at Paris Space Week

Gisaia will be at Paris Space Week on March 14 - 15, ready to meet and show you how ARLAS Exploration and ARLAS-EO help accelerate Earth observation data exploration and uptake.

February 03, 2022


Unlike most sectors, Earth Observation sector players do not have many international events that unite stakeholders to explore industry trends. Paris Space Week is one of the few events that bring together many stakeholders from the spatial industry: upstream and downstream markets. Here, participants get to showcase and learn about the latest innovations besides discussing the future of the industry.

This year, Paris Space Week is expecting over 1000 attendees drawn from diverse countries and backgrounds; government, academia, and the private sector. The event presents diverse opportunities for attendees to network through different activities set in their agenda. Gisaïa uses this opportunity to keep up with the industry trends and meet with potential users of our solutions for geo big data analytics.

The Earth observation industry is quickly growing in significance and in size. This is partly due to the increase in new sensors and constellations deployed. They are also of a wide variety and when coupled with innovation in the ground segment, they generate data that is processed and can be distributed widely. The application of artificial intelligence to derive richer analytics and support change detection capabilities helps to reduce the “time to market” from academia to society, for evidence-based decision making. 

EO data’s significance in drawing valuable intelligence to benefit the society is without question. But, the increased data generation is not matched in consumption. That is why Gisaia provides solutions that helps EO sector players to quickly put their data in the hands of those who need it. We will be at the Paris Space Week, 2022 on March 14 -15 where we look forward to interacting, learning and sharing how the Earth observation downstream market growth can be quickly accelerated.

Showcase all available EO data in one place with ARLAS-EO

If you are an Earth Observation provider, you most probably get your products and data from multiple sources. Sometimes the data comes from in-house constellations plus secondary suppliers. Your users may need to access this data from the different sources for a single project. Providing this data on a single platform not only facilitates smooth exploration of the data, it also ensures quick retrieval.   

ARLAS-EO allows you to showcase all your EO data in one place. With the multi-collection feature, users can easily select the data source and even more interesting, select multiple sources to view the available data all at once. Also, for EO data providers, this helps centralise maintenance, support and even supply, eventually limiting costs linked to operations

Now more than ever, data platforms need to be intuitive and responsive besides being informative.

Data-driven evidence with ARLAS Exploration

Gisaia also provides ARLAS-Explo upon which ARLAS-EO  is built. It facilitates geospatial intelligence. Built upon big data frameworks, it scales with your data eliminating the challenges posed by a growing data archive. Arlas-Explo allows EO data users to get deeper insights from their collection, supporting data-driven evidence. You can carry out analytics on various datasets at the same time by easily cross-linking them. This helps save on the time it takes to move from one view to the next or one platform to another. 

ARLAS-Explo is versatile as demonstrated in various applications leveraging Earth observation data: telecommunication, fleet management, insurance, maritime intelligence, among other change detection subjects. Whether you are working on sustainable management of resources, security, or business optimisation linked to Earth observation, our solutions built upon the ARLAS stack are an important brick to support data-driven decision making.

Come meet us at Paris Space Week, booth number S8 where our team will be waiting to hear about your mission and give you live demonstrations of both ARLAS-EO and ARLAS-Explo.

Contact us to book a demo in advance

ITS Congress in hamburg


October 04, 2021


Globally, property pricing has always been tied to essential amenities. As agents often say “Location. Location. Location.” Up in the list of coveted ‘should haves’ is ‘public transport nearest to me’. The ‘near me’ phenomena means that people are increasingly demanding easily accessible efficient services from their mass transit providers. 

Google trends record of the searches with the term ‘near me’ between 2004-2021

Even with COVID 19’s triggered migration out of city centres (where public transportation is often better connected) to suburbs, properties closer to public transportation still top buyers’ and renters’ requirements. This means that public transport has a future way beyond COVID 19. Current data already shows positive heat maps around mass transit areas. Decision makers are of course interested in the trend as they seek to optimise their offer. The answers they know, lie in analysing past activities against new trends. Historical and real data merged into one platform can start drawing a clear picture.

OPTIMISING TRANSPORTATION SERVICES WITH DATA is designed to help authorities and operators to have a global view of their offer and make necessary changes backed by data. As the near me trend continues, a great combination of key user indicators; frequency, accessibility and reliability offers services that ensures riders get as close as possible to their destination, and in the least amount of time. These indicators are already set in But that’s not all, there is room to add as many datasets as required to expand the analytics for even more nuanced analysis.’

Isochrons calculations of the Toulouse mass transit network showing how much time it takes to go from one point to diverse destinations.


The need for better systems often draws the mobility sector together to explore innovative ways to move the industry forward. One such event is the  ITS (Intelligent Transport Systems) Congress which is one of the biggest occasions that brings together the mobility industry to discuss smart mobility and the digitalisation of transport. The event takes either as a regional or global assembly. This year, Hamburg will be hosting the world congress from the 11th to the 15th of October. It is a great platform to promote innovative solutions for sustainable mobility. The participants, who are also drawn from the mass transit sector, are invited to ‘Experience Future Mobility Now’. The event offers various activities; exhibitions, academic track, plenary sessions, thematic conferences and live demonstrations.

ITS Congress Hamburg  2021 already has over 300 exhibitors confirmed, and expects over 15,000 visitors invested in the transit industry from all over the world, including public transport authorities and operators who will be seeking solutions for smarter, cleaner and greener mobility. 

Gisaïa is part of the Business France entourage. We will be happy to receive congress participants at the French Pavilion to demonstrate our solutions for data-backed decisions for public transportation and fleet management analytics

You can book a live demo with us during your visit by sending an email to: .

Gisaia wins EU Horizon2020 UFO Challenge with ARLAS for geospatial data - AIS data. European Union Horizon2020 UFO Challenge 2021 Winners

FAIR WINS UFO 2021 Challenge

EUROPE UNION Horizon 2020 UFO Challenge

 06 July 2021, Media Release


FAIR Consortium,

Media brief, 06 July 2021

Gisaïa, Skyline Partners, e-Odyn are excited to announce that their consortium won a grant by the European Union’s Horizon 2020 research and innovation programme coordinated by Aerospace Valley. The award was through a tendering process that saw the consortium emerge with top scores for their proposal responding to “Emerging indUstries new value chains boosted by small Flying Objects – UFO” 

The UFO project seeks to develop cross-sectoral industrial value-chains between selected emerging industries, to stimulate new products and services from small and medium enterprises. 

Mr Thaddé Bouchard, the UFO Coordinator at Aerospace Valley shares what got FAIR on the winning list.

Based on a high quality application, the project FAIR presents for UFO a great opportunity to combine new market opportunities with climate change tackling. The parametric products proposed by FAIR, leveraging on advanced scientific and insurance models, represent a highly innovative approach for ship insurance. FAIR proposes a promising solution in contrast with traditional practices of the insurance industry in the marine sector demonstrating how satellite data can foster the value chains of emerging industries.”

The award will allow the consortium to bring together their aggregated technologies to develop and test a parametric index insurance product for the marine sector. Mr Bouchard notes that FAIR put together the right actors to successfully execute the project.

The grant runs between May 2021 – May 2022. After the one year development period, the consortium aims to put a fully transparent risk transfer product that protects ship owners while also benefiting the environment . This will be achieved through full automatiomation of risk calculations based on Earth observation data to cover overlooked aspects of operations.

The consortium, which is made up of marine data specialists, geo-big data analytics experts and parametrics insurance specialists, believes that this project will open up a new revenue stream for Small Flying Objects (SFOs), in high value marine insurance . 

For more details contact


UFO’s media release from published here on their website.


About the consortium:

eOdyn’s solutions rely on its Omni-Situ ocean dynamics (wind, wave, surface current) measurement technology. It delivers high temporal and spatial resolution, in real-time with virtually global offshore coverage, thanks to machine learning algorithms mining into marine traffic data.

Gisaïa brings seven years of geo-big data analytics expertise, and a robust geo-analytics solution, “ARLAS”. The ARLASframework has been tried and tested in diverse use cases for geospatial intelligence, especially in Earth observation data value creation. The ARLASframework already powers INSDEXⓇ, an index insurance technology platform produced and run by Skyline Partners.

Skyline Partner is a UK Insurtech company, specialised in index-based parametric insurance. Our solutions are data & technology-driven and underwritten by top tier international re/insurers with superior ratings. Skyline has developed its own index insurance technology platform INSDEX® and aggregates high-value data from multiple sources.

Time spent in traffic congestion in Europe



January 19, 2021

What can public transportation authorities and operators do to get more people using public transport? Is there a solution that brings; population data, public transportation data and residents activity data together to help public transport decision-makers? Yes, we propose, a geo-analytic SaaS. _ Toulouse Metropole tram and metro lines

Toulouse tram and metro lines displayed on, composed from Tisséo’s GTFS data.

But first, let us look at the challenges in public transportation data analysis.

A developed country is not a place where the poor have cars. It’s where the rich use public transportation.” 

This statement by Enrique Penalosa can’t be truer. In other words, using public transport should be a choice and not a need. 

A recent study by the European Commission on ‘quality of life’ in cities surveyed nearly 60,000 European city residents with a section on how public transportation affected residents. It revealed that: 

  • Men, people with a higher income and families were less likely to use public transport.
  • Retired people, younger folks – between 15 and 24 years old, and those with only secondary education – frequently used public transportation.
  • Big-city residents like London, Prague and Paris were more likely to use public transportation than their counterparts in smaller cities.
public transportation use by working status

But why would cities experience less public transportation uptake when data indicates that with each passing decade, cities have become even denser?  And what would it take to move private transport users to public transportation? One of the many answers is; intermodalism.

Intermodalism not only gives users multiple options to reach their destination, but it also allows public transportation authority to quickly adapt services to growing needs. Creating transfer zones where frequent transport lines intersect. This allows people to reach more destinations faster.

In the European Commission study, it was no surprise to find that there was a strong correlation between efficient public transport and happy residents.

Public transport satisfaction by European residents

What was surprising was that the cost of public transportation did not have a significant impact on resident’s happiness.

Residents want efficient and reliable transportation.

To promise these, public transportation authorities and operators mix up different modes of travel, ensuring that travellers get the best available option for each stretch of the journey. 

Choosing the right mode highly depends on staying connected to the ever-changing needs of the users. This means constantly looking at data to offer seamless mobility.

But if there is an industry that churns out volumes of data every day, then public transportation would definitely be amongst the top. Big data presents a lot of opportunities which of course come coupled with challenges. Challenges that mostly come from data collection that precedes its uses and is often stored in different silos. 

Public transportation authorities and Operators now find themselves looking at multiple lakes of data, swimming with diverse dimensions, which then leads to time wasted in decision making. And, sometimes the decisions, arrive when the original scenarios have changed. 

Thanks to the advancement in location intelligence, going back in time and referencing volumes of historical data, merging data in silos and aligning it is now possible. presents public transportation authorities and operators with a robust solution that scales with their data. They are able to easily and quickly dive into their aligned data for a unique analytical perspective of their entire network.

Toulouse GTFS data on

Visual display of ‘Segments speed’ on a network’s lines: bus, metro and tram.

Not only, that, but public transportation data analytics can also now be plugged into the cities’ population data and residents’ activities, so that authorities and operators can really respond to present events and projected trends. 

Population data mapped on

Population density data created and visualised in, a geo-analytic platform for public transportation that can facilitate all this.

Bordeaux Métropole transport network on, composed from Keolis GTFS data. which is designed for public transportation authorities and operators gives decision-makers the opportunity to make timely data-backed decisions, to meet residents’ needs and desires of efficient public transportation. 

Aligning data from all modes with other dimensions would save lots of time. But the ability to quickly visualise it and stay ahead of potential roadblocks would result in happier residents. 

These residents only want:

  • efficiency – are public transportation services reliable?
  • accessibility – are the services where people want them?
  • comfort – do they meet people’s needs?

Another European Union analysis on transport and mobility found that in 2017, Europe residents spent an average of 29 hours annually in traffic congestion. UK residents were the most unfortunate with an average of about 46 hours annually, up by five hours in just two years where they spent an average of 41 hours annually in 2015. France’s residents, while not recording a significant increase, also went up from 29 hours in 2015 to 30 hours annually in 2017.

Time spent in traffic congestion in Europe

Most travellers just want to go from one place to another. They want to take the shortest time getting there. They are willing to pay a fair price for it. Including isochrons in public transportation analysis helps decision-makers to provide multiple short routes to diverse destinations.

Isochrons calculations for public transportation
Isochrons in minutes

Isochrons’ mapping of travel time  in minutes, from one point to different destinations.

Travellers choose the services that bring them the closest to their destination for either the lowest cost or in the least amount of time. In the era of smart cities, residents expect their public transportation services to be even more effective, dependable and convenient.

Setting up public transportation services for thousands (let alone) millions of users cannot be easy. What with continuous changes in needs like; a new school in a neighbourhood, a shopping mall or even unpredicted global events like COVID-19 where working and other social habits are affected. By analysing: 

  • ticket validation data
  • scheduled vs achieved trips
  • delays
  • population 
  • residents’ movement

Decision-makers can understand residents’ past trends to respond to current events and even predict future needs.

Get in touch with us if you want to see’s application on your data. We are happy to organise a live demonstration and to help you meet your travellers’ diverse needs for public transportation.


If we understand it, we can fix it

July 27, 2020

4.2 million people die every year. 

That number of deaths is linked to outdoor air pollution as recorded by the World Health Organisation (WHO). When you include indoor pollution, the number goes up to 7 million people every year. 

While most of these deaths are in developing and middle-income countries, major cities in developed countries still record higher than recommended levels of substances linked to dangerous pollutants.

So, what are these pollutants and how do they affect people?

The OpenAQ database that is used in ARLAS’s – also an open-source framework- demonstration, collects data from 12,000 stations spread across 93 countries. The stations monitored by OpenAQ record diverse air pollutants; NO₂, SO₂, NO₃, BC, PM₂.₅, PM₁₀, and CO₂.

NO₂, Nitrogen Dioxide, is produced in abnormal quantities by human activities like burning of fuel, motor vehicle emissions, and power plants. It is toxic and easy to inhale, known to trigger asthma.

The PM₂.₅ is also a killer pollutant. Simply referred to as ‘Particulate Matter’, it is composed of solid particles and liquid droplets. It is highly inhalable causing many health problems, especially linked to the heart.

PM₁₀ is four times bigger than PM₂.₅ but just as dangerous because it can also be easily inhaled.

The trouble with air pollution is that it affects even those who didn’t create it. The big question would then be, how to trace the danger in the air and prevent exposure to these deadly agents? While many answers speak to long-term strategies, the immediate response involves aggressive monitoring and warning systems that give individuals the ability to make decisions that protect them. 

Having reliable air pollution monitoring tools like ARLAS ensures that everyone in the decision-making chain is well equipped to act.



The world ground to a halt and immediately opened the skies – quite literary in some locations – to the possibilities of tackling air pollution. The near-global lockdown courtesy of COVID-19 made it apparent for ‘pollution effects believers and non-believers’, that the Earth had been choking.

It was no surprise to see pollution levels go down as mobility reduced and non-essential factories’ tracks go on a standstill, cutting pollutants by significant numbers. 

China for example is on record as the highest contributor to CO₂ levels globally. During their lockdown, their CO₂ emissions went down by about 25%, equivalent to 150,000 tons. 

To put that into perspective, that is nearly five times what  Angola emits yearly.

We tested the theory of human contribution to air pollution. Using ARLAS, we compared March – April 2019, March – April 2020, and June 2020 data. This period represents, before and during COVID-19 for the same periods and just after the lockdown was lifted in some countries.

Focusing on provinces around Beijing, ARLAS shows  PM₂.₅ levels reducing by about 30% over the period when the lockdown is ongoing. It is clear from this demonstration that reduced human activity also reduced the volume of pollutants released in the air. There is also a significant reduction in PM₁₀ levels. 

Some activities that are traditionally low contributors to pollution like home heating and data centres increased their pollution contribution as human activities migrated home and online. This kept some pollutants volumes high.



On ARLAS, a dive down to specific stations reveals a more localized picture. 

Based on the dangers associated with PM₂.₅ and PM₁₀, the WHO advises that exposure to these two agents should be kept below 20μg/m3 for  PM₁₀  and  10 μg/m3  for PM₂.₅. Some locations record levels that are over five times higher than the recommended values. 

Residents of New Delhi benefited from a 56% drop in PM₂.₅ emissions between 26 April – 7 May, 2020, compared to the same period in 2019.

But, it was still, way above the recommended threshold.

Comparision of the PM₂.₅ emissions over New Dehli city between 26 April – 7 May 2019 (mean of 95.8μg/m3)  and 26 April – 7 May 2020 (mean of 43.4 μg/m3)

NO₂ emissions also have an adverse effect on health especially when higher than 100μg/m3 on an hourly average. Between January and August 2019, Paris experienced levels above 100μg/m3 85 times.  In 2020, it was cut down 21 times to only 4 measures of similar quantities that were recorded at the end of June, just after the lockdown.

NO2_New Delhi
Zoom on the legend Over the City of Paris :
Above: Distribution of numbers of measures of quantities of NO₂ emissions. Here, you see a selection of emissions above 100μg/m3.
Below: Distribution of the average of NO₂ emissions over time (In the 1st semester of 2019, there are 13 peaks. For the same period in 2020, only 1 peak). 


Strict monitoring of air pollution is a growing phenomenon with more stations being set up to facilitate this. The European Union region has stringent policies on pollution which have resulted in lower deaths linked to air pollution. France for instance has reduced air pollution linked deaths by half in only 25 years.

Pollution data gives the ability to analyse it and fix it. 

An ecosystem of monitoring and prevention would ideally save many lives: different players acting from different angles, easily and quickly guided by data. 

To start, policymakers like scientists and regulators, require needlepoint precision to determine their actions.

Travel companies that issue alerts on destinations based on pollution levels could help many at-risk groups to make informed choices – for example, people with preexisting pulmonary conditions. Could this lead to cheaper insurance premiums for travellers to/during low pollution zones and periods? Or even better, saving lives.

Individuals may also want to proactively stay connected to pollution information within their localities or elsewhere they intend to visit. Access to mobile applications that have credible up to date data would put pollution-fighting power in their hands like; where to find a job or buy a home amongst other human habitation decisions.

WHO is keen to have more stations set-up because the more air pollution data is collected, the clearer the picture. The OpenAQ currently collects up to 588 million air quality measurements. This is big data that ARLAS can quickly and easily process for Air pollution analysis.



The irony of the COVID-19 pandemic is that within the initial limited time of confinement – mid March – end of May 2020 – more lives may have been saved from the direct effects of exposure to pollution than were lost due to COVID-19 during the same period. 

Scientists are already linking higher critical COVID-19 impact amongst people who were previously exposed to high levels of pollution.

All efforts towards air pollution monitoring are expected to help reduce premature deaths linked to toxic air. If you are working in monitoring, policy setting or warning mechanisms around pollution, check out our demo to get a glimpse of Arlas at work on OpenAQ pollution data.

Get in touch with us at if you would like to discuss tools and services to get you acting faster.