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.

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.

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!

Locusts

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.

Monkeys

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.

Blue Holes from Space

Andros Island in The Bahamas. Acquired by Landsat 8 in February 2017. Data courtesy of NASA.

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 ‘blue hole’ 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’s an archipelago, it is considered as a single island. It’s 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:

Blues in the Blue Hole National Park on the Andros Island in The Bahamas. Acquired by Landsat 8 in February 2017. Data courtesy of NASA.

  • Blue Holes National Park covers over 33,000 acres and includes a variety of blue holes, freshwater reservoirs and forests within its boundaries. The image to the right covers an area of the national park. In the centre, just above the green water there are five black circles  – despite the colour, these are blue holes.
  • Uncle Charlie’s Blue Hole, also called Little Frenchman Blue Hole, is just off Queen’s Highway in Nicholls Town and has a maximum depth of 127 metres.
  • Atlantis Blue Hole has a maximum depth of about 85 metres.
  • Stargate Blue Hole his blue hole is located about 500 miles inland from the east coast of South Andros on the west side of The Bluff village.
  • Guardian Blue Hole is in the ocean and is believed to have the second deepest cave in The Bahamas, with a maximum explored depth of 133 metres.

Blue hole in the south of Andros Island in The Bahamas. Acquired by Landsat 8 in February 2017. Data courtesy of NASA.

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’t always appear blue!

Pixalytics: Five Years & Thriving!

Background Image: Sutichak Yachaingham / 123 Stock Photo

The start of June marked the five-year anniversary of Pixalytics!

For a small start-up business, like ours, five years is an important milestone. Depending on which you report you believe only around 50%, or even 40%, of new small business survive their five years! So we should definitely celebrate the fact that we’re still here!

The last twelve months have been successful for us. Our key highlights have included:

  • Continuing to grow our income year-on-year
  • Expanded our team to five, soon to be six, employees – which is a 100% increase over the last year!
  • Moved to a new office on Plymouth Science Park
  • Part of a consortium developing a Drought and Flood Mitigation Service (DFMS) in Uganda.
  • Secured our first European Contract and so now we are exporters!

It has been a lot of hard work, but we’re really pleased with what we’ve achieved.

In a similar blog last year, we wrote about our target of releasing an innovative series of automated Earth Observation products and services. You’ll have noticed that this is not listed in our highlights, as despite our efforts we’ve not managed to do this … yet.

We have made significant progress with our eStore. We have a number of products almost ready to go, the product interface has been developed and we’re currently developing the front end eCommerce website. We’re intending to go live with flooding, turbidity and ocean colour products. So watch this space, things will be happening later this year – we hope!

Launching the products is really the easy bit, the difficult part will be getting people to buy them and this a challenge which firms much larger than us are still to effectively solve. As a small business we tend to market through our website, social media and the odd exhibition. However, we’ll need to come up with some new cost-effective innovative ideas for our eStore if it is to be successful. We’re also participating in Europe wide projects established by EARSC and the Copernicus World Alliance looking at ways of developing the market and promoting Earth Observation products and services.

For the last couple of years we’ve quoted a phrase from ‘Worstward Ho’, a monologue by Samuel Beckett which is ‘Ever tried. Ever failed. No matter. Try Again. Fail again. Fail better.’

This sums up our approach. We try things. If they don’t work out, we try something else. It’s worked okay so far.

Before we leave our five year celebration, we wanted to take the opportunity to thank all of the people who’ve helped us along our journey, including the readers of our blog.

Let’s hope we’re still here in another five years!

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.