polar Regions has poked its head above the ice recently.

On the 8th February The Cryosphere, a journal of the European Geosciences Union, published a paper by Smith et al titled ’Connected sub glacial lake drainage beneath Thwaites Glacier, West Antarctica’. It described how researchers used data from ESA’s CryoSat-2 satellite to look at lakes beneath a glacier.

This work is interesting from a remote sensing viewpoint as it is a repurposing of Cryosat-2’s mission. It’s main purpose is to measure the thickness of the ice sheets and marine ice cover using its Synthetic Aperture Radar (SAR)/Interferometric Radar Altimeter, known as SIRAL, and it can detect millimetre changes in the elevation of both ice-sheets and sea-ice.

The team were able to use this data to determine that the ice of the glacier had subsided by several metres as water had drained away from four lakes underneath. Whilst the whole process took place between June 2012 and January 2014, the majority of the drainage happened in a six month period. During this time it’s estimated that peak drainage was around 240 cubic metre per second, which is four times faster than the outflow of the River Thames into the North Sea.

We’ve previously highlighted that repurposing data – using data for more purposes than originally intended – is going to be one of the key future innovation trends for Earth Observation.

Last week, ESA also described how Sentinel-1 and Sentinel-2 data have been used over the last five months to monitor a crack in the ice near to the Halley VI research base of the British Antarctic Survey (BAS). The crack, known as Halloween Crack, is located on the Brunt ice Shelf in the Wedell Sea sector of Antarctica and was identified last October. The crack grew around 600 m per day during November and December, although it has since slowed to only one third of that daily growth.

Since last November Sentinel-2 has been acquiring optical images at each overflight, and this has been combined with SAR data from the two Sentinel-1 satellites. This SAR data will be critical during the Antarctic winter when there are only a few hours of daylight and a couple of weeks around mid-June when the sun does not rise.

This work hit the headlines as BAS decided to evacuate their base for the winter, due to the potential threat. The Halley VI base, which was only 17km from the crack, is the first Antarctic research station to be specifically designed to allow relocation to cope with this sort of movement in the ice shelf. It was already planned to move the base 23 km further inland, and this was successfully completed on the 2nd February. Further movement will depend on how the Halloween Crack develops over the winter.

Finally, the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project was announced this week at the annual meeting of the American Association for the Advancement of Science. Professor Markus Rex outlined the project, which will sail a research vessel into the Arctic sea ice and let it get stuck so it can drift across the North Pole. The vessel will be filled with a variety of remote sensing in-situ instruments, and will aim to collect data on how the climate is changing in this part of the world through measuring the atmosphere-ice-ocean system.

These projects show that the Polar Regions have a lot of interest, and variety, for 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.

Ten Top Tips Learnt Working for a Small Remote Sensing Company

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

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

I am approaching the end of my year at Pixalytics, and this blog is summary of what I’ve learnt from working for a small commercial remote sensing company.

The work itself has been a real blessing for me. Remote sensing product development was just the role I had been looking for, so I took it on with relish. During the year I have spent time researching, and supporting the product development of, flood mapping using SAR imagery, vegetation time series and light pollution.

I’ve learnt a huge amount over the past twelve months, and here are my top ten tips on researching & developing remote sensing products:

  1. Keep in mind who your stakeholders are and exactly what they require.
  2. Ensure your ground site is really covered by the satellite image, as coverage tends to be diagonal rather than straightforward latitude and longitude square and can miss a site altogether.
  3. Practise program version control at all times!
  4. Check the images you are using are the best ones for your requirements, i.e., not 16 day composites when daily images are more suitable and available; stopping you wasting a day downloading the wrong images!
  5. Write down problem solving routines, so next time you can do it for yourself!
  6. It’s always important to run pilots and streamline programming. This will save time and effort, and help verify that your end product is statistically robust.
  7. Write down what you find and keep good records of your algorithms and programming, so that you don’t duplicate work.
  8. Write technical notes on your work, so that programs can be easily shared, reviewed and run by others.
  9. Allow sufficient time before deadlines for reviewing and reworking.
  10. Make notes on the data you are using as you go along, including source, dates, locations and any company/organisation credits needed.

These are all lessons I’ll be taking with me when I leave, whether in commerce or academia.

It’s also been an insight into how a business is run, via these activities and hearing (one side!) of Sam’s teleconferences. Plus I’ve been involved in valuable encounters with the Environment Agency on products and have attended conferences, and given a presentation at one, on behalf of Pixalytics.

Plymouth has also been fun to explore. I’ve enjoyed visiting the various arts venues all over the city together with the galleries and museums, festivals and excellent cuisine.

Many thanks to Sam and Andy at Pixalytics for giving me this opportunity. I’m sad to leave and have enjoyed my time here.

Blog written by Dr Louisa Reynolds.

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.

Gliding Across The Ice

ESA’s Earth Explorer CryoSat. Image courtesy of ESA/AOES Medialab.

ESA’s Earth Explorer CryoSat. Image courtesy of ESA/AOES Medialab.

There’s been a flurry of reports in the last couple of weeks, reporting melting ice and retreating glaciers in Greenland and the Himalayas respectively.

A paper by McMillan et al (2016), titled ‘A high-resolution record of Greenland mass balance’ and published in Geophysical Research Letters earlier this month, highlighted that Greenland’s melting ice has contributed twice as much to sea level rise than in the previous twenty years. The research used CryoSat-2 radar altimetry between 1 January 2011 and 31 December 2014 to measure elevation changes in the Greenland ice.

The main instrument on ESA’s CryoSat-2 satellite is a Synthetic Aperture Radar (SAR)/Interferometric Radar Altimeter known as SIRAL, although also carries a second version of this instrument as a back-up. The SIRAL instrument has been enhanced to detect millimetre changes in the elevation of both ice-sheets and sea-ice. It sends out bursts of radar pulses, with an interval of 50 μs between them, covering a 250 m wide strip of the Earth and measures the time of the return signal to determine the height of the satellite above the Earth. It requires a very accurate measurement of its position to calculate this, and so it also carries a Doppler Orbit and Radio Positioning Integration by Satellite (DORIS) instrument to determine its orbit.

The research team discovered that the Greenland Ice Sheet lost an average of 269 ± 51 Gt/yr of snow and ice during the investigative period, which compared well with other independent measurements from sensors such as the Gravity Recovery and Climate Experiment (GRACE) satellite and results from climate models. This snow and ice loss corresponds to a 0.75 mm contribution to global sea-level rise each year.

It was reported this week that research undertaken by the Indian Space Research Organisation, Wadia Institute of Himalayan Geology and other institutions have revealed that the majority of the glaciers in India are retreating; albeit at different rates. Using remote sensing data up to 2006, the study looked at 82 glaciers in the Bhagirathi and Alaknanda river basins and found that there had been an overall loss of 4.6% of the glaciers within the region. The Dokriani glacier in Bhagirathi is retreating between 15 and 20 metres per year since 1995, whereas the Chorabari glacier in the Alaknanda basin is retreating 9-11 metres per year.

It’s interesting to read the retreating glacial picture alongside the research published by Schwanghart et al (2016), titled ‘Uncertainty in the Himalayan energy–water nexus: estimating regional exposure to glacial lake outburst floods’, in Environmental Research Letters. Here the research team completed the first region wide risk assessment of floods from glacial lakes, even though this only covered around a quarter dams in the Himalaya’s. The study mapped 257 dams against more than 2,300 glacial lakes within the region and found that over 20% of the dams are likely to be overwhelmed with flood water as rock systems that surround glacier-fed lakes fail. Due to the hydro-electric power needs of the region, more dams have been built in recent years, putting them closer to glacier-fed lakes.

The potential danger of this issue is demonstrated by the collapse of Zhangzangbo, a glacier-fed lake in southern Tibet, in 1981 where 20 million cubic meters of floodwater damaged hydroelectric dams and roads causing damage of approximately $4 million.

These three reports also show the potential danger melting ice and glaciers pose both locally and globally. Remote sensing data, particularly from satellites such as CryoSat-2, can help us monitor and understand whether this danger is increasing.

Sentinel’s Milestone and Millstone

Sentinel-1A multi-temporal colour composite of land coverage across Ireland. Contains modified Copernicus Sentinel data [2015], processed by ESA. Data courtesy of ESA.

Sentinel-1A multi-temporal colour composite of land coverage across Ireland. Contains modified Copernicus Sentinel data [2015], processed by ESA. Data courtesy of ESA.

There was be a significant milestone achieved for the European Commission’s Copernicus Programme with the launch of the Sentinel-1B satellite. It was the fourth satellite launched, and will complete the first of the planned constellations as the second Sentinel-1 satellite.

It was launched on 25th April from French Guiana. In addition, to Sentinel-1B, three student cubesats were onboard the Soyuz rocket. Students from the University of Liege, Polytechnic of Turin, Italy, and the University of Aalborg have developed 10cm square cubesats as part of ESA’s ‘Fly Your Satellite!’ programme which will be deployed into orbit.

Sentinel-1B is an identical twin to Sentinel-1A which was launched on the 3rd April 2014, and they will operate as a pair constellation orbiting 180 degrees apart at an altitude of approximately 700 km. They both carry a C-band Synthetic Aperture Radar (SAR) instrument and together will cover the entire planet every six days, although the Arctic will be revisited every day and Europe, Canada and main shipping routes every three days.

Sentinel-1 data has a variety of applications including monitoring sea ice, maritime surveillance, disaster humanitarian aid, mapping for forest, water and soil management. The benefits were demonstrated this week with:

  • Issuing a video showing the drop in rice-growing productivity in Mekong River Delta over the last year; and
  • The multi-temporal colour composite of land coverage of Ireland as shown at the top of this post. It was created from 16 radar scans over 12 days during May 2015, where:
    • The blues represent changes in water or agricultural activities such as ploughing, the yellows represent urban centres, vegetated fields and forests appear in green and the reds and oranges represent unchanging features such as bare soil.

With this constellation up and working, the revisit speed has the chance to be the game changer in the uptake of space generated data.

Sadly there’s a millstone hanging around the Copernicus Programme neck hindering this change – accessing the data remains difficult for commercial organisations.

Currently, selecting and downloading Sentinel data is a painful process, one that mostly either does not work, or is so slow you give up on it! This has been created by the size of the datasets and popularity of the data that’s free to access for everyone worldwide.

There are a number of ways of getting access to this data, with varying success in our experience, including:

  • EU’s Copernicus Hub – Operational, but slow to use. Once you have selected the data to download, either manually or via a script, the process is extremely slow and often times out before completing the downloading.
  • USGS – Offers Sentinel-2, but not Sentinel-1, data via it’s EarthExplorer and Glovis interfaces. The download process is easier, but the format of Sentinel-2 makes searching a bit strange in Glovis and it’s only a partial representation of the available acquisitions.
  • The UK Collaborative Ground Segment Access, despite signing an agreement with ESA in March 2015, has not yet been made available for commercial entities.
  • It is possible to apply for access to the academically focused STFC Centre for Environmental Data Analysis (CEDA) system, which provides FTP access, and that has good download speed’s for the data that’s available.
  • Amazon’s archive of Sentinel-2 data which has good download speeds, but is cumbersome to search without the development of software i.e. scripts.

There are also further services and routes being developed to facilitate searching and downloading from the various archives, e.g., there’s a QGIS ‘Semi-Automatic Classification’ plugin and EOProc SatCat service for Sentinel-2. With the Sentinel-3A data coming online soon the situation will get more complex for those of us trying to use data from all the Sentinel missions.

Getting the satellites into space is great, but that is only the first step in widening the use of space generated data. Until the data is put into the hands of people who use it to create value and inspire people, the Sentinel data will not fulfill its full potential in widening the use of space generated data.

Two Fantastic Remote Sensing Innovations

Aberdeenshire (Scotland) January 2016 flooding captured by Sentinel-1; Data courtesy of Copernicus/ESA

Aberdeenshire (Scotland) January 2016 flooding captured by Sentinel-1

Two academic remote sensing research announcements caught our eye this week. To be fair most remote sensing announcements catch our eye, but these two were intriguing as they are repurposing remote sensing techniques.

Remote Sensing the Human Body
Researchers at Kyoto University Centre of Innovation have developed a system based on spread-spectrum radar technology to remotely sense signals from the human body. They have focussed on heartbeats, although they acknowledge that other elements such as breathing and movement are also measured by the system. It uses a unique signal analysis algorithm to extract the beats of the heart from the radar signals, and then calculates the intervals to give the heartbeat.

Anyone who has ever needed to wear a Holter monitor for twenty-four or forty-eight hours will appreciate the advantage of having measurements taken remotely, in real time. In addition, under controlled conditions, the system has worked with a similar accuracy to an electrocardiographs (ECG). This will be music to the ears of regular ECG takers who know how much removing those sticky electrode pads can hurt!

This system is still at an early developmental stage and further testing and validation is necessary, but it offers a potential new use of remote sensing technology.

Remote Sensing & Social Media
Researchers from Pennsylvania State University have led a project developing an innovative way of combining social media and remote sensing. The research was undertaken on a flood in Boulder, Colorado in September 2013 with a particular focus on urban locations.

The team identified over 150,000 flood related tweets and used a cloud-based geo-social networking application called CarbonScanner, from The Carbon Project, to cluster the pictures from Twitter and Flickr to identify flooding hotspots. These were then used to obtain optical data, in this case from the high resolution commercial satellite Worldview 2 and the lower resolution, but freely available, Landsat 8.

A machine learning algorithm was developed to perform a semi-automated classification to identify individual pixels that contained water. As the data was optical it used the near infrared band as, due to its strong absorption, water is easily distinguishable from soil and vegetation. The researchers believe that this methodology has the potential to give emergency teams near real-time data, which could make live-saving differences to their work.

This is a particularly interesting development for us, given our current work on flood-mapping using synthetic aperture radar (SAR) data as part of the Space for Smarter Government Programme.

These two current examples show that remote sensing is an exciting, innovative and developing field, and one that is not solely related to Earth observation.

Twinkle, Twinkle, Little SAR

Copyright : NASA/JPL Artist's impression of the Seasat Satellite

Copyright : NASA/JPL
Artist’s impression of the Seasat Satellite

Last week ESA released a new synthetic aperture radar (SAR) dataset from NASA’s Seasat mission; nothing unusual in that you might think, except that this data is over 36 years old. As part of its Long Term Data Preservation Programme, ESA has retrieved, consolidated and reprocessed the Seasat data it holds, and made this available to the Earth observation (EO) community.

Seasat was a landmark satellite in EO terms when it was launched on the 27th June 1978. Not only was it the first satellite specifically designed for remote sensing of the oceans, but it was also the first to carry a SAR instrument. Seasat was only in orbit for 106 days as a problem with the electrical system ended the mission just over three months later on 10th October. Although, there is a conspiracy theory that the electrical fault was just a cover story, and the military actually shut down Seasat once they discovered it could detect submerged submarines wakes!

Synthetic aperture radar (SAR) is so called as it uses a small physical antenna to imitate having a large physical antenna; to detect the long wavelengths would require a physical antenna of thousands of metres, while the same result can be achieved with a synthetic antenna of around 10 metres in length. It is an active sensing radar system which works in the microwave part of the electromagnetic spectrum, and uses pulses of radiation to map the surface of the Earth. Pulses are transmitted with wavelengths of between metres and millimetres, some of these pules are absorbed by the surface, whereas others are reflected back and recorded by the SAR. As the satellite moves, the antenna’s position relative to the area that it is mapping changes over time providing multiple observations. This movement crates a large synthetic antenna aperture, because all the recorded reflections of a particular area are processed together as if they were collected by a single large physical antenna, which gives an improved spatial resolution.

SAR is extremely sensitive to small changes in surface roughness, and can provide both day and night imagery as it works independently of visible light, and is generally unaffected by cloud cover. It is used for assessing changes in waves, sea ice features and ocean topography, and recent research is applying it to other fields such as flood mapping. Seasat blazed the trail for SAR instruments, which has since been followed by many other satellites including ESA’s ERS-1 and ERS-2, ENVISAT’s ASAR, RadarSAT, COSMO-SkyMed, TerraSAR-X; and in 2014 both the Japanese ALOS, and ESA’s Sentinel-1, satellites carried SAR instruments.

The potential value residing in Seasat data is demonstrated not only by ESA reprocessing Seasat, but last year NASA also released a reprocessed Seasat dataset. The use of historic data is one of EO most powerful tools, and it is one the remote sensing community needs to exploit more.

SMAP ready to map!

Artist's rendering of the Soil Moisture Active Passive satellite.  Image credit: NASA/JPL-Caltech

Artist’s rendering of the Soil Moisture Active Passive satellite.
Image credit: NASA/JPL-Caltech

On the 31st January NASA launched their Soil Moisture Active Passive satellite, generally known by the more pronounceable acronym SMAP, aboard the Delta 2 rocket. It will go into a near polar sun-synchronous orbit at an altitude of 685km.

The SMAP mission will measure the amount of water in the top five centimetres of soil, and whether the ground is frozen or not. These two measurements will be combined to produce global maps of soil moisture to improve understanding of the water, carbon and energy cycles. This data will support applications ranging from weather forecasting, monitoring droughts, flood prediction and crop productivity, as well as providing valuable information to climate science.

The satellite carries two instruments; a passive L-Band radiometer and an active L-Band synthetic aperture radar (SAR). Once in space the satellite will deploy a spinning 6m gold-coated mesh antenna which will measure the backscatter of radar pulses, and the naturally occurring microwave emissions, from off the Earth’s surface. Rotating 14.6 times every minute, the antenna will provide overlapping loops of 1000km giving a wide measurement swath. This means that whilst the satellite itself only has an eight day repeat cycle, SMAP will take global measurements every two to three days.

Interestingly, although antennas have previously been used in large communication satellites, this will be the first time a deployable antenna, and the first time a spinning application, have been used for scientific measurement.

The radiometer has a high soil moisture measurement accuracy, but has a spatial resolution of only 40km; whereas the SAR instrument has much higher spatial resolution of 10km, but with lower soil moisture measurement sensitivity. Combining the passive and active observations will give measurements of soil moisture at 10km, and freeze/thaw ground state at 3km. Whilst SMAP is focussed on provided on mapping Earth’s non-water surface, it’s also anticipated to provide valuable data on ocean salinity.

SMAP will provide data about soil moisture content across the world, the variability of which is not currently well understood. However, it’s vital to understanding both the water and carbon cycles that impact our weather and climate.