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By Scott McCulloch. Edinburgh-based environment mapping firm awarded the contract from the UK Space Agency’s recently launched International Partnership Programme

Edinburgh-based environment mapping firm Ecometrica has won a £14.2 million contract with the UK Space Agency’s recently launched International Partnership Programme (IPP).

Ecometrica has developed a web-based geographic information system (GIS) which collates satellite data and on the ground information to create detailed environmental impact assessment maps.

The deal with IPP is for the ‘Forests 2020’ project, which aims to help countries improve the management and protection of more than 300 million hectares of tropical forests.

Ecometrica will lead an international consortium which includes some of the world’s leading experts on forest monitoring.

The contract, the largest to date from the £150 million UK Space Agency programme, was secured following a competitive tender process.

Last September Ecometrica signed a five-year memorandum of understanding with the University of Edinburgh’s School of Geosciences to provide academics unlimited access to Ecometrica’s state-of-the-art Earth Observation, geospatial intelligence and satellite mapping applications.

In return, the University will incorporate the Ecometrica Platform into research applications in the geospatial area.

As part of the IPP project, Ecometrica will sub-contract experts from the University of Edinburgh, the University of Leicester, and fellow Edinburgh company Carbomap, a specialist in LiDAR forest mapping.

The project will also see Ecometrica bring together various partners in Brazil, Colombia, Ghana, Indonesia, Kenya and Mexico, where Earth Observation laboratories will be set up to assess threats to rainforests and help direct conservation resources.

The project is expected to complete by March 2020.

Commenting on the new contract win, Dr Richard Tipper, executive chairman of Ecometrica, said: “This will help to establish Ecometrica as a leading international provider of digital infrastructure for earth observation services.

“Working with several organisations in each of the six countries, including research institutions, NGOs and conservationists on the ground, this project will help improve the capacity to implement effective forest and ecosystem monitoring services.

“It is estimated that improved monitoring systems, which enable a more targeted approach, could help prevent the loss of four to six million hectares of forest over the next decade: that’s an area more than half the size of Scotland, or two to three times the size of Wales.”

Dr Tipper added: “We all know how important tropical rainforests are to the survival of the global ecosystem, but most people are only just waking up to the fact that we need to use technology to make sure conservation efforts are effective and properly directed.

“The Earth Observation platforms will ensure threats such as fires and illegal logging are detected sooner, and make the response on the ground faster and more cost effective.”

Ray Fielding, head of the International Partnership Programme at the UK Space Agency, said: “We are very pleased to be working with Ecometrica to address deforestation and sustainable forest management for developing nations.

“The programme will identify innovative ways that space technology can help in this important area, which has been identified by the UN as key for sustainable development, and we intend to make a real difference to the people on the ground working to preserve the world’s forests.”

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Although not designed to deliver information on ice, ESA’s Earth Explorer SMOS satellite can detect thin sea-ice. Since its cousin, CryoSat, is better at measuring thicker ice scientists have found a way of using these missions together to yield an even clearer picture of the changing Arctic.

Carrying a radiometer, SMOS was designed capture images of brightness temperature. While these images can be turned into information on soil moisture and ocean salinity to improve our understanding of the water cycle, it turns out that these data can also be used to measure sea ice.

In contrast, CryoSat carries a radar altimeter that measures freeboard of sea ice, which is the distance between the waterline and the top of the ice.

This is being used to work out how the thickness of sea ice is changing and, in addition, how the volume of Earth’s ice is being affected by the climate.

Despite the two missions being very different, scientists from the University of Hamburg and the Alfred Wegener Institute (AWI) in Germany, who are involved in both Earth Explorer missions, have found a way of combining data from both satellites to gain a more complete picture of changes in the thickness of ice floating in Arctic waters.

While the accuracy of measurements from CryoSat increases with increasing ice thickness, SMOS data are more accurate when the sea ice is relatively thin, less than about a metre.

CryoSat measurements yield high-spatial resolution information and cover the Arctic every month. While SMOS offers daily images, they are a much coarser resolution than CryoSat.

Dr Robert Ricker from AWI said, “By combining ice-thickness estimates from CryoSat and SMOS, we obtain a more accurate and comprehensive view on the actual state of Arctic sea ice.
“Users need timely information across the entire Arctic and we can meet their needs by combing information from these two different, but complementary satellite missions.”

The University of Hamburg is already using SMOS to provide daily maps of Arctic sea-ice thickness during the winter. These maps are produced within 24 hours of the measurements being taken in space.

SMOS is also helping to improve the accuracy of sea-ice forecasts, which could help marine traffic operators to determine the safest and most economic routes through waters such as the Northwest Passage and the Northern Sea Route as the ice becomes thinner owing to climate change.

In addition, both missions’ archived data have been merged to generate information on thin sea-ice going back to 2010.

This will make an important contribution to studies into the fragile component of the Earth system and help to understand annual variations and climate change.

Prof. Lars Kaleschke, from the University of Hamburg, emphasised, “It is good see how information from two different types of measurements can be combined into one product to advance science and improve operational applications.
“It has now been demonstrated that using ice thickness information from SMOS improves the model computations and forecasts. It will be interesting to see how ocean current and air temperature models will benefit from a better understanding of the sea-ice fields.”

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(1 December 2016) Since the launch of the first Earth-observing satellites in the 1970s, numerous missions from international space organisations have taken to the sky. Today, decades of data are helping scientists to build a better picture of changes to our planet.

Between 2008 and 2009, a 750 sq km-area of ice in the northern Antarctic – known as the Wilkins Ice Shelf – partly disintegrated. At the time, ESA’s Envisat satellite monitored the event with the help of the DLR German Aerospace Center’s TerraSAR-X mission.

While the event itself made headlines, scientists got to work studying the ice’s behaviour before the break-up and continued to monitor the area for years afterward.

In a study published recently, a team of researchers from the German university Erlangen-Nürnberg examined data dating back to 1994 from the ERS mission to map the ice speed on the Wilkins Ice Shelf up through 2010 using Envisat, TerraSAR-X and Japan’s ALOS.

Measuring the speeds over different periods, the team discovered that while very stable in the mid-1990s, the major ice-front retreat in 2008 greatly affected upstream ice-shelf areas, causing an increase. This suggests that the area of ice lost was responsible for restraining upstream ice.

Monitoring the behaviour of ice yields important information for climate change modelling.

But in order to monitor changes in ice – or any other climate variables such as sea levels, greenhouse gases or land cover – over long periods, it is imperative that there are no gaps in the data.

ESA’s archives date back to the 1980s and include not only information from ESA’s own satellites, but also data from international missions.

Access to information from different satellites carrying similar sensors allows scientists to obtain a more complete picture of an area of interest. For example, Envisat continued to monitor the Wilkins Ice Shelf until its mission ended in 2012, but Germany’s TerraSAR-X, Canada’s Radarsat and Italy’s Cosmo-SkyMed continued to collect data over the area.

Within ESA’s Third Party Mission programme, access to data from these and other missions are available to the worldwide scientific community at no cost, following the submission of a project proposal.

Today, the Sentinel-1 mission ensures global satellite radar coverage into the future, and the Copernicus programme’s free and open data policy also allows access to these important data.

As with any technology, formats change over time. Data from Envisat or the even older ERS radar mission is not identical to those from Sentinel-1. ESA is addressing this issue through the Long Term Data Preservation Programme, which ensures that both old and new satellite data and associated information are properly preserved and available for scientists, policy-makers and value-adding companies.

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A new update of the ESA Sentinel App is coming up! The latest changes have brought us the acquisition plans and swath animations for Sentinel-1A, Sentinel-1B and Sentinel-2A, a powerful visualization of Sentinel product availability on the geographic and temporal dimensions, the highlights of the Sentinel-1 mission achievements and even a more complete picture of the satellite surroundings in the 3D model section, with the Earth, the Moon, the Sun and the stars now visible.

The Sentinel App is a gateway to knowing the Sentinel satellites. It lets users track the satellites in real-time, discover their key elements, read the latest news and learn more about their products.

Users can, among other things, explore detailed 3D models of the satellites, see the last and next time they have been and will be over the user’s location, move the satellites to the time of the last data transmission and smoothly move them back to their current location on the 3D globe. Notifications can also be set to be warned when the satellites are flying by.

On 25 December 2016, ESA has launched a very special update that introduces the details of the inside of the Sentinel-1, Sentinel-2, and Sentinel-3 units.
You can download ESA Sentinel App, it is available for iOS on the App Store and for Android on Google Play

RESOURCESAT-2A is a Remote Sensing satellite intended for resource monitoring. RESOURCESAT-2A was launched successfully by PSLV-C36 / on December 07, 2016 at 10:25 hrs (IST) from SDSC SHAR, Sriharikota.

RESOURCESAT-2A is a follow on mission to RESOURCESAT-1 and RESOURCESAT-2, launched in 2003 and 2011 respectively. RESOURCESAT-2A is intended to continue the remote sensing data services to global users provided by RESOURCESAT-1 and RESOURCESAT-2.

RESOURCESAT-2A carries three payloads which are similar to those of RESOURCESAT-1 and RESOURCESAT-2. They are a high-resolution Linear Imaging Self Scanner (LISS-4) camera operating in three spectral bands in the Visible and Near-Infrared Region (VNIR) with 5.8 m spatial resolution and steerable up to ± 26 deg across track to achieve a five-day revisit capability.

The second payload is the medium resolution LISS-3 camera operating in three spectral bands in VNIR and one in Short Wave Infrared (SWIR) band with 23.5 m spatial resolution. The third payload is a coarse resolution Advanced Wide Field Sensor (AWiFS) camera operating in three spectral bands in VNIR and one band in SWIR with 56 m spatial resolution.

RESOURCESAT-2A carries two Solid State Recorders with a capacity of 200 Giga Bits each to store the images taken by its cameras which can be read out later to ground stations.

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(By Juliet Van Wagenen | January 10, 2017) DigitalGlobe announced the results of the first SpaceNet Challenge, which will release openly licensed satellite imagery of Rio de Janeiro taken from the WorldView 2 satellite at 50cm Ground Sample Distance (GSD) using eight spectral bands.

[Via Satellite 01-10-2017] SpaceNet is a collaboration between DigitalGlobe, CosmiQ Works and NVIDIA, which consists of an online repository of freely available satellite imagery, co-registered map layers to train algorithms, and public challenges that aim to accelerate innovation in machine learning.

DigitalGlobe launched the first SpaceNet Challenge in November 2016, and 42 developers competed in an open challenge hosted by TopCoder to create algorithms that extract building footprints from satellite imagery. The participants submitted 242 solutions over a three-week period to compete for a total prize pool of $35,000 that was awarded to the top five performing contestants. The winning algorithms will be made available to the open-source community through the SpaceNet GitHub repository and users of DigitalGlobe’s Geospatial Big Data platform (GBDX).

“We are really thrilled by the developers’ level of engagement to use DigitalGlobe imagery, training data, and open-source code to create innovative algorithms,” said Tony Frazier, senior vice president and general manager of services at DigitalGlobe.

A newly released Points of Interest (POI) dataset for Rio de Janeiro is now freely available to the public via SpaceNet on AWS. This data is made available through the participation of the U.S. National Geospatial-Intelligence Agency, which licensed the dataset produced by DigitalGlobe. The Rio geodatabase contains 12 datasets with 35 unique layers containing more than 120,000 individual points of interest.

The next phase of the SpaceNet Challenge will be a follow-on competition using DigitalGlobe’s 30 cm imagery from WorldView 3 and building footprints across new locations around the globe. The competition will challenge developers to improve performance from the first competition using the higher-resolution imagery and more geographically diverse training data samples.

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On Nov. 14, 2016, the SpaceNet Challenge competition kicked off. Its goal is to advance the development of machine learning and deep learning algorithms that enable new applications in automated and more accurate mapping, and also to exploit a large corpus of satellite imagery for intelligence that can contribute to new technologies like automated vehicles.

“There is a need to take advantage of the vast repositories of satellite imagery that we already have so that new breakthroughs in geospatial disciplines and applications can be facilitated,” says Tod Bacastow, director of strategic alliances for DigitalGlobe, which owns and operates a constellation of in-orbit commercial satellites, and has under management a large body of satellite imagery that can be further plumbed and exploited for commercial and non-profit applications.

Bacastow references a time seven or eight years ago when researchers at Stanford University expressed a need for more advanced computer visualization technology that could be applied to geospatial data. “They wanted the technology to develop smarter geospatial information that could tell us more, and they also recognized that there was a machine language challenge that they were bumping up against,” Bacastow says. “What was needed was a body of raw satellite imagery that researchers could work with so that machine-based intelligence could be trained to interpret this data and provide automation for certain geospatial mapping and analytics functions that users could benefit from.”

A group of companies that included DigitalGlobe and Nvidia created a satellite imagery data repository for researchers so they could work on machine training and automation — and the SpaceNet competition was launched.

“For the first competition, we wanted to focus on urban infrastructure mapping,” Bacastow says. “So we started with a data repository that contained 200 square kilometers of imagery with over 200,000 building footprints for Rio de Janeiro. What we wanted to do in training the machines was to take a lot of the manual mapping steps out of urban infrastructure mapping.”

Bacastow says that when maps are created today, the process begins with taking satellite imagery and creating map vectors, which collect geographic information at various levels of detail. “The individual doing the mapping then traces against this satellite imagery, but he also discovers that it doesn’t scale well and that its accuracy could be questioned. … This is a process which could be improved with the map drawer creating a polygon and attributing certain attributes to it, like the type of building that is being mapped, and what its various functions are. After this step, potentially a machine automation process could follow this by drawing the vectors.”

Equally important is the ability to analyze the vast numbers of satellite images that are collected on a daily basis. It is humanly impossible to do this, but machine-based intelligence and automation could be inserted into the process to help.

As machine automation techniques get refined and the resulting data becomes more accurate, more practitioners in disciplines that use geospatial technology will trust and rely on it. This is where installing metrics into the process that can measure results for accuracy becomes very important.

“We score for map accuracy and we use human checkers and determine how well the map aligns with the on-the-ground physical truth,” Bacastow says. “We also score each vector that we evaluate.”

It is friendly competitions like the SpaceNet Challenge that will energize researchers from around the world to see just how they can use machine automation to not take geospatial satellite imagery and mapping to the next level. The possibilities are unlimited. The mapping of urban and remote areas of the world can be automated with intelligence-machine-based technology. In areas like humanitarian aid and disaster mitigation, resources can be expeditiously directed to where they are needed. In autonomous vehicle navigation and monitoring, more accurate mapping and higher precision results can be obtained.

“By training machines to analyze and work with satellite imagery, and then opening it up to research, we are also opening up new opportunities in innovation,” Bacastow says.

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(December 16, 2016 by George Leopold) Access to huge volumes of weather data—volumes that will likely soar after the November launch of the U.S. GOES-R weather satellite—has been limited to a few users at great expense.

Now a university-private sector networking effort will attempt to broaden access to atmospheric and weather data.

George Mason University, Fairfax, Va., and Ligado Networks, a satellite and terrestrial network specialist based on Reston, Va., said this week they would demonstrate the feasibility of delivering real-time weather data at lower cost over a cloud-based network.

The data is managed by the U.S. National Oceanic and Atmospheric Administration (NOAA), which also oversees the nation’s fleet of weather satellites. The constellation includes the next generation GOES-R, which stands for Geostationary Operational Environmental Satellite-R Series.

The partners said they would initially compare the delivery of data from current weather satellites with the new cloud-based weather data network. One goal is measuring the access speed and reliability of data delivery to meteorologists and other users across the U.S. The networking initiative also is intended to improve the accuracy of weather forecasting models as well as earlier detection of extreme weather such as tornadoes and dense ground fog.

Along with the cloud network, the partners said they also would provide free information extraction tools.

With the increase in extreme weather events, climate researchers at George Mason University and elsewhere have been studying how changes in the oceans and atmosphere affect weather patterns. The networking collaboration with Ligado is part of a push to train the next generation of climate researchers, including the university’s new bachelor’s program in atmospheric sciences.

“Faster and more accurate climate modeling and weather prediction will help people and organizations—including emergency responders—better prepare for and respond more quickly to weather-related events such as tornadoes, floods and wildfires, saving lives and livelihoods,” Deborah Crawford, the university’s vice president for research, noted in a statement Thursday (Dec. 15) announcing the weather network partnership.

Ligado also partners with other service providers to deliver secure communications to customers in North America. It is currently preparing to deploy a satellite and ground-based network infrastructure targeting Internet of Things and 5G wireless network markets.

Ligado CEO Doug Smith said the new network could be expanded to provide others schools, libraries and the public with improved access to NOAA weather data.

With the Nov. 19 launch of NOAA’s GOES-R satellite, there will plenty of new weather data to sift through. The next-generation geostationary weather satellite will provide continuous imagery and atmospheric measurements of the earth’s Western Hemisphere, significantly boosting satellite coverage for weather forecasters and climate scientists.

The payload of sensors also includes a lightning mapper along with a visualization tool that traces how lightning propagates through the atmosphere. The satellite reached its permanent station in geosynchronous orbit 22,000 miles away on Nov. 29. After the reaching its orbital slot, NOAA said the designation for GOES-R changed to GOES-16.

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Orchardists could soon benefit from space age technologies and increase farm productivity in terms of yield and management efficiencies.

Mapping our food from space will soon be the norm. Scientists from the University of New England (UNE) are testing satellite technologies as a way to track the health and growth of tropical tree crops, including avocados, mangoes, macadamia and bananas.

The scientists – Andrew Robson, Moshiur Rahman and Jasmine Muir, from the Agricultural Remote Sensing Team (ARST) within the university’s Precision Agricultural Research Group (PARG) – are investigating whether satellite-based remote sensing technology can provide accurate measures of crop yield, fruit size and quality.

If successful, growers will have access to up-to-date parameter-specific maps within a growing season to help them identify areas performing poorly because of inadequate nutrition, pests, diseases, too much moisture or not enough management. This will allow them to better manage crop inputs and make more informed decisions regarding harvest scheduling and forward selling.

At present, yield forecasting of tree crops such as avocado is undertaken by counting the fruit of a small number of trees, then extrapolated across the entire farm – a process both labour-intensive and inaccurate. An initial evaluation of satellite imagery coupled with targeted field sampling has indicated this approach to be more accurate for both avocado and macadamia. Using satellite imagery allows differences in individual tree health to be clearly seen across an orchard. When calibrated with actual fruit yield parameters, the imagery can be converted into surrogate fruit yield, size and quality maps.

The UNE team, in collaboration with the University of Queensland, University of Sydney, Central Queensland University and Queensland Department of Agriculture and Fisheries, has been sampling mango, banana, macadamia and avocado orchards across four Australian states, as part of an ongoing project funded by the Federal Rural Research and Development For Profit scheme and Horticulture Innovation Australia.

The scientists use satellite imagery, as well as a number of other ground and airborne sensors, to measure the health or vigour of individual tree canopies via their spectral characteristics. From this information, measures such as the Normalised Difference Vegetation Index, a scale commonly used to determine the amount of live green vegetation in a given area, is used to select specific trees for targeted field sampling. Once sampled, the varying yield parameters are correlated with additional vegetation indices to identify that which produces the strongest relationship.

For avocados in Bundaberg, Queensland, the team identified a correlation between a number of vegetation indices and fruit weight, both as tree yield and for individual fruit. These results are being validated across other growing regions and across seasons.

“We are still investigating this relationship,” says Robson, “but the research indicates there is an association between how big or healthy a tree is and its ability to set and then fill fruit.”

Satellite sensing might also enable farmers to better determine the quality and maturity of fruit across an orchard. This will lead to greater efficiencies at harvest time.

At present, fruit-pickers undertake selective harvesting at the start of the harvest season to pick fruits of optimal size and quality, which attract highest prices. This is achieved by the pickers inspecting each piece of fruit and choosing only those ripe and ready. In some cases, entire regions of an orchard may only produce lower grade fruit, the harvest of which demands high costs of wages and fuel, but results in low returns.

Strong correlations between satellite imagery and fruit size, achieved over three seasons, indicate that “fruit size” maps can be derived. This information allows growers to adopt targeted harvesting to intensively pick only those areas of the orchard that are bearing large fruit.

Although there is still a great deal of research to validate these results, if confirmed the technologies investigated through the entire project have the potential to revolutionise the Australian tree cropping industry and potentially other agricultural sectors as well.

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Business Beyond Borders is a new initiative funded by the European Commission with the objective to help EU businesses, in particular Small and Medium Enterprises (SMEs) and Clusters, to operate internationally.

The ultimate goal of Business Beyond Borders is to increase economic growth within and outside Europe.

Among the services it offers, the initiative helps companies participating in international fairs and exhibitions in maximising the benefits of their participation, notably through the organisation of Business to Business (B2B) and Cluster to Custer (C2C) matchmaking events.

The proposed support covers “before the event” activities (e.g. selection of potential business contacts and arrangement of business meetings), “during the event” activities (e.g. personalised assistance on the spot) and “after the event” activities (e.g. further development of first business contacts).

The initiative is coordinated by EUROCHAMBRES, the Association of European Chambers of Commerce and Industry, which represents over 20 million businesses in Europe – 98% of which are SMEs.

first opportunities in the year 2017 for EO companies:

28 Feb – 3 Mar Madrid Spain Energy, environment GENERA
16 May – 18 May Cape Town South Africa Power, water, waste utilities industries, in parallel with hydro, wind solar AUW
23 May- 25 May Sydney Australia ICT and digital services CEBIT Australia

more will come…visit BBB page
(Source European Commission and Copernicus website)