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GeoVille is delighted to announce the release of the first, validated Sentinel-2 based land cover map. It’s the first national implementation retrieved via landmonitoring.earth, a fully-automatic land monitoring solution set-up by GeoVille. The homogenous and seamless land cover map was produced for entire Austria covering an area of 84,000 km².

In order to meet the reporting obligations from international conventions, European directives and national legislations, countries are required to produce up to date, detailed and harmonised information on their land cover and its use, at different scales and for different domains of applications. Although Europe can build upon a long experience of land cover and land use mapping, most of the existing national datasets respond to different needs and have been produced with differing standards and methodologies. Thus, they lack comparability across sectors and are in many cases outdated.

To this end, GeoVille set-up a unique solution for monitoring every country in Europe in high spatial resolution and in dense time intervals. This fully-automatic, dynamic, land-monitoring solution is based on highly-advanced processing technologies and is available as a direct service on landmonitoring.earth or as B2B API services, ready to be integrated into client workflows or business solutions. Thereby, it enables continuous information feeds to web-based Land Information Systems (LIS), geoportals, platforms or any analytical IT systems.

The first national implementation is a validated Sentinel-2 based, homogenous and seamless land cover map for entire Austria covering an area of 84,000 km². The map is integrated into the Land Information System Austria (LISA) that was implemented with the objective to achieve a national consensus on how to perform a continuous mapping of the national land cover and monitor its change. The dynamic product is available at a monthly frequency and comprises information such as agricultural activities, changes in ecosystem conditions and the management intensity of grassland areas. Thereby, it reduces the existing lack of information is various fields such as spatial planning, forestry, agriculture, water as well as environmental protection and conservation.

The full system implementation was funded by the Federal Ministry for Transport, Innovation and Technology (bmvit) through the Austrian Space Applications Programme (ASAP) as well as the European Space Agency (ESA).

For more information please visit:
landmonitoring.earth
https://www.landinformationsystem.at/#/lisa/overview
http://www.copernicus.eu/news/first-validated-sentinel-2-land-cover-map-austria

Toulouse, 10 April 2018 – Airbus has entered into an agreement with Twenty First Century Aerospace Technology Co. Ltd (21AT), the Chinese commercial satellite operator, for the distribution of the images acquired by their TripleSat constellation.

The TripleSat constellation consists of three identical very high-resolution Earth observation satellites set 120° apart, travelling around the same orbit. They offer daily monitoring of any place on Earth revealing details as small as 80 centimetres. The satellites were specifically designed to map large area coverage and will therefore reinforce the Pléiades and SPOT satellite capacities, improving access to information in critical situations.

On the optical side, Airbus’ constellation already comprises the very high-resolution Pléiades 1A and 1B, the high-resolution SPOT 6 and SPOT 7 satellites as well as the DMC constellation. On the radar side, weather-independent satellites such as TerraSAR-X and TanDEM-X were recently joined by the PAZ radar satellite. The constellation is also reinforced by satellite partners such as KazEOSat. These partnerships complement the offering and service for demanding applications.

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Precision agriculture aims to optimize returns by automated observation of crop fields using small unmanned aerial vehicles. The challenge is to provide a complete system that combines very high spatial resolution and detailed spectral measurements to extract the information you need.

Let me tell you how a compact camera, like ButterflEYE LS, combined with our new spatiospectral processing chain allows you to image agricultural fields to analyse vegetation down to the individual plant level, while detailed spectral measurements allow early detection of vegetation stress and diseases.

Raw image as captured by a spatiospectral imager, measuring different wavelengths along the vertical axis

DESIGNING A MINIATURE HYPERSPECTRAL IMAGING SYSTEM

To make this happen, two elements are essential! A small and lightweight camera that fits the platform and a powerful processing solution that turns the data into useful products. Ideally, hardware and software are developed in tandem, so they can be optimized together to generate high quality results. That is why we developed the spatio-spectral imager, a very innovative spectral imaging concept to build a miniature camera. It combines strong points of push-broom and frame based imagers and is ideally suited to capture images with both high spatial and spectral resolution. As a result, it collects more information per gram camera weight than competing systems.

The core of the camera is a frame sensor with a large number of hyperspectral filters deposited on the sensor pixels, with different spectral bands arranged in lines. A raw image taken with such a sensor looks a bit odd: it resembles a regular 2D image, but in fact every few lines it captures a different part of the electromagnetic spectrum.

THE CHALLENGES OF COLLECTING DATA

To collect full spectra at each spot of the terrain, images are captured at high speed. Conventional frame cameras on drones typically acquire images at much lower speed, e.g. 1 per second. To avoid motion blur, the integration times are much shorter, e.g. 1/1000 second, so the camera is only collecting light for a very small fraction of the total flying time. By acquiring images much more rapidly, a spatiospectral camera can extract much more information in the same time.

The dense image sequences looks like an aerial movie which gradually explores an area. However, with every new image, the spatiospectral camera does not just capture new locations, but probes additional spectral information for all points in sight. A beautiful concept, but also a big challenge on the image processing side since the spectral information of one point on the ground is coded in multiple raw images.

SOLVING THE SPATIOSPECTRAL PUZZLE

So how do we unravel the spectral information and produce high quality image products? We had to rethink the entire processing flow to solve this. Based on solid photogrammetric principles to ensure geometrically accurate results, we developed a unique and innovative set of methods containing dedicated tools to handle dense spatiospectral image sequences.

The processing includes:
- aerial triangulation
- bundle block adjustment and outlier detection
- camera calibration
- dense point cloud extraction
- detailed 3D digital surface model generation

The spectral information at all wavelengths is extracted from the input images and is projected onto hyperspectral layers so it becomes aligned at pixel level. Radiometric and spectral corrections are applied to generate reliable spectral reflectance products, from which maps containing useful information such as vegetation indices and biophysical parameter estimates are derived for precision agriculture and environmental monitoring. All this bundled in a generic automated processing solution which can be adapted to various camera systems.

CAMERA SYSTEMS GENERATING USEFUL INFORMATION

Currently, we are developing several spatiospectral cameras which benefit from this processing. The first result is the ButterflEYE LS camera, developed together with German camera builder Cubert gmbh. For this camera, the processing creates hypercubes with orthomosaiced hyperspectral reflectance maps.

For all our spatiospectral cameras, the goal is to provide a complete system which enables the users to concentrate on carrying out their flights, and be assured that the processing system takes care of the spectral data. The magic performed under the hood transforms this data into detailed useful information.

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Descartes Labs and Planetek Italia have announced a partnership to transform big data from space into actionable knowledge for global users. The agreement brings together Descartes Labs’ machine learning algorithms and computer vision tools with Planetek’s monitoring services based on the Rheticus® cloud platform.

Under the agreement, Descartes Labs and Planetek Italia will develop new remote sensing applications in areas such as precision farming and sustainable development. This partnership follows the paradigm shift of Earth observation services, moving from a project-based model to an information-as-a-service model.

Thanks to the automatic analysis of satellite big data in the cloud, the creation of analytics with a spatial dimension becomes dynamic. This is possible by combining the capabilities of Descartes Labs’ artificial intelligence, machine learning, and cloud computing, with Planetek Italia’s more than twenty years of experience and activity in the design and development of Earth observation services related to Copernicus, the European Union flagship program for Space.

“I have no doubt that our partnership with Descartes Labs will boost the value of our Rheticus® platform tremendously. Thanks to this partnership, our customers will benefit from the improvement in our geoanalytics production, offering superior value to our customers worldwide,” said Planetek Italia Chief Executive Officer, Giovanni Sylos Labini. “This agreement also gives us the ability to follow the path toward an information-as-a-service model, drown by Europe with the Copernicus Data and Information Access Services (DIAS). The European Space Agency has been far-sighted in favoring the meeting between European companies and companies like Descartes Labs at the last Future EO conference in May 2017.”

“We are very pleased to partner with Planetek, a company that is aligned with our business and acts as a compliment to the work we’re doing in geospatial science,” said Co-Founder and Chief Executive Officer of Descartes Labs, Mark Johnson. “Planetek’s team is using Copernicus and ESA’s state-of-the art imagery to raise the standard in mapping, change detection, and applications of remote sensing to agriculture. Our goal is that by working together, we can more quickly and accurately diagnose some of the world’s most plaguing forecasting problems.”

Companies’ assets and agreement highlights

Descartes Labs has created a cloud-based supercomputing platform for the application of machine intelligence to massive data sets. Capitalizing on the confluence of advances in AI and high-performance cloud computing — along with the rapid increase of sensors capturing information all over the globe — Descartes Labs has created an enterprise data refinery. Today, Descartes Labs uses satellite imagery to model complex systems on the planet, like forestry and agriculture. The company processes data flows from all the major satellite constellations at scale to provide instant access to analysis-ready images of the entire world in a massive, searchable, on-demand interface.

Planetek has created Rheticus®, an automatic cloud-based geo-information service platform, designed to provide fresh and accurate data and information on our changing world. Rheticus® provides timely information that fits the needs of a growing number of business applications. The information is provided as a service and includes maps, reports and geospatial indexes, designed to monitor several phenomena: territorial changes, urban dynamics and land use changes, ground displacements (landslide and subsidence), infrastructure stability, new infrastructure and construction areas, wildfire burned areas or coastal seawater quality.

Thanks to this agreement, Planetek Italia will expand the range of monitoring services and geoanalytics provided by Rheticus® on the web on a global scale through an international network of Rheticus® partners. Descartes Labs will find potential new applications and research areas, positioning both partners to fully unlock the value of big satellite data from Space and create significant new value for customers.

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Planetek Hellas and Planetek Italia have signed a framework contract with the European Union Satellite Center (SatCen), for the provision of Earth Observation based Very High Resolution Reference Mapping products in support to FRONTEX, the European Border and Coast Guard Agency.

The information products to be provided will enhance border surveillance, a current challenge for the European Union as regards migration and security. The Reference Mapping Service aims at providing a background of geographical context, including relevant information on hydrography, topography, land cover, infrastructure and population. The service will support the monitoring of border areas and the improvement of decision-making and response capabilities of the authorities responsible for controlling and monitoring European borders.

“Being the only SME’s within this group of large companies that have signed the same framework contract is certainly a challenge for us”, said Giovanni Sylos Labini, CEO, Planetek Italia and Planetek Hellas. “We are thankful to SatCen for the trust that has shown to Planetek Group and we are committed to provide the best possible services to this highly esteemed EU Entrusted Entity”, he concluded.

“We are very pleased and at the same time very conscious about the responsibility we undertake, to be able to contribute to such a delicate issue for the European Union. The fact that our countries, Greece and Italy, are among the most affected ones from the situation in the wider neighbouring region, increases the level of our commitment to perform well,” said Stelios Bollanos, Director of Planetek Hellas, who is the leading company of the consortium.

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Hurricane Irma was the largest Atlantic storm in the last decade. It was the 5th costliest hurricane on record in the U.S.A, causing $5 billion of damage after hitting the south west coast of Florida and moving up through Atlanta and Georgia. A 3m storm surge in the Florida Keys caused damage to approximately 90% of all buildings and collapsed 25%. Disaster response teams struggled for weeks to clear debris and distribute aid. A key requirement for dealing with the destruction was access to timely, accurate information about ground conditions after the storm.

Image: Marco Island, Florida, captured on 18 September 2017 by KOMPSAT-3A

Satellite derived Earth Observation (EO) data can fill this need and has become an indispensable part of disaster response and management. The International Disasters Charter, which provides EO data in the case of a disaster, has been activated 6 times in 2018 already. When hurricane Irma hit in 2017, the charter was activated, and a variety of EO analysis initiatives were started by groups including M.I.T. and Oxford’s Machine Learning Group. A mix of crowd-sourced and machine learning methods were used to guide the rescue efforts of “Rescue Global”, a disaster risk reduction and response charity. The crowd-derived results were analysed using machine learning algorithms to generate heat maps of areas where aid was needed most. Such a “Planetary Response Network” is an excellent example of how remotely sensed data can be an invaluable tool in disaster response, however, it is still reliant on user input. What if new data could identify damage automatically, and create data products for disaster response teams without manual interpretation?

Research has attempted to address this issue, but, a fundamental problem of damage identification is that, in many cases, it cannot be seen from above. Collapsed roofs, for instance, are notoriously difficult to identify because, without height information, collapsed and intact roofs can look very similar. If a digital surface model (DSM) could be generated from one satellite pass shortly before a disaster and another after, the change in height between the two could be used to identify building collapse. This would require stereo data acquisition from a constellation with rapid re-visit times and an automated system for generating DSMs, something that is not currently viable.

“Video from Space” could change this. Multiple frames from a video sequence can be used to derive accurate DSMs –through photogrammetry. Earth-i’s new Vivid-i constellation, with revisit times of up to 4 times a day, will be able to generate accurate DSMs several times a day. In disaster hit cities this information could be an invaluable tool for identifying damage and planning response. Even without high level processing, timely video feeds could show traffic movement and other local ground activity vital for disaster management. The human activity level, visible in a time based video sequence will help immensely with the response activity.

Earth-i is looking to maximise the utilisation of EO data. We are redefining the limits of what Earth Observation can do with new technology and innovation. Our work will provide unique solutions to the global challenges we face today. To have an exclusive ‘first look’ preview to the first video imagery captured by VividX2, please enter your email address below.

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Watch the latest Earth-i video blog as members of our technology team discuss how we’re delivering brand new types of data that provide full motion 4D context to space-derived Earth Observation intelligence. With detailed analytics and insights capabilities, innovators, policy makers, and geospatial professionals can make more effective decisions, more rapidly.

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Border Areas are at the centre of today’s geopolitical challenges and geopolitical developments. Terrorism, illegal immigration and trafficking, proximity to crisis zones, EEZ monitoring and the need for in-depth ISR are some of their current defining characteristics. Also, the multi-faceted threats generated within border geographic neighbourhood are ever-changing and blended. In the last five years, we have seen major crises in neighbouring regions, especially in the Middle East and Africa, that bring wider European implications and the likelihood of unpredictable developments, which necessitate an early warning and constant monitoring system.

Currently, border area control systems are structured in networks of base stations (pylons) carrying radar and EO/IR sensors. These pylons are based in suitable selected locations, which offer a line of sight (LOS) surveillance to the Area of Interest (AOI). These systems are commonly supported, especially in terrestrial cases, with special fences or ditches adding a considerable amount of investment, labour and time for their design, construction, operation and maintenance over several years. They are mainly effective in covering tactical requirements or short-range surveillance up to 20km and they are vulnerable to external threats if they are not guarded or secured on a 24/7, 365 basis. The morphology of ground, the type of land-cover and the infrastructure available to the last mile of the sensor is highly influential in the design and the total number of the ground sensors required. The proximity to areas of political instability in the greater region will determine the need for an augmented solution with complementary components that are reliable and deter multiple threats.

The economics behind a border security system must include the securing of a country’s borders for national security and simultaneously an economic imperative to protect the nation’s trading interests, both EEZ protection and strategic deterrence. The ideal system must provide a proactive surveillance – intelligence driven, offering monitoring and surveillance beyond the borders, in depth and persistent. It must have a dual-use character covering Civil security: illegal immigration, environmental disasters, trafficking, fire-fighting; and Military security: intel, early warning and advance functionality. It must focus its assets on anticipated “hot spots” and provide early preparation for targeted asset mobilisation, early detection and early interdiction beyond the horizon. It must be of high fidelity and allow sharable and actionable intelligence. It must support regional and international collaboration and enable the sharing of timely, accurate and decisive intelligence among multi-national agencies.

All such fixed border infrastructure comes at a high cost and is not always as cost-effective as proponents of such physical infrastructure would like us to believe. Given the squeeze on most government budgets the imperative now is to find less asset-based and more data-driven technology solutions to the ever-growing challenge of maintaining border security. So what role might satellite-based sensors play in the future?

Earth-i is building the Vivid-i Constellation, a unique European space-based surveillance system comprised of a constellation of many small satellites offering dynamic monitoring based, for the first time, on full-colour High Definition video and unprecedented daily revisit to any AOI. Vivid-i can be considered as the space-based multi-purpose solution complementing ground-based border control systems and augmenting their capabilities for improved proactive intelligence, pre-frontier and frontier control, terrestrial and maritime situational awareness, early warning, surveillance and monitoring, and environmental security.
The Vivid-i Constellation will be comprised of a minimum 15 small, but highly capable optical satellites, deployed in various orbital planes. Beyond this initial scale, it will grow in batches of 5 satellites depending on customer demand, This will provide un-paralleled space-imaging capabilities offering daily multiple revisits, data fusion potential, high collection capacity and availability, combined with an operationally flexible service. Built on data-as-a-service principles, Vivid-i will provide autonomous and secure real-time satellite tasking and rapid data downlink to allow customers C2 facilities to perform a range of data processing, analyses and integrations to better serve defence, civil, and commercial users.

In summary, Vivid-i is a world-class information system enhancing customer national security and its role in ensuring regional stability. It is expected to support European Security and Space Policy and assist border control projects that demand the use of the high spatial and temporal resolution with a reliable flow of geospatial data on a 24/7 365 basis, on and beyond the borders.

VITO Remote Sensing distributes processed Earth Observation data to users worldwide. In this blog, we are giving the word to Action Contre La Faim (ACF) describing their use of PROBA-V data for monitoring West-African cattle herders. Their work is an interesting example of how global Earth observation data can be used to support pastoralists locally.

MONITORING WEST-AFRICAN CATTLE HERDERS

Action Contre la Faim (ACF) is an international humanitarian aid organization with operations in 50 countries with a focus on Food Security, Nutrition, Water/Sanitation and Advocacy. Since 2007, the organisation has been monitoring the resources of cattle herders (pastoralists) in West Africa. The food security of this population is highly dependent on livelihood shocks and the loss of their herds. With natural biomass as the only source of forage for their cattle, these pastoralists are particularly vulnerable to drought.

These herders represent 30% of the population in Sahelian Countries, contribute up to 40% of agricultural GDP and handle between 70 and 90% of the Sahelian livestock. These herds are a critical source of income and protein for local populations. When droughts hit, the pastoralists are often the first to be affected, but the impact is quickly spread to the rest of the population.

FROM EO DATA TO HUMANITARIAN RESPONSE

ACF uses “PROBA-V“http://proba-v.vgt.vito.be/en: based products, provided by the Copernicus Global Land Service, such as NDVI, Dry Matter Productivity (DMP) and Small Water Bodies (SWB). These images serve as input for added value products generated by data integration software developed by ACF. The “BioGenerator” uses PROBA-V’s DMP and NDVI to create annual biomass data. Surface water datasets on the other hand are created with another tool called, “HydroGenerator”.

Thanks to the annual biomass data we can isolate areas of drought after the Sahelian rainy season (July-September). This means that we have 6 months to prepare for the places that will be the most affected by drought. Between the period of October-March, natural resources produced by the rainy season (pasture and water) will dry up and cattle herds will move to find these resources. If we know ahead of time which areas are going to be the worst hit, we can prepare humanitarian response and assist the herders for various purposes such as:

- veterinary care
- distributions of cash or animal feed
- destocking and restocking of herds
- water provision
- …

SPREADING THE INFORMATION

The EO data is made into maps and reports that are published on our web portal, www.sigsahel.info. The data is shared with UN Agencies, NGOs, Government actors and herder organisations to help plan interventions. The new and interactive portal provides EO data (PROBA-V, SPOT-VEGETATION, … ) in interactive format alongside field data showing the concentrations of cattle and results of field surveys. We also publish the data in raster and tabular formats on the Humanitarian Data Exchange. make sure the data, maps and information is consumable for the end users, we provide trainings on how to interpret and use the data. For example, the National Early Warning System of Mali has appropriated our methods to make their own biomass analyses every year.

BENEFITS OF EO DATA

The importance of this data is that it allows us to quickly assess a situation and make important predictions. Without it, we would have to rely on field measurements, which are too costly and time-consuming to do regularly across all of West Africa. As a result, ACF and its partners have access to fast information on Biomass and Water that allow us to target areas for humanitarian intervention. We have begun work with partners to provide this information directly to the herders. To serve the cattle herders in Northern Mail, we (ACF together with SNV, Orange, Hoefsloot Spatial Solutions, Project Concern International, Tassaght (A Malian Pastoralist Organisation) and the Malian Government) set up a call center. Herders can easily contact the center to receive information on the biomass and water for an area of interest. This helps herders plan their movements. Our goal is to go beyond institutional work with humanitarian actors and democratize this data for herders all across the region.

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Today we travel back in time, to March 24th 1998. It is exactly 20 years ago that the first VEGETATION instrument was launched on board the SPOT 4 satellite.

20 years may go unnoticed in the evolution of the Earth, but leaves its footprint in the lifespan of a man. Not only because of the immense technological progress that was made, but even more for the growing importance remote sensing and geo-information play nowadays in our daily life.

Dominant land cover from the Global Land Cover for the year 2000 (GLC2000, Bartholome & Belward, 2005)

SDGS OF THE SEVENTIES

Growing awareness of the interdependence of environment, economy and social well-being resulted in 1972 in the Stockholm Conference, the first UN Conference calling upon all countries to manage the environment for the benefit of present and future generations. In 1992 the Rio Declaration and Agenda 21 followed, and later in 2000, The Millennium Declaration on Environment and Development with its Millennium Development Goals.

The goal to monitor our environment and safeguard our livelihoods stressed the need for a European long-term commitment of space-based environmental monitoring services, as put forward by the Baveno Manifesto in 1998, the starting point of the GMES initiative, in 2012 renamed to the famous COPERNICUS programme.

24 MARCH 1998! THE BIRTH OF GLOBAL VEGETATION MONITORING

Our great and ambitious adventure started in 1997, a year prior to the successful launch, when the VITO Centre for Remote Sensing and Atmospheric processes (now called VITO Remote Sensing) signed its first CTIV contract (Centre de Traitement des Images de SPOT Végétation) with OSTC (now BELSPO), as part of the SPOT VEGETATION programme financed by the European Commission, France, Belgium, Sweden and Italy.

The VEGETATION programme was setup to ensure daily global vegetation monitoring by imaging our Earth’s surface with a spatial resolution of 1 km. The programme was very ambitious, demonstrating European operational leadership in delivering high quality Earth observation products to end users in less than 24 hours after image acquisition.
With 10 motived image processing experts we were ready to be a part of this challenging mission, busy controlling the production and distribution entities and operating the central image processing and archiving center, working in close collaboration with our Swedish and French colleagues.

Since 1998 we’ve grown to a group of more than 150 professionals, working in the remote sensing and environmental monitoring research units. Satellite image processing in all its forms is still a core business, but in the meantime it is also complemented with new technological research in the field of airborne data and the development of innovative information products and services.

A JOURNEY TOWARDS FULL, FREE AND OPEN DATA

To support the European GMES initiative, the VEGETATION programme implemented a free data policy in 2001, promoting the free distribution of its premium product, the 10 day synthesis VGT-S10. With its VEGA 2000 project, the CTIV processed global data acquired by the VEGETATION instrument for the year 2000. This was distributed for free to over 30 research teams across the world. But there was no cloud storage in 2000! Shipment in those days was still done via DVD and SDLT as per request. The general objective of the VEGA 2000 data set was to generate a harmonized land cover database over the entire globe for the year 2000, the year being a reference year for environmental assessment in relation to the United Nations’ international conventions. Under guidance of the EC Joint Research Centre, the VEGA 2000 images finally resulted in the Global Land Cover 2000 data set.

This free and open data policy was later on fully incorporated in EC directives “Communication on open data” (2011) and “re-use of public sector information” (2013).

Over the years, VEGETATION satellite data has been used in a wide variety of research projects to monitor the global land surface (e.g. Geoland, BOSS4GMES), the carbon cycle and forests (GlobCarbon, GSE Forest Monitoring) and agriculture and food security (Global Monitoring for Food Security).

Benefiting from the results of several research projects, and responding to the growing economic and societal needs, the Earth observation data and derived information products found their way into operational services for the European Commission’s Joint Research Centre, notably the Global component of the Copernicus Land Service, Copernicus Climate Change Service, the Monitoring of Agriculture with Remote Sensing or MARS.
But also abroad, for instance by United Nations and the U.S. Department of Agriculture (USDA). Effectively serving thousands, around the world.

That’s why we love what we do. Offering useful tools and consumable information to assist end users in making evidence-based decisions for sustainable development.

LOOKING BACK TO LOOK AHEAD

On May 7, 2013 ESA’s small satellite PROBA-V was launched. With its 1-km, 300-m and 100-m resolutions, this instrument is the successor of the SPOT VEGETATION 1 and 2 instruments, carefully continuing the global vegetation daily time series for more than 20 years now. PROBA-V was designed as the gap filler between SPOT VEGETATION and the Sentinel satellites of ESA, and as the precursor of the SLSTR instrument on SENTINEL-3.

The CTIV catalogue of the late 90ties has now evolved into a modern multi-mission VITO Product Distribution Portal , giving users free access to several data products a.o. SPOT-VEGETATION, ENVISAT-Meris, PROBA-V, AVHRR, Sentinel data.

Via the online product distribution portal, users can:
- consult the data via an interactive Geo Viewer or Time Series Viewer
- make their own composites with the N-daily Compositor
- request a Virtual Machine to create their own virtual research environment and work on the data with a powerful set of tools and libraries
- develop and debug test applications

Nanosatellites and CubeSats, drones, big data, artificial intelligence and machine learning. Some of the technological innovations rushing by and transforming the geospatial information market. We are now in the middle of the transition from mass production of data and images to mass customization, with web information services, personalized products and user-centric solutions.

WatchIT grow is an online platform which combines several types of data (e.g. satellite, drone, weather and soil data) to monitor and increase potato yields in a sustainable way.

Together with colleagues from universities, the industry and relevant public bodies, we concentrate on developing new applications for our clients and try out new business models. We have extended our playing field from the national and European scene to the international and worldwide market.

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