AND BEST WISHES FOR 2018¬†
from everyone at Pixalytics
AND BEST WISHES FOR 2018¬†
from everyone at Pixalytics
One of the key global challenges is food security. A number of reports issued last week, coinciding with World Food Day on the 16th October, demonstrated how Earth Observation (EO) could play a key part in tackling this.
Climate change is a key threat to food security. The implications were highlighted by the¬†U.S. Geological Survey (USGS) report who described potential changes to suitable farmland for rainfed crops. Rainfed farming accounts for approximately 75 percent of global croplands, and it‚Äôs predicated that these locations will change in the coming years. Increased farmland will be available in North America, western Asia, eastern Asia and South America, whilst there will be a decline in Europe and the southern Great Plains of the US.
The work undertaken by USGS focussed on looking at the impact of temperature extremes and the associated changes in seasonality of soil moisture conditions. The author of the study, John Bradford said ‚ÄúOur results indicate the interaction of soil moisture and temperature extremes provides a powerful yet simple framework for understanding the conditions that define suitability for rainfed agriculture in drylands.‚ÄĚ Soil moisture is a product that Pixalytics is currently working on, and its intriguing to see that this measurement could be used to monitor climate change.
Given that this issue may require farmers to change crops, work by India‚Äôs Union Ministry of Agriculture to use remote sensing data to identify areas best suited for growing different crops is interesting. The Coordinated Horticulture Assessment and Management using geoinformatics (CHAMAN) project has used data collected by satellites, including the Cartosat Series and RESOURCESAT-1, to map 185 districts in relation to the best conditions for growing bananas, mangos, citrus fruits, potatoes, onions, tomatoes and chilli peppers.
The results for eight states in the north east of the country will be presented in January, with the remainder a few months later, identifying the best crop for each district. Given that India is already the second largest producer of fruit and vegetables in the world, this is a fascinating strategic development to their agriculture industry.
The third report was the announcement of a project between the University of Queensland and the Chinese Academy of Sciences which hopes to improve the accuracy of crop yield predictions. EO data with an improved spatial, and temporal, resolution is being used alongside biophysical information to try to predict crop yield at a field scale in advance of the harvest. It is hoped that this project will produce an operational product through this holistic approach.
These are some examples of the way in which EO data is changing the way we look at agriculture, and potential help provide improved global food security in the future.
Last week, whilst Europe‚Äôs Earth Observation (EO) community was focussed on the successful launch of Sentinel-5P, over in America Tuesday 10th October was Earth Observation Day!
This annual event is co-ordinated by AmericaView, a non-profit organisation, whose aim to advance the widespread use of remote sensing data and technology through education and outreach, workforce development, applied research, and technology transfer to the public and private sectors.
Earth Observation Day is a Science, Technology, Engineering, and Mathematics (STEM) event celebrating the Landsat mission and its forty-five year archive of imagery. Using satellite imagery provides valuable experience for children in maths and sciences, together with introducing subjects such as land cover, food production, hydrology, habitats, local climate and spatial thinking. The AmericaView website contains a wealth of EO materials available for teachers to use, from fun puzzles and games through to a variety of remote sensing tutorials. Even more impressive is that the event links schools to local scientists in remote sensing and geospatial technologies. These scientists provide support to teachers including giving talks, helping design lessons or being available to answer student‚Äôs questions.
This is a fantastic event by AmericaView, supporting by wonderful resources and remote sensing specialists. We first wrote about this three years ago, and thought the UK would benefit from something similar. We still do. The UK Space Agency recently had an opportunity for organisations interested in providing education and outreach activities to support EO, satellite launch programme or the James Webb Space Telescope. It will be interesting to see what the successful candidates come up with.
At Pixalytics we‚Äôre passionate about educating and inspiring the next generation of EO scientists. For example, we regularly support the Remote Sensing and Photogrammetry Society‚Äôs Wavelength conference for students and early career scientists; and sponsored the Best Early-Career Researcher prize at this year‚Äôs GISRUK Conference. We‚Äôre also involved with two exciting events at Plymouth‚Äôs Marine Biological Association, a Young Marine Biologists (YMB) Summit for 12-18 year olds at the end of this month and their 2018 Postgraduate conference.
Why is this important?
The space industry, and the EO sector, is continuing to grow. According to Euroconsult’s ‚ÄėSatellites to Be Built & Launched by 2026‚Äô ‚Äď I know this is another of the expensive reports we highlighted recently ‚Äď there will be around 3,000 satellites with a mass above 50 kg launched in the next decade ‚Äď of which around half are anticipated as being used for EO or communication purposes. This almost doubles the number of satellites launched in the last ten years and doesn‚Äôt include the increasing number of nano and cubesats going up.
Alongside the number of satellites, technological developments mean that the amount of EO data available is increasing almost exponentially. For example, earlier this month World View successfully completed multi-day flight of its Stratollite‚ĄĘ service, which uses high-altitude balloons coupled with the ability to steer within stratospheric winds. They can carry a variety of sensors, a mega-pixel camera was on the recent flight, offering an alternative vehicle for collecting EO data.
Therefore, we need a future EO workforce who are excited, and inspired, by the possibilities and who will take this data and do fantastic things with it.
To find that workforce we need to shout about our exciting industry and make sure everyone knows about the career opportunities available.
Last Tuesday I was at the academic launch event for the Tru-Nject project at Cranfield University. Despite the event‚Äôs 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‚Äôs official title is ‚ÄėTru-Nject: Proximal soil sensing based variable rate application of subsurface fertiliser injection in vegetable/ combinable crops‚Äô. 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‚Äôd acquired the imagery, we processed it to:
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, ‚ÄúI never believed I‚Äôd get to tell a satellite what to do.‚Äô 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‚Äôve 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 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‚Äôt 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 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:
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‚Äôs, 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!
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 ‚Äď 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‚Äôve spotted so far, although there may be others, are:
It‚Äôs clear this is a huge iceberg, so huge in fact that most news agencies don‚Äôt 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:
This event shows how¬†satellites are monitoring the planet, and the¬†different ways we can see the world changing.
Spatial resolution is a key characteristic in remote sensing, as we‚Äôve previously discussed. Often the view is that you need an object to be significantly larger than the resolution to be able to see it on an image. However, this is not always the case as often satellites can identify indicators of objects that are much smaller.
We‚Äôve previously written about satellites identifying phytoplankton in algal blooms, and recently two interesting reports have described how satellites are being used to determine the presence of locusts and monkeys!
Desert locusts are a type of grasshopper, and whilst individually they are harmless as a swarm they can cause huge damage to populations in their paths. Between 2003 and 2005 a swarm in West Africa affected eight million people, with reported losses of 100% for cereals, 90% for legumes and 85% for pasture.
Swarms occur when certain conditions are present; namely a drought, followed by rain and vegetation growth. ESA and the UN Food and Agriculture Organization (FAO) have being working together to determine if data from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to forecast these conditions. SMOS carries a Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) instrument – a 2D interferometric L-band radiometer with 69 antenna receivers distributed on a Y-shaped deployable antenna array. It observes the ‚Äėbrightness temperature‚Äô of the Earth, which indicates the radiation emitted from planet‚Äôs surface. It has a temporal resolution of three days and a spatial resolution of around 50 km.
By combining the SMOS soil moisture observations with data from NASA‚Äôs MODIS instrument, the team were able to downscale SMOS to 1km spatial resolution and then use this data to create maps. This approach then predicted favourable locust swarming conditions approximately 70 days ahead of the November 2016 outbreak in Mauritania, giving the potential for an early warning system.
This is interesting for us as we‚Äôre currently using soil moisture data in a project to provide an early warning system for droughts and floods.
Earlier this month the paper, ‚ÄėConnecting Earth Observation to High-Throughput Biodiversity Data‚Äô, was published in the journal Nature Ecology and Evolution. It describes the work of scientists from the Universities of Leicester and East Anglia who have used satellite data to help identify monkey populations that have declined through hunting.
The team have used a variety of technologies and techniques to pull together indicators of monkey distribution, including:
Combining these various datasets provides a huge amount of information, and can be used to identify areas where monkey populations are vulnerable.
These projects demonstrate an interesting capability of satellites, which is not always recognised and understood. By using satellites to monitor certain aspects of the planet, the data can be used to infer things happening on a much smaller scale than individual pixels.
Blue holes are deep marine caverns or sinkholes which are open at the surface, and they get their name from their apparent blue colour of their surface due to the scattering of the light within water. The often contain both seawater and freshwater, and in their depths the water is very clear which makes them very popular with divers.
The term ‚Äėblue hole‚Äô first appeared on sea charts from the Bahamas in 1843, although the concept of submarine caves had been described a century earlier (from Schwabe and Carew, 2006). There are a number of well-known blue holes in Belize, Egypt and Malta amongst others. The Dragon Hole in the South China Sea is believed to be the deepest blue hole with a depth of 300 metres.
The Andros Island in The Bahamas has the highest concentration of blue holes in the world, and last week we watched a television programme called River Monsters featuring this area. The presenter, Jeremy Wade, was investigating the mythical Lusca, a Caribbean sea creature which reportedly attacks swimmers and divers pulling them down to their lairs deep within of the blue holes. Jeremy fished and dived some blue holes, and spoke to people who had seen the creature. By the end he believed the myth of the Lusca was mostly likely based on a giant octopus. Whilst this was interesting, by the end of the programme we were far more interested in whether you could see blue holes from space.
The image at the top is Andros Island. Although, technically it‚Äôs an archipelago, it is considered as a single island. It‚Äôs the largest island of The Bahamas and at 2,300 square miles is the fifth largest in the Caribbean. There are a number of well known blue holes in Andros, both inland and off the coast, such as:
The image to the¬†right is from the south of the island. Just off the¬†centre, you can see a blue hole surrounded by forests and vegetation.
So we can confirm that the amazing natural features called blue holes can be seen from space, even if they don‚Äôt always appear blue!
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.
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 Yucat√°n 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‚Äôs thermal band detected temperatures higher than normal.
Compare this to a wildfire on Florida-Georgia border acquired from NASA‚Äôs 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.
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 ‚Äď 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.
The first national geo-information study of China was released last week at a State Council Information Office press briefing.
The study, also referred to as the national census of geographic conditions, was originally announced in March 2013. Over the last three years 50,000 professionals have been involved in collecting a variety of data about China and it‚Äôs reported that they have achieved a 92% coverage of the country, generating around 770 terabytes of data in the process.
Data has been collected on natural resources, such as land features, vegetation, water and deserts; together with urban resources such as transport infrastructure, towns and neighbourhoods. This information was gathered, and verified, through remote sensing satellites, drones, aerial photography, 3D laser scanning and in-situ data. It‚Äôs reported that the accuracy is 99.7% with a 1 m resolution.
China is one of the largest countries in the world by land mass, at approximately 9.6 m square kilometres. Therefore, simply completing such a study with the accuracy and resolution reported is highly impressive.
It may take years to fully appreciate the variety, size and usefulness of this new dataset. However, a number of interesting high level statistics have already been released by the Chinese Ministry of Land and Resources including:
According to Kurex Mexsut, deputy head of the National Administration of Surveying, Mapping and Geoinformation, the Chinese Government will be looking to establish a data sharing mechanism and information services platform for this dataset, together with a variety of data products. It is hoped that public departments and companies will be able to use this to help improve the delivery of public services.
Although not from the survey, the image at the top is of the Yuqiao Reservoir, situated just to the east of Beijing. It has a surface area of 119 sq km, with an average depth of 14 metres.
Not only is this a comprehensive geo-information dataset for a single country, but there is also huge potential for further information to be derived from this dataset. We‚Äôll be watching with interest to see how the data is used and the impact it has.