Evolution of the Earth Observation Market

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

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

The changing Earth Observation (EO) market has been a topic of office conversation this week at Pixalytics. We’re currently in the final stage of developing our own product portal, and it was interesting to see that some of our thoughts were echoed by reports from last week’s World Satellite Business Week event in Paris.

Unsurprisingly, speakers at the event agreed that the EO sector has huge growth potential. This is something we regularly see highlighted in various emails and press releases. For example, in the last few weeks we’ve had:

At a few thousand dollars for access to each report, we’ve said before that one of the products we should develop is an annual report on the EO market!

As we’ve been working towards our portal, one of issues we’ve identified is how difficult some portals are to navigate, particularly if you are not an EO expert. This was also recognised at the Paris event, with an acknowledgement that EO companies need to understand what customers want and then provide a user friendly experience to deliver those needs.

As reported by Tereza Pultarova in Space News, there was also discussion on the need to move away from simply selling data, and instead provide answers to the practical questions about the planet that businesses and consumers have. It is only through this transformation that new sectors and markets for EO will open which will be the key for the aforementioned future growth. The Paris event also highlighted some of the key trends that will be the backbone of this transformation:

  • Providing as close as possible to near real time data.
  • Increased data analytics, particularly through machine learning and artificial intelligence platforms to analyse data and highlight anomalies and changes faster.
  • Bringing satellite data together with social media information to rapidly enable context to be added to images.
  • Vertical integration within the industry within satellite firms acquiring with data processing and analytics companies; for example, Digital Globe acquired The Radiant Group earlier this year.
  • Processing data onboard satellites, so users download the information they want, rather than reams of data.

There was a really interesting analogy with the navigation industry given by Wade Larson, president and CEO of Urthecast. He said “Navigation became kind of embedded infrastructure in a much larger industry called location-based services. We think that this is happening with geoanalytics.”

This is the direction of travel for the industry, and some players are moving faster than others. Last week Airbus confirmed their four satellite very high-resolution-imaging constellation, Pléiades Neo, is on schedule for launch in 2020. This will have 30 cm spatial resolution and will utilise the Space Data Highway, also known as the European Data Relay System (EDRS), to stream the images into an online platform. The ERDS uses lasers to transfer up to 40 terabytes a day at a speed of up to 1.8 Gbits per second, meaning users will have access to data in near real time.

This evolution of the EO market needs to be recognised by every company in the industry from the Airbus down to the small company’s trying to launch their own product portal. If you don’t move with the changing market, you won’t get any of the market.

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.

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.

AgriTech Seeds Start to Grow in Cornwall

On Monday I attended the Jump Start AgriTech event hosted by the South West Centre of Excellence in Satellite Applications at the Tremough Innovation Centre on the University of Exeter’s Penryn campus near Falmouth in Cornwall. As the name suggests the one day event covered innovations in AgriTech with a particular focus on what is, or could be, happening in the South West.

The day began with a series of short presentations and Paul Harris, Rothamsted Research, was up first on their Open Access Farm Platform. North Wyke Farm in Devon has been equipped with a variety of sensors and instruments to understand the effects of different farming practices. Of particular interest to me was their analysis of run-off, weather monitoring and soil moisture every 15 minutes; this is a great resource for satellite product validation.

I was up next talking about Earth Observation (EO) Satellite Data for AgriTech. Having seen people overpromise and oversell EO data too many times, I began with getting people to think about what they were trying to achieve, before looking at the technology. The circle of starting questions, on the right, is how I begin with potential clients. If satellite EO is the right technology from these answers, then you can start considering the combinations of both optical/microwave data and free-to-access and commercial data. I went on to show the different types of satellite imagery and what the difference in spatial resolution looks like within an agriculture setting.

I was followed by Vladimir Stolikovic, Satellite Applications Catapult, who focused on the Internet of Things and how it’s important to have sensor network data collected and communicated, with satellite broadband being used in conjunction with mobile phones and WiFi coverage.

Our last talk was by Dr Karen Anderson, University of Exeter, who looked at how drones can capture more than imagery. I was particularly intrigued by the ‘structure from motion photogrammetry’ technique which allows heights to be determined from multiple images; such that for a much lower cost, you can create something similar to what is acquired from a Lidar or laser scanning instrument. Also, by focusing on extracting height, data can be collected in conditions where there’s variable amounts of light, such as under clouds, and it doesn’t requirement high accuracy radiometric calibration.

After coffee, case studies were presented on farming applications:

  • VirtualVet – Collecting data on animal health and drug use digitally, via mobile apps, so paper records don’t become out of data and data can be collated to gain greater insights.
  • Steve Chapman, SC Nutrition Ltd, talked about improving milk production by making sure dried food is optimally prepared – large pieces of dried sweetcorn are digested less well, and a lower nutritional value is extracted from them.
  • The delightfully named, Farm Crap App from FoAM Kernow, aims to encourage farmers to spread manure rather than use artificial fertilizer. Farmers tended to go for the latter as it is easier to calculate the effects, and so having advice, regulations and the important calculations in a phone app, rather than in paper tables, should help them use manure.
  • Caterina Santachiara, ABACO, describing their siti4FARMER solution which is a cloud-computing based platform that includes data which scales from the field to farm and large land areas, with individual customisation so that users can easily see what they need to know.
  • Finally, Glyn Jones from AVANTI, talked about how farmers can stay connected to the internet, and tech support, while out in their fields. This sounds straightforward, but none of the current technologies work well enough – mainly due to the fact that fields aren’t flat! So a new technological area of investigation is ‘white space’ – these are frequencies allocated to broadcasting services, but left unused in particular geographical locations as buffers. The availability varies from location to location, but it is available to lower-powered devices.

After lunch, there were some presentations on Agritech funding opportunities from Innovate UK, AgriTech Cornwall and the South West Centre of Excellence in Satellite Applications. The day concluded with a facilitated session where small groups explored a variety of different ideas in more detail.

It was a really good day, and shows that there is real potential for AgriTech to grow in the South West.

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.

Three Exciting Ways to Protect Forests With Remote Sensing

Forests cover one third of the Earth’s land mass and are home to more than 80% of the terrestrial species of animals, plants and insects. However, 13 million hectares of forest are destroyed each year. The United Nations International Day of Forests took place recently, on 21st March, to raise awareness of this vital resource.

Three remote sensing applications to help protect forests caught our eye recently:

Two scans show the difference between infected, on the right, and uninfected, on the left, patches of forest. Image Courtesy of University of Leiceste

Identifying Diseased Trees
In the March issue of Remote Sensing, researchers from the University of Leicester, (Barnes et al, 2017), published a paper entitled ‘Individual Tree Crown Delineation from Airborne Laser Scanning for Diseased Larch Forest Stands’. It describes how the researchers were able to identify individual trees affected by larch tree disease, also known as phytophthora ramorum.

This fungus-like disease can cause extensive damage, including the death, and diseased trees can be identified by defoliation and dieback. Airborne LiDAR surveys were undertaken by the company Bluesky at an average altitude of 1500 m, with a scan frequency of 66 Hz that gave a sensor range precision within 8 mm and elevation accuracy around 3–10 cm.

Remote sensing has been used to monitor forests for many years, but using it to identify individual trees is uncommon. The researchers in this project were able to successfully identify larch canopies partially or wholly defoliated by the disease in greater than 70% of cases. Whilst further development of the methodology will be needed, it is hoped that this will offer forest owners a better way of identifying diseased trees and enable them to respond more effectively to such outbreaks.

Monitoring Trees From Space
An interesting counterpoint to work of Barnes et al (2017) was published by the journal Forestry last month. The paper ‘Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications‘ written by Fassnacht et al (2017).

It describes work undertaken to compare the results of very high resolution optical satellite data with that of airborne LiDAR and hyperspectral data to provide support for forestry management. The team used WorldView-2 images, of a temperate mixed forest in Germany, with a 2m pixel size, alongside a LiDAR DTM with a 1 m pixel size. This data was then used to estimate tree species, forest stand density and biomass.

They found  good results for both forest stand density and biomass compared to other methods, and although the tree classification work did achieve over eighty percent, this was less than achieved by hyperspectral data over the same site; although differentiation of broadleaved and coniferous trees was almost perfect.

This work shows that whilst further work is needed, optical data has the potential to offer a number of benefits for forestry management.

Monitoring Illegal Logging
Through the International Partnership Programme the UK Space Agency is funding a consortium, led by Stevenson Astrosat Ltd, who will be using Earth Observation (EO) data to monitor, and reduce, illegal logging in Guatemala.

The issue has significant environmental and socioeconomic impacts to the country through deforestation and change of land use. The Guatemalan government have made significant efforts to combat the problem, however the area to be monitored is vast. This project will provide a centralised system using EO satellite data and Global Navigation Satellite Systems (GNSS) technology accessed via mobile phones or tablets to enable Guatemala’s National Institute of Forestry (INAB) to better track land management and identify cases of illegal logging.

Overall
The protection of our forests is critical to the future of the planet, and it’s clear that satellite remote sensing can play a much greater role in that work.

Supporting Uganda’s Farmers

Map of Uganda showing vegetation productivity. Underlying data is the MODIS 2014 NPP Product, MOD17 – Zhoa et al. (2005).

Uganda is a landlocked country of just over 240,000 square kilometres. Agriculture is a key element of the country’s economy and was responsible for 23% of gross domestic product in 2011 and almost half the country’s exports the following year. According to the Food & Agriculture Organisation of the United Nations, 80% of the population relies on farming for its livelihood.

It has an equatorial climate, with regional variations, although recent recurrent dry spells have impacted on crop and livestock productivity. Pixalytics is delighted to be part of a consortium led by the RHEA Group, working with the Ugandan Ministry of Water and Environment and local NGOs to develop a Drought and Flood Mitigation Service (DFMS) to give practical information to help local communities respond to the effects of climate change.

Using computer models populated with satellite, meteorological, water resources and ground based data an innovative Environment Early Warning Platform will be developed to provide Ugandan farmers, via local NGO organisations, with forecasts throughout the growing seasons to enable them to take actions to maximise their crop yield.

Pixalytics, along with fellow consortium member, Environment Systems, are responsible for the Earth Observation data in the project. We’ll be looking at variety of optical and radar data to provide information about flood and drought conditions alongside crops and their growing conditions.

The project should benefit local communities by:

  • Improving the ability to forecast and mitigate droughts and floods on a local actionable scale.
  • Allowing NGOs to target resources saving time, money and lives.
  • Allowing farmers to improve their lives and better protect their livestock and crops.

Alongside ourselves, and RHEA Group, our consortium includes Environment Systems, Databasix, AA International, AgriTechTalk International, HR Wallingford, UK Met Office, Mercy Corps, and Oxford Policy Management. We will also work with international partners, including the Uganda Government Ministries, Kakira Sugar Company, and the NGO Green Dreams/iCOW. The first of a number of visits to Uganda took place last week, where we had the opportunity to make lots of local contacts and meet some of those whom we hope to benefit from this work.

This work is part of the UK Space Agency’s International Partnership Programme and ours is one of 21 projects chosen to provide solutions to local issues in counties across Africa, Asia, Central and South America.

This is a really exciting project to be involved with, and we’re looking forward to providing useful information to local farmers to allow them to take real and meaningful action to enhance the productivity, and protection, of their livestock and crops.

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.