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.

Satellite Data Continuity: Hero or Achilles Heel?

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

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

One of satellite remote sensing’s greatest strengths is the archive of historical data available, allowing researchers to analyse how areas change over years or even decades – for example, Landsat data has a forty year archive. It is one of the unique aspects of satellite data, which is very difficult to replicate by other measurement methods.

However, this unique selling point is also proving an Achilles Heel to industry as well, as highlighted last week, when a group of 179 researchers issued a plea to the European Commission (EC) and the European Space Agency (ESA) to provide a replacement for the aging Cryosat-2 satellite.

Cryosat-2 was launched in 2010, after the original Cryosat was lost during a launch failure in 2005, and is dedicated to the measurement of polar ice. It has a non sun-synchronous low earth orbit of just over 700 km with a 369 day ground track cycle, although it does image the same areas on Earth every 30 days. It was originally designed as three and half year mission, but is still going after six years. Although, technically it has enough fuel to last at least another five years, the risk of component failure is such that researchers are concerned that it could cease to function at any time

The main instrument onboard is a Synthetic Aperture Interferometric Radar Altimeter (SIRAL) operating in the Ku Band. It has two antennas that form an interferometer, and operates by sending out bursts of pulses at intervals of only 50 microseconds with the returning echoes correlated as a single measurement; whereas conventional altimeters send out single pulses and wait for the echo to return before sending out another pulse. This allows it to measure the difference in height between floating ice and seawater to an accuracy of 1.3cm, which is critical to measurement of edges of ice sheets.

SIRAL has been very successful and has offered a number of valuable datasets including the first complete assessment of Arctic sea-ice thickness, and measurements of the ice sheets covering Antarctica and Greenland. However, these datasets are simply snapshots in time. Scientists want to continue these measurements in the coming years to improve our understanding of how sea-ice and ice sheets are changing.

It’s unlikely ESA will provide a follow on satellite, as their aim is to develop new technology and not data continuity missions. This was part of the reason why the EU Copernicus programme of Sentinel satellites was established, whose aim is to provide reliable and up to date information on how our planet and climate is changing. The recently launched Sentinel-3 satellite can undertake some of the measurements of Cryosat-2, it is not a replacement.

Whether the appeal for a Cryosat-3 will be heard is unclear, but what is clear is thought needs to be given to data continuity with every mission. Once useful data is made available, there will be a desire for a dataset to be continued and developed.

This returns us to the title of the blog. Is data continuity the hero or Achilles Heel for the satellite remote sensing community?

How to Measure Heights From Space?

Combining two Sentinel-1A radar scans from 17 and 29 April 2015, this interferogram shows changes on the ground that occurred during the 25 April earthquake that struck Nepal. Contains Copernicus data (2015)/ESA/Norut/PPO.labs/COMET–ESA SEOM INSARAP study

Combining two Sentinel-1A radar scans from 17 and 29 April 2015, this interferogram shows changes on the ground that occurred during the 25 April earthquake that struck Nepal. Contains Copernicus data (2015)/ESA/Norut/PPO.labs/COMET–ESA SEOM INSARAP study

Accurately measuring the height of buildings, mountains or water bodies is possible from space. Active satellite sensors send out pulses of energy towards the Earth, and measure the strength and origin of the energy received back enabling them to determine of the heights of objects struck by the pulse energy on Earth.

This measurement of the time it takes an energy pulse to return to the sensor, can be used for both optical and microwave data. Optical techniques such as Lidar send out a laser pulse; however within this blog we’re going to focus on techniques using microwave energy, which operate within the Ku, C, S and Ka frequency bands.

Altimetry is a traditional technique for measuring heights. This type of technique is termed Low Resolution Mode, as it sends out a pulse of energy that return as a wide footprint on the Earth’s surface. Therefore, care needs to be taken with variable surfaces as the energy reflected back to the sensor gives measurements from different surfaces. The signal also needs to be corrected for speed of travel through the atmosphere and small changes in the orbit of the satellite, before it can be used to calculate a height to centimetre accuracy. Satellites that use this type of methodology include Jason-2, which operates at the Ku frequency, and Saral/AltiKa operating in the Ka band. Pixalytics has been working on a technique to measure river and flood water heights using this type of satellite data. This would have a wide range of applications in both remote area monitoring, early warning systems, disaster relief, and as shown in the paper ‘Challenges for GIS remain around the uncertainty and availability of data’ by Tina Thomson, offers potential for the insurance and risk industries.

A second methodology for measuring heights using microwave data is Interferometric Synthetic Aperture Radar (InSAR), which uses phase measurements from two or more successive satellite SAR images to determine the Earth’s shape and topography. It can calculate millimetre scale changes in heights and can be used to monitor natural hazards and subsidence. InSAR is useful with relatively static surfaces, such as buildings, as the successive satellite images can be accurately compared. However, where you have dynamic surfaces, such as water, the technique is much more difficult to use as the surface will have naturally changed between images. Both ESA’s Sentinel-1 and the CryoSat-2 carry instruments where this technique can be applied.

The image at the top of the blog is an interferogram using data collected by Sentinel-1 in the aftermath of the recent earthquake in Nepal. The colours on the image reflect the movement of ground between the before, and after, image; and initial investigations from scientists indicates that Mount Everest has shrunk by 2.8 cm (1 inch) following the quake; although this needs further research to confirm the height change.

From the largest mountain to the smallest changes, satellite data can help measure heights across the world.

EO applications and the ESA Living Planet Symposium

Last week’s blog looked at developments in the technology providing Earth Observation (EO); however the industry is evolving and much more attention is now being paid to downstream activities. It’s no longer good enough to get a satellite to collect data, everyone has to think about how applications will, and can, use the data.

At the Living Planet Symposium there were presentations on the applications being developed from European Space Agency’s (ESA) CryoSat-2, which was launched in April 2010; it’s a replacement for Cryosat-1, which was lost due to a launch failure in 2005. CryoSat-2’s main focus is the monitoring of sea ice thickness in the polar oceans and ice sheets over Greenland and Antarctica. During its 3 years of full operation it has witnessed a continuing shrinkage of winter ice volume.

However, the on-board altimeter can also be used for many other applications, for example it doesn’t just acquire data over the polar regions. More interestingly the presenters also showed its potential for mapping coastal waters and inland water bodies with a spatial coverage that’s not possible from current low resolution altimeters.

Freshwater is a scarce resource, 97.5% of the earth’s water is saltwater, and given that almost three quarters of that freshwater is used in agriculture to grow food; the benefits of developing a method for remotely obtaining accurate river/lake water heights with frequent coverage are obvious.

No doubt there will be a variety of new applications developed using this freshwater data over the coming period. However, these applications need to have one eye on the next significant revolution in EO; data visualisation. It’s becoming vital that data is made available in a form that is understandable for non-scientists, and this will be the subject of next weeks blog!