No Paraskevidekatriaphobia For Sentinel-5P!

Sentinel-5P carries the state-of-the-art Tropomi instrument. Image courtesy of ESA/ATG medialab.

On Friday the latest of the Sentinel satellites, Sentinel-5P, is due to be launched at 09.27 GMT from Plesetsk Cosmodrome in Russia.

Friday is the 13th October, and within parts of the western world this is considered to be an unlucky date – although in Italy its Friday 17th which is unlucky and in some Spanish speaking countries it is Tuesday the 13th. Fear of Friday 13th is known as paraskevidekatriaphobia, although evidently it isn’t something Sentinel-5P worries about!

Sentinel-5 Precursor, to give the full title, is dedicated to monitoring our atmosphere. It will create maps of the various trace gases such as nitrogen dioxide, ozone, formaldehyde, sulphur dioxide, methane and carbon monoxide alongside aerosols in our atmosphere. The mission will also support the monitoring of air pollution over cities, volcanic ash, stratospheric ozone and surface UV radiation.

An internal view of the Copernicus Sentinel-5P satellite. Image courtesy of ESA/ATG medialab.

The satellite itself is a hexagonal structure as can be seen in the image to the right. It has three solar wings which will be deployed once the polar sun-synchronous 824 km low earth orbit has been achieved. Sentinel-5P will be orbiting three and half minutes behind NOAA’s Suomi-NPP satellite which carries the Visible/Infrared Imager and Radiometer Suite (VIIRS). This synergy will allow the high resolution cloud mask from VIIRS to be used within the calculations for methane from Sentinel-5P.

Within the hexagonal body the main scientific instrument is the Tropospheric Monitoring Instrument (Tropomi). This is a push-broom imaging spectrometer covering a spectral range from ultraviolet and visible (270–495 nm), near infrared (675–775 nm) and shortwave infrared (2305–2385 nm). The spatial resolution of the instrument will be 7 km x 3.5 km. However, one of the exciting elements of this instrument is that it will have a swath width of 2600 km meaning it can map almost the entire planet every day. It will have full daily surface coverage of radiance and reflectance measurements for latitudes > 7° and < -7°, and better than 95 % coverage for other latitudes.

The key role of Sentinel-5P is to reduce the data gap between the end of the Envisat mission in May 2012 and the launch of Sentinel-5 in 2020. Sentinel-5, and Sentinel-4, will be instruments onboard meteorological satellites operated by Eumetsat and both will be used to monitor the atmosphere.

The timing of Sentinel-5 is interesting for those of within the UK given that almost three quarters of the funding from Copernicus comes from the European Union. By this time Brexit will have occurred and it is currently unclear how that will impact on our future involvement in this programme. This also applies to the work announced at the end of last month to look at an expansion of the Sentinel missions. Invitations to tender (ITT) are due to be issued in the near future, and given our previous blogs on potential limitations and issues, it will be interesting to see which UK companies bid, and whether they will be successful.

Sentinel-5P will help improve our understanding of the processes within the atmosphere which affect our climate, the air we breathe and ultimately the health of everyone on the planet.

Marine Zulu Gathering

Looking out from the Woods Hole Oceanographic Institute, taken on the 1st October 2017

This week I’m at the Integrated Marine Biosphere Research (IMBeR) IMBIZO5 event at the Woods Hall Oceanographic Institute. IMBIZO is a Zulu word meaning a meeting or gathering called by a traditional leader and this week a group of marine scientists have heeded the call.

The fifth meeting in the IMBIZO series is focussing on Marine Biosphere Research for a Sustainable Ocean: Linking ecosystems, future states and resource management. Its aim is help understand, quantify and compare the historic and present structure and functioning of linked ocean and human systems to predict and project changes including developing scenarios and options for securing or transitioning towards ocean sustainability.

Woods Hole is located in the US state of Massachusetts. It is well-known centre of excellence in marine research and the world’s largest private, non-profit oceanographic research institution. Despite my career travels, it was somewhere I had never visited before. So this was a great opportunity to see a place I had read a lot about, and to meet people from a variety of marine disciplines.

After my Saturday morning flight to Boston, my first challenge was to find the fantastically named ‘Peter Pan Bus’ for the two hour drive to Falmouth, a town near the Woods Hole Institute. Regular readers will spot that this is the second Falmouth I’ve visited this summer, as I gave talk in the Cornish version in July. It’s actually slightly odd to hear familiar place names such as Plymouth, Barnstaple and Taunton in a different country. Carrying my poster also singled me out as an IMBIZO attendee, Lisa stopped to give me a lift to hotel as I walked through the town – not sure that would happen back in the UK!

I needed to be up early on Sunday as we had an Infographics workshop led by Indi Hodgson-Johnston from the University of Tasmania. We learnt about how to work through the creative process, starting with choosing a theme through to defining 4 to 8 factoids (1 to 2 sentences with a single message) to finally bringing the factoids and accompanying images together into the infographic.

Interestingly, Indi highlighted that only 20% of the people who start watching a video on social media are still watching after 15 seconds! In addition, most watch without sound. The key message for me was to make very short videos with subtitles. Or better still make infographics.

The workshop itself began on Monday with three keynotes. The first by Edward Allison, of the University of Washington, focussed on the limits of prediction and started by defining terms and their time scales:

  • Forecasts: from minutes to weeks e.g. weather forecasting
  • Predictions: from months to years e.g. climate variability
  • Scenarios: front decades to centuries e.g. climate change

As we go from forecasts to predictions uncertainty increases, and further still when we move to scenarios. Therefore, we need to be clear about the limits of what’s possible. Secondly, whilst we’ve become good at understanding bio-chemical and physical processes, uncertainty grows as we move to modelling ecosystems and human interactions.

Mary Ann Moran from the University of Georgia spoke about the ‘Metabolic diversity and evolution in marine biogeochemical cycling and ocean ecosystem processes’ and emphasised the linkage between phytoplankton and microbes, and how omics (fields such as metabolomics, (meta)-proteomics and -transcriptomics) can help us to understand this complex relationship.

The final keynote was by Andre Punt from the University of Washington on ‘Fisheries Management Strategy Evaluation’. It looked at how we move from data on fish catches to deciding what a sustainable quota is for managing fishing stocks. Management strategy evaluation involves running multiple simulations to compare the relative effectiveness of achieving management objectives i.e., a “fisheries flight simulator”. Given the different stakeholders in this debate will often have opposing requirements; the wrong choice can have catastrophic effects on either fish populations or livelihoods. Hence, this approach often involves finding the least worst solution.

The workshop streams began in the afternoon and I’m in one focussing on ‘Critical Constraints on Prediction’. We all gave 3 minute lightening talks to introduce ourselves and started the discussion on the topic of uncertainties and how these can be reduced in future projections.

Exploring this topic over the next few days is going to be really interesting!

Can You See The Great Wall of China From Space?

Area north of Beijing, China, showing the Great Wall of China running through the centre. Image acquired by Sentinel-2 on 27th June 2017. Data courtesy of ESA/Copernicus.

Dating back over two thousand three hundred years, the Great Wall of China winds its way from east to west across the northern part of the country. The current remains were built during Ming Dynasty and have a length of 8 851.8 km according to 2009 work by the Chinese State Administration of Cultural Heritage and National Bureau of Surveying and Mapping Agency. However, if you take into account the different parts of the wall built by other dynasties, its length is almost twenty two thousand kilometres.

The average height of the wall is between six and seven metres, and its width is between four to five metres. This width would allow five horses, or ten men, to walk side by side. The sheer size of the structure has led people to believe that it could be seen from space. This was first described by William Stukeley in 1754, when he wrote in reference to Hadrian’s Wall that ‘This mighty wall of four score miles in length is only exceeded by the Chinese Wall, which makes a considerable figure upon the terrestrial globe, and may be discerned at the Moon.’

Despite Stukeley’s personal opinion not having any scientific basis, it has been repeated many times since. By the time humans began to go into space, it was considered a fact. Unfortunately, astronauts such as Buzz Aldrin, Chris Hatfield and even China’s first astronaut, Yang Liwei, have all confirmed that the Great Wall is not visible from space by the naked eye. Even Pixalytics has got a little involved in this debate. Two years ago we wrote a blog saying that we couldn’t see the wall on Landsat imagery as the spatial resolution was not small enough to be able to distinguish it from its surroundings.

Anyone who is familiar with the QI television series on the BBC will know that they occasionally ask the same question in different shows and give different answers when new information comes to light. This time it’s our turn!

Last week Sam was a speaker at the TEDx One Step Beyond event at the National Space Centre in Leicester – you’ll hear more of that in a week or two. However, in exploring some imagery for the event we looked for the Great Wall of China within Sentinel-2 imagery. And guess what? We found it! In the image at the top, the Great Wall can be seen cutting down the centre from the top left.

Screenshot of SNAP showing area north of Beijing, China. Data acquired by Sentinel-2 on 27th June 2017. Data courtesy of ESA/Copernicus.

It was difficult to spot. The first challenge was getting a cloud free image of northern China, and we only found one covering our area of interest north of Beijing! Despite Sentinel-2 having 10 m spatial resolution for its visible wavelengths, as noted above, the wall is generally narrower. This means it is difficult to see the actual wall itself, but it is possible to see its path on the image. This ability to see very small things from space by their influence on their surroundings is similar to how we are able to spot microscopic phytoplankton blooms. The image on the right is a screenshot from Sentinel Application Platform tool (SNAP) which shows the original Sentinel-2 image of China on the top left and the zoomed section identifying the wall.

So whilst the Great Wall of China might not be visible from space with the naked eye, it is visible from our artificial eyes in the skies, like Sentinel-2.

Two New Earth Observation Satellites Launched

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

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

Two new Earth observation satellites were launched last week from European Space Centre in Kourou in French Guyana, although you may only get to see the data from one. Venµs and OPTSAT-3000 were put into sun synchronous orbits by Arianespace via its Vega launch vehicle on the 1st August. Both satellites were built by Israel’s state-owned Israel Aerospace Industries and carry instruments from Israel’s Elbit Systems.

Venµs, or to give its full title of Vegetation and Environment monitoring on a New MicroSatellite, is a joint scientific collaboration between the Israeli Space Agency (ISA) and France’s CNES space agency.

Venµs is focussed on environmental monitoring including climate, soil and topography. Its aim is to help improve the techniques and accuracy of global models, with a particular emphasis on understanding how environmental and human factors influence plant health. The satellite is equipped with the VENµS Superspectral Camera (VSSC) that uses 12 narrow spectral bands in the Visible Near Infrared (VNIR) spectrum – ranging from 420nm wavelength up to 910 nm wavelength – to capture 12 simultaneous overlapping high resolution images which are then combined into a single image. The camera uses a pushbroom collection technique and has a spatial resolution of 5.3m and a swath size of 27.56 km.

Venµs won’t have full global coverage; instead there are 110 areas of interest around the world that includes forests, croplands and nature reserves. With a two day revisit time, during which time it completes 29 orbits of the planet. This means every thirtieth image will be collected over the same place, at the same time and with the same angle. This will provide high resolution imagery more frequently than is currently available from existing EO satellites. The consistency of the place, time and angle will help researchers better assess fine-scale changes on the land to improve our understanding of the:

  • State of the soil,
  • vegetation growth,
  • detection of spreading disease or contamination,
  • snow cover and glacial movements; and
  • sediment movement in coastal estuaries

A specific software algorithm has been developed for the mission to work with the different wavelengths to remove clouds and aerosols from the satellite’s imagery, giving clear images of the planet irrespective of atmospheric conditions.

The second satellite launched was the OPTSAT-3000 which is an Italian controlled optical surveillance satellite, which will operate in conjunction with the COSMO-SkyMed radar satellites giving Italy’s Ministry of Defence independent autonomous national Earth observation capability across optical and radar imagery.

This is a military satellite and so some of the details are difficult to verify. As mentioned earlier the instrument was made by Elbit systems, and the camera used usually offers a spatial resolution of around 0.5 m. However, it has been reported that the resolution will be much closer to 0.3m because the satellite is in a very low earth orbit of a 450 km.

OPTSAT-3000 will collect high resolution imaging of the Earth, it’s not clear at this stage whether any of the imagery will be made available for commercial/scientific use or purchase, although it is worth noting that COSMOS-SkyMed images are sold.

Two more Earth observation satellites launched shows that our industry keeps on moving forward! We’re really interested, and in OPTSAT’s case hopeful, to see the imagery they produce.

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.

Locusts & Monkeys

Soil moisture data from the SMOS satellite and the MODIS instrument acquired between July and October 2016 were used by isardSAT and CIRAD to create this map showing areas with favourable locust swarming conditions (in red) during the November 2016 outbreak. Data courtesy of ESA. Copyright : CIRAD, SMELLS consortium.

Spatial resolution is a key characteristic in remote sensing, as we’ve 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’ve 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 ‘brightness temperature’ of the Earth, which indicates the radiation emitted from planet’s 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’s 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’re currently using soil moisture data in a project to provide an early warning system for droughts and floods.


Earlier this month the paper, ‘Connecting Earth Observation to High-Throughput Biodiversity Data’, 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:

  • Earth observation data to map roads and human settlements.
  • Automated recordings of animal sounds to determine what species are in the area.
  • Mosquitos have been caught and analysed to determine what they have been feeding on.

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.

Small Sea Salinity & Satellite Navigation Irrigation

Artists impression of the Soil Moisture and Ocean Salinity (SMOS) satellite. Image courtesy of ESA – P. Carril.

A couple of interesting articles came out in the last week relating to ESA’s Soil Moisture and Ocean Salinity (SMOS) mission. It caught our attention, as we’re currently knee deep in SMOS data at the moment, due to the soil moisture work we’re undertaking.

SMOS was launched in November 2009 and uses the interferometry technique to make worldwide observations of soil moisture over land and salinity over the ocean. Although its data has also been used to measure floating ice and calculate crop-yield forecasts.

The satellite carries the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument, which is a 2D interferometric L-band radiometer with 69 antenna receivers distributed on a Y-shaped deployable antenna array. It has a temporal resolution of three days, with a spatial resolution of around 50 km.

A recent ESA article once again showed the versatility of SMOS, reporting that it was being used to measure the salinity in smaller seas, such as the Mediterranean. This was never an anticipated outcome due to radio interference and the land-sea boundary contamination – where the land and ocean data can’t be distinguished sufficiently to provide high quality measurements.

However, the interference has been reduced by shutting down illegal transmitters interrupting the SMOS signal and the land-sea contamination has been reduced by work at the Barcelona Expert Centre to change the data processing methodology.

All of this has meant that it’s possible to use SMOS to look at how water flows in and out of these smaller seas, and impact on the open oceans. This will help complement the understanding being gained from SMOS on ocean climate change, ocean acidification and the El Niño effect.

A fascinating second article described a new methodology for measuring soil moisture using reflected satellite navigation signals. The idea was originally from ESA engineer Manuel Martin-Neira, who worked on SMOS – which we accept is a bit more of a tenuous link, but we think it works for the blog! Manuel proposed using satellite navigation microwave signals to measure terrestrial features such as the topography of oceans.

This idea was further developed by former ESA employee Javier Marti, and his company Divirod, and they have created a product to try and reduce the overuse of irrigation. According to Javier, the system compares reflected and direct satnav signals to reveal the moisture content of soil and crops and could save around 30% of water and energy costs, and improve crop yields by 10-12%. It is a different methodology to SMOS, but the outcome is the same. The work is currently been tested with farmers around the Ogallala aquifer in America.

For anyone working in soil moisture, this is an interesting idea and shows what a fast moving field remote sensing is with new approaches and products being developed all the time.

Beware of the Bluetooth Gnomes and Other Stories from GISRUK 2017

Gorton Monastry, GISRUK 2017

The 2017 GIS Research UK (GISRUK) Conference took place last week in Manchester, and Pixalytics sponsored the Best Early-Career Researcher Prize.

I was looking forward to the event, but I nearly didn’t get there! I was planning to catch the train up from London on Wednesday. However, the trackside fire at Euston station put paid to that, as my train was cancelled. Instead I was at the station bright and early on Thursday morning.

The first presentation I saw was the inspiring keynote by Professor Andrew Hudson-Smith. He talked about ‘getting work out there and used’ and using the Internet of Things to create a ‘census of now’ i.e., rather than having census data a number of years out-of-date, collect it all of the time. Personally, I also enjoyed hearing about his Bluetooth gnomes in Queen Elizabeth Olympic Park, which talk to you about cyber security. A visit to his gnomes is definitely on my list for the next spare weekend in London!

I spent the rest of the afternoon in the Infrastructure stream of presentations where there were talks on spatially modelling the impact of hazards (such as flooding) on the National Grid network, human exposure to hydrocarbon pollution in Nigeria, deciding where to site, and what type of, renewable energy and investigating taxi journeys.

In the evening, the conference dinner was at ‘The Monastery’, also known as Gorton Monastery. Despite the name, it was actually a friary built by the Franciscan monks who travelled to Manchester in 1861 to serve the local Catholic community. It was one of the first churches to be completed by the Franciscans in England after the Reformation. It became derelict in the mid 1990’s and ended up on the World Monuments Fund Watch List of 100 Most Endangered Sites in the World. Since then it has been restored and is used as a spectacular community venue.

Friday started with the morning parallel sessions, and I picked ‘Visualisation’ followed by ‘Machine Learning’. Talks included ‘the Curse of Cartograms’ (and if you don’t know what these curses are, have a look here!), land-use mapping and tracking behaviour at music festivals using mobile phone generated data – which won the best spatial analysis paper. However, my favourite talk was given by Gary Priestnall on the projection augmented relief models, which use physical models of a location’s terrain that are then overlaid with imagery/videos shown using a projector. The effect was fantastic!

Our closing keynote, ‘The Great Age of Geography 2017’, was from Nick Crane, known to UK TV viewers as the ‘map man’. He reflected on the role of geographers throughout history and then into the future. He equated the breakthrough in printing, from wood blocks to copper plates that could be engraved in more detail and updated, to today’s transition from analogue to digital.

The conference finished with the awards. I was delighted to present Alyson Lloyd and James Cheshire with the Best Early-Career Researcher Prize for their presentation on ‘Challenges of Big Data for Social Science: Addressing Uncertainty in Loyalty Card Data’. Unfortunately, as it was on Wednesday afternoon, it wasn’t one I’d seen personally. However, I’ve downloaded the conference paper, available from here, and I’m look forward to reading it.

It was an excellent conference, and I was really enjoyed my time in Manchester. Looking forward to GISRUK 2018!

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.

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.

Catching Wavelength 2017

Remote sensing, like GIS, excels in integrating across disciplines and people. Whilst no one ever said being a multi-disciplinary scientist was going to be easy, for the ‘thirsty’ mind it challenges, cross pollinates ideas and looks at problems with new eyes. A diverse group of people connected by a common thread of spatial and remotely sensed data found themselves doing all these things and more in London last week at the Wavelength 2017 conference.

The talks and posters took us on whirlwind tour through the ever varying landscape of remote sensing. We moved through subject areas ranging from detecting ground ice, vegetation and overall land cover, through to earth surface movement and 3D imaging, and onto agriculture yield and drought. We also covered the different vertical scales from which remotely sensed data is collected, whether from satellites, planes, drones or cameras operated from ground level. On top of this focus we also had some great key note talks, running through the varied career of a remote sensing scientist (Groeger Ltd), as well as in depth data assimilation of remote sensing imagery in models (UCL) and commercial developments in airborne camera work (Geoxphere Ltd).

In parallel, we were taken on a grand tour covering the temperate UK, parts of the Middle East, the tundra in North America, the central belt of Africa, and even onto the moon and Mars! In many cases we heard talks from scientists from these countries (though not the moon or Mars …). Some are based at the universities in the UK, whilst, others came specifically to talk at the conference.

I found myself transfixed by the far flung places. Listening to how the dark side of the moon is being mapped, a place that never sees daylight and is incredibly ‘chilly’ and traps ice in these shadowed lands. I also heard about the CO2 that precipitates out of the atmosphere on Mars as snow and forms a 1m blanket. Working in places like Africa started to feel really quite local and accessible!

Possibly the most intriguing aspect of the conference for me, was the advancements that have been made in photogrammetry and how multiple photos are now being used to produce highly intricate 3D models. We saw this applied to cliff morphology and change detection, as well as the 3D point clouds that are produced when modelling trees and vegetation generally.

The 3D models aren’t totally complete due to line of sight and other issues. The model visualisations look like an impressionist painting to me, with tree leaves without trunks or clumps of green mass suspended in mid air. However, this does not matter when calculating leaf volume and biomass, as these discrepancies can be worked with and lead to some very useful estimates of seasonality and change.

Setting this up is no small feat for the organiser, and PhD student, James O’Connor. He delivered an interesting programme and looked after the delegates well. I can truly say I haven’t been to such a friendly conference before. It was also unique in providing ample time to discuss aspects of material presented, both from talks and posters, and sharing technical know-how. This felt of real value, especially to the PhD students and young professionals this conference is geared towards, but equally myself with experience in only certain fields of remote sensing.

I would highly recommend Wavelength, and look forward to seeing what they are planning for 2018!

Blog written by Caroline Chambers, Pixalytics Ltd.