Medio ambiente

To achieve its environmental sustainability goals, Europe needs accurate, accessible and up-to-date information that enables evidence-based decision-making. The Green Deal Data Space (GDDS) will facilitate this transformation by integrating diverse data sources into a common, interoperable and open digital infrastructure.

In Europe, work is being done on its development through various projects, which have made it possible to obtain recommendations and good practices for its implementation. Discover them in this article!

What is the Green Deal Data Space?

The Green Deal Data Space (GDDS) is an initiative of the European Commission to create a digital ecosystem that brings together data from multiple sectors. It aims to support and accelerate the objectives of the Green Deal: the European Union's roadmap for a sustainable, climate-neutral and fair economy. The pillars of the Green Deal include:

• An energy transition that reduces emissions and improves efficiency.
• The promotion of the circular economy, promoting the recycling, reuse and repair of products to minimise waste.
• The promotion of more sustainable agricultural practices.
• Restoring nature and biodiversity, protecting natural habitats and reducing air, water and soil pollution.
• The guarantee of social justice, through a transition that makes it easier for no country or community to be left behind.

Through this comprehensive strategy, the EU aims to become the world's first competitive and resource-efficient economy, achieving net-zero greenhouse gas emissions by 2050. The Green Deal Data Space is positioned as a key tool to achieve these objectives. Integrated into the European Data Strategy, data spaces are digital environments that enable the reliable exchange of data, while maintaining sovereignty and ensuring trust and security under a set of mutually agreed rules.

In this specific case, the GDDS will integrate valuable data on biodiversity, zero pollution, circular economy, climate change, forest services, smart mobility and environmental compliance. This data will be easy to locate, interoperable, accessible and reusable under the FAIR (Findability, Accessibility, Interoperability, Reusability) principles.

The GDDS will be implemented through the SAGE  (Dataspace for a Green and Sustainable Europe) project and will be based on the results of the GREAT (Governance of Responsible Innovation) initiative.

A report with recommendations for the GDDS

How we saw in a previous article, four pioneering projects are laying the foundations for this ecosystem: AD4GD, B-Cubed, FAIRiCUBE and USAGE.  These projects, funded under the HORIZON call, have analysed and documented for several years the requirements necessary to ensure that the GDDS follows the FAIR principles. As a result of this work, the report "Policy Brief: Unlocking The Full Potential Of The Green Deal Data Space”. It is a set of recommendations that seek to serve as a guide to the successful implementation of the Green Deal Data Space. 

The report highlights five major areas in which the challenges of GDDS construction are concentrated: 

1. Data harmonization 

Environmental data is heterogeneous, as it comes from different sources: satellites, sensors, weather stations, biodiversity registers, private companies, research institutes, etc. Each provider uses its own formats, scales, and methodologies. This causes incompatibilities that make it difficult to compare and combine data. To fix this, it is essential to:

• Adopt existing international standards and vocabularies, such as INSPIRE, that span multiple subject areas.
• Avoid proprietary formats, prioritizing those that are open and well documented.
• Invest in tools that allow data to be easily transformed from one format to another.

2. Semantic interoperability

Ensuring semantic interoperability is crucial so that data can be understood and reused across different contexts and disciplines, which is critical when sharing data between communities as diverse as those participating in the Green Deal objectives. In addition, the Data Act requires participants in data spaces to provide machine-readable descriptions of datasets, thus ensuring their location, access, and reuse. In addition, it requires that the vocabularies, taxonomies and lists of codes used be documented in a public and coherent manner. To achieve this, it is necessary to:

• Use  linked data and metadata that offer clear and shared concepts, through vocabularies, ontologies and standards such as those developed by the OGC or ISO standards.
• Use existing standards to organize and describe data and only create new extensions when really necessary.
• Improve the already accepted international vocabularies, giving them more precision and taking advantage of the fact that they are already widely used by scientific communities.

3. Metadata and data curation

Data only reaches its maximum value if it is accompanied by clear metadata explaining its origin, quality, restrictions on use and access conditions. However, poor metadata management remains a major barrier. In many cases, metadata is non-existent, incomplete, or poorly structured, and is often lost when translated between non-interoperable standards. To improve this situation, it is necessary to:

• Extend existing metadata standards to include critical elements such as observations, measurements, source traceability, etc.
• Foster interoperability between metadata standards in use, through mapping and transformation tools that respond to both commercial and open data needs.
• Recognize and finance the creation and maintenance of metadata in European projects, incorporating the obligation to generate a standardized catalogue from the outset in data management plans.

4. Data Exchange and Federated Provisioning

The GDDS does not only seek to centralize all the information in a single repository, but also to allow multiple actors to share data in a federated and secure way. Therefore, it is necessary to strike a balance between open access and the protection of rights and privacy. This requires:

• Adopt and promote open and easy-to-use technologies that allow the integration between open and protected data, complying with the General Data Protection Regulation (GDPR).
• Ensure the integration of various APIs used by data providers and user communities, accompanied by clear demonstrators and guidelines. However, the use of standardized APIs  needs to be promoted to facilitate a smoother implementation, such as OGC (Open Geospatial Consortium) APIs for geospatial assets.
• Offer clear specification and conversion tools to enable interoperability between APIs and data formats.

In parallel to the development of the Eclipse Dataspace Connectors  (an open-source technology to facilitate the creation of data spaces), it is proposed to explore alternatives such as blockchain catalogs  or digital certificates, following examples such as the FACTS (Federated Agile Collaborative Trusted System).

5. Inclusive and sustainable governance

The success of the GDDS will depend on establishing a robust governance framework that ensures transparency, participation, and long-term sustainability. It is not only about technical standards, but also about fair and representative rules. To make progress in this regard, it is key to:

• Use only European clouds to ensure data sovereignty, strengthen security and comply with EU regulations, something that is especially important in the face of today's global challenges.
• Integrating open platforms such as Copernicus, the European Data Portal and INSPIRE into the GDDS strengthens interoperability and facilitates access to public data. In this regard, it is necessary to design effective strategies to attract open data providers and prevent GDDS from becoming a commercial or restricted environment.
• Mandating data in publicly funded academic journals increases its visibility, and supporting standardization initiatives strengthens the visibility of data and ensures its long-term maintenance.
• Providing comprehensive training and promoting cross-use of harmonization tools prevents the creation of new data silos and improves cross-domain collaboration.

The following image summarizes the relationship between these blocks: 

Conclusion

All these recommendations have an impact on a central idea: building a Green Deal Data Space that complies with the FAIR principles is not only a technical issue, but also a strategic and ethical one. It requires cross-sector collaboration, political commitment, investment in capacities, and inclusive governance that ensures equity and sustainability. If Europe succeeds in consolidating this digital ecosystem, it will be better prepared to meet environmental challenges with informed, transparent and common good-oriented decisions.

Synthetic images are visual representations artificially generated by algorithms and computational techniques, rather than being captured directly from reality with cameras or sensors. They are produced from different methods, among which the antagonistic generative networks (Generative Adversarial NetworksGAN), the Dissemination models, and the 3D rendering techniques. All of them allow you to create images of realistic appearance that in many cases are indistinguishable from an authentic photograph.

When this concept is transferred to the field of Earth observation, we are talking about synthetic satellite images. These are not obtained from a space sensor that captures real electromagnetic radiation, but are generated digitally to simulate what a satellite would see from orbit. In other words, instead of directly reflecting the physical state of the terrain or atmosphere at a particular time, they are computational constructs capable of mimicking the appearance of a real satellite image.

The development of this type of image responds to practical needs. Artificial intelligence systems that process remote sensing data require very large and varied sets of images. Synthetic images allow, for example, to recreate areas of the Earth that are little observed, to simulate natural disasters – such as forest fires, floods or droughts – or to generate specific conditions that are difficult or expensive to capture in practice. In this way, they constitute a valuable resource for training detection and prediction algorithms in agriculture, emergency management, urban planning or environmental monitoring.

 

 

Its value is not limited to model training. Where high-resolution images do not exist – due to technical limitations, access restrictions or economic reasons – synthesis makes it possible to fill information gaps and facilitate preliminary studies. For example, researchers can work with approximate synthetic images to design risk models or simulations before actual data are available.

However, synthetic satellite imagery also poses significant risks. The possibility of generating very realistic scenes opens the door to manipulation and misinformation. In a geopolitical context, an image showing non-existent troops or destroyed infrastructure could influence strategic decisions or international public opinion. In the environmental field, manipulated images could be disseminated to exaggerate or minimize the impacts of phenomena such as deforestation or melting ice, with direct effects on policies and markets.

Therefore, it is convenient to differentiate between two very different uses. The first is use as a support, when synthetic images complement real images to train models or perform simulations. The second is use as a fake, when they are deliberately presented as authentic images in order to deceive. While the former uses drive innovation, the latter threatens trust in satellite data and poses an urgent challenge of authenticity and governance.

Risks of satellite imagery applied to Earth observation

Synthetic satellite imagery poses significant risks when used in place of images captured by real sensors. Below are examples that demonstrate this.

A new front of disinformation: "deepfake geography"

The term deepfake geography has already been consolidated in the academic and popular literature to describe fictitious satellite images, manipulated with AI, that appear authentic, but do not reflect any existing reality. Research from the University of Washington, led by Bo Zhao, used algorithms such as CycleGAN to modify images of real cities—for example, altering the appearance of Seattle with non-existent buildings or transforming Beijing into green areas—highlighting the potential to generate convincing false landscapes.

One OnGeo Intelligence (OGC) platform article stresses that these images are not purely theoretical, but real threats affecting national security, journalism and humanitarian work. For its part, the OGC warns that fabricated satellite imagery, AI-generated urban models, and synthetic road networks have already been observed, and that they pose real challenges to public and operational trust.

Strategic and policy implications

Satellite images are considered "impartial eyes" on the planet, used by governments, media and organizations. When these images are faked, their consequences can be severe:

• National security and defense: if false infrastructures are presented or real ones are hidden, strategic analyses can be diverted or mistaken military decisions can be induced.
• Disinformation in conflicts or humanitarian crises: An altered image showing fake fires, floods, or troop movements can alter the international response, aid flows, or citizens' perceptions, especially if it is spread through social media or media without verification.
• Manipulation of realistic images of places: not only the general images are at stake. Nguyen et al. (2024) showed that it is possible to generate highly realistic synthetic satellite images of very specific facilities such as nuclear plants.

Crisis of trust and erosion of truth

For decades, satellite imagery has been perceived as one of the most objective and reliable sources of information about our planet. They were the graphic evidence that made it possible to confirm environmental phenomena, follow armed conflicts or evaluate the impact of natural disasters. In many cases, these images were used as "unbiased evidence," difficult to manipulate, and easy to validate. However, the emergence of synthetic images generated by artificial intelligence has begun to call into question that almost unshakable trust.

Today, when a satellite image can be falsified with great realism, a profound risk arises: the erosion of truth and the emergence of a crisis of confidence in spatial data.

The breakdown of public trust

When citizens can no longer distinguish between a real image and a fabricated one, trust in information sources is broken. The consequence is twofold:

• Distrust of institutions: if false images of a fire, a catastrophe or a military deployment circulate and then turn out to be synthetic, citizens may also begin to doubt the authentic images published by space agencies or the media. This "wolf is coming" effect generates skepticism even in the face of legitimate evidence.
• Effect on journalism: traditional media, which have historically used satellite imagery as an unquestionable visual source, risk losing credibility if they publish doctored images without verification. At the same time, the abundance of fake images on social media erodes the ability to distinguish what is real and what is not.
• Deliberate confusion: in contexts of disinformation, the mere suspicion that an image may be false can already be enough to generate doubt and sow confusion, even if the original image is completely authentic.

The following is a summary of the possible cases of manipulation and risk in satellite images:

Ambit	Type of handling	Main risk	Documented example
Armed conflicts	Insertion or elimination of military infrastructures.	Strategic disinformation; erroneous military decisions; loss of credibility in international observation.	Alterations demonstrated in deepfake geography studies  where dummy roads, bridges or buildings were added to satellite images.
Climate change and the environment	Alteration of glaciers, deforestation or emissions.	Manipulation of environmental policies; delay in measures against climate change; denialism.	Studies have shown the ability to generate modified landscapes (forests in urban areas, changes in ice) by means of GANs.
Gestión de emergencias	Creation of non-existent disasters (fires, floods).	Misuse of resources in emergencies; chaos in evacuations; loss of trust in agencies.	Research has shown the ease of inserting smoke, fire or water into satellite images.
Mercados y seguros	Falsification of damage to infrastructure or crops.	Financial impact; massive fraud; complex legal litigation.	Potential use of fake images to exaggerate damage after disasters and claim compensation or insurance.
Derechos humanos y justicia internacional	Alteration of visual evidence of war crimes.	Delegitimization of international tribunals; manipulation of public opinion.	Risk identified in intelligence reports: Doctored images could be used to accuse or exonerate actors in conflicts.
Geopolítica y diplomacia	Creation of fictitious cities or border changes.	Diplomatic tensions; treaty questioning; State propaganda	Examples of deepfake maps that transform geographical features of cities such as Seattle or Tacoma.

Figure 2. Table showing possible cases of manipulation and risk in satellite images

Impact on decision-making and public policies

The consequences of relying on doctored images go far beyond the media arena:

• Urbanism and planning: decisions about where to build infrastructure or how to plan urban areas could be made on manipulated images, generating costly errors that are difficult to reverse.
• Emergency management: If a flood or fire is depicted in fake images, emergency teams can allocate resources to the wrong places, while neglecting areas that are actually affected.
• Climate change and the environment: Doctored images of glaciers, deforestation or polluting emissions could manipulate political debates and delay the implementation of urgent measures.
• Markets and insurance: Insurers and financial companies that rely on satellite imagery to assess damage could be misled, with significant economic consequences.

In all these cases, what is at stake is not only the quality of the information, but also the effectiveness and legitimacy of public policies based on that data.

The technological cat and mouse game

The dynamics of counterfeit generation and detection are already known in other areas, such as  video or audio deepfakes: every time a more realistic generation method emerges, a more advanced detection algorithm is developed, and vice versa. In the field of satellite images, this technological career has particularities:

• Increasingly sophisticated generators: today's broadcast models can create highly realistic scenes, integrating ground textures, shadows, and urban geometries that fool even human experts.
• Detection limitations: Although algorithms are developed to identify fakes (analyzing pixel patterns, inconsistencies in shadows, or metadata), these methods are not always reliable when faced with state-of-the-art generators.
• Cost of verification: independently  verifying a satellite image requires access to alternative sources or different sensors, something that is not always available to journalists, NGOs or citizens.
• Double-edged swords: The same techniques used to detect fakes can be exploited by those who generate them, further refining synthetic images and making them more difficult to differentiate.

From visual evidence to questioned evidence

The deeper impact is cultural and epistemological: what was previously assumed to be objective evidence now becomes an element subject to doubt. If satellite imagery is no longer perceived as reliable evidence, it weakens fundamental narratives around scientific truth, international justice, and political accountability.

• In armed conflicts, a satellite image showing possible war crimes can be dismissed under the accusation of being a deepfake.
• In international courts, evidence based on satellite observation could lose weight in the face of suspicion of manipulation.
• In public debate, the relativism of "everything can be false" can be used as a rhetorical weapon to delegitimize even the strongest evidence.

Strategies to ensure authenticity

The crisis of confidence in satellite imagery is not an isolated problem in the geospatial sector, but is part of a broader phenomenon: digital disinformation in the age of artificial intelligence. Just as  video deepfakes have called into question the validity of audiovisual evidence, the proliferation of synthetic satellite imagery threatens to weaken the last frontier of perceived objective data: the unbiased view from space.

Ensuring the authenticity of these images requires a combination of technical solutions and governance mechanisms, capable of strengthening traceability, transparency and accountability across the spatial data value chain. The main strategies under development are described below.

Robust metadata: Record origin and chain of custody

 Metadata is the first line of defense against manipulation. In satellite imagery, they should include detailed information about:

• The sensor used (type, resolution, orbit).
• The exact time of acquisition (date and time, with time precision).
• The precise geographical location (official reference systems).
• The applied processing chain (atmospheric corrections, calibrations, reprojections).

Recording this metadata in secure repositories allows the chain of custody to be reconstructed, i.e. the history of who, how and when an image has been manipulated. Without this traceability, it is impossible to distinguish between authentic and counterfeit images.

EXAMPLE: The  European Union's Copernicus program  already implements standardized and open metadata for all its Sentinel images, facilitating subsequent audits and confidence in the origin.

Digital signatures and blockchain: ensuring integrity

Digital signatures allow you to verify that an image has not been altered since it was captured. They function as a cryptographic seal that is applied at the time of acquisition and validated at each subsequent use.

Blockchain technology  offers an additional level of assurance: storing acquisition and modification records on an immutable chain of blocks. In this way, any changes in the image or its metadata would be recorded and easily detectable.

EXAMPLE: The ESA – Trusted Data Framework project  explores the use of blockchain to protect the integrity of Earth observation data and bolster trust in critical applications such as climate change and food security.

 Invisible watermarks: hidden signs in the image

Digital watermarking involves embedding imperceptible signals in the satellite image itself, so that any subsequent alterations can be detected automatically.

• It can be done at the pixel level, slightly modifying color patterns or luminance.
• It is combined with cryptographic techniques to reinforce its validity.
• It allows you to validate images even if they have been cropped, compressed, or reprocessed.

EXAMPLE: In the audiovisual sector, watermarks have been used for years in the protection of digital content. Its adaptation to satellite images is in the experimental phase, but it could become a standard verification tool.

Open Standards (OGC, ISO): Trust through Interoperability

Standardization is key to ensuring that technical solutions are applied in a coordinated and global manner.

• OGC (Open Geospatial Consortium) works on standards for metadata management, geospatial data traceability, and interoperability between systems. Their work on geospatial APIs and FAIR (Findable, Accessible, Interoperable, Reusable) metadata is essential to establishing common trust practices.
• ISO develops standards on information management and authenticity of digital records that can also be applied to satellite imagery.

EXAMPLE: OGC Testbed-19 included specific experiments on geospatial data authenticity, testing approaches such as digital signatures and certificates of provenance.

Cross-check: combining multiple sources

A basic principle for detecting counterfeits is to contrast sources. In the case of satellite imagery, this involves:

• Compare images from different satellites (e.g. Sentinel-2 vs. Landsat-9).
• Use different types of sensors (optical, radar SAR, hyperspectral).
• Analyze time series to verify consistency over time.

EXAMPLE: Damage verification in Ukraine following the start of the Russian invasion in 2022 was done by comparing images from several vendors (Maxar, Planet, Sentinel), ensuring that the findings were not based on a single source.

AI vs. AI: Automatic Counterfeit Detection

The same artificial intelligence that allows synthetic images to be created can be used to detect them. Techniques include:

• Pixel Forensics: Identify patterns generated by GANs or broadcast models.
• Neural networks trained to distinguish between real and synthetic images based on textures or spectral distributions.
• Geometric inconsistencies models: detect impossible shadows, topographic inconsistencies, or repetitive patterns.

EXAMPLE: Researchers at the University of Washington and other groups have shown that specific algorithms can detect satellite fakes with greater than 90% accuracy under controlled conditions.

Current Experiences: Global Initiatives

Several international projects are already working on mechanisms to reinforce authenticity:

• Coalition for Content Provenance and Authenticity (C2PA): A partnership between Adobe, Microsoft, BBC, Intel, and other organizations to develop an open standard for provenance and authenticity of digital content, including images. Its model can be applied directly to the satellite sector.
• OGC work: the organization promotes the debate on trust in geospatial data and has highlighted the importance of ensuring the traceability of synthetic and real satellite images (OGC Blog).
• NGA (National Geospatial-Intelligence Agency) in the US has publicly acknowledged the threat of synthetic imagery in defence and is driving collaborations with academia and industry to develop detection systems.

Towards an ecosystem of trust

The strategies described should not be understood as alternatives, but as complementary layers in a trusted ecosystem:

Id	Layers	Benefits
1	Robust metadata  (source, sensor, chain of custody)	Traceability guaranteed
2	Digital signatures and blockchain (data integrity)	Ensuring integrity
3	Invisible watermarks  (hidden signs)	Add a hidden level of protection
4	Cross-check  (multiple satellites and sensors)	Validates independently
5	AI vs. AI (counterfeit detector)	Respond to emerging threats
6	International governance  (accountability, legal frameworks)	Articulate clear rules of liability

Figure 3. Layers to ensure confidence in synthetic satellite images

Success will depend on these mechanisms being integrated together, under open and collaborative frameworks, and with the active involvement of space agencies, governments, the private sector and the scientific community.

Conclusions

Synthetic images, far from being just a threat, represent a powerful tool that, when used well, can provide significant value in areas such as simulation, algorithm training or innovation in digital services. The problem arises when these images are presented as real without proper transparency, fueling misinformation or manipulating public perception.

The challenge, therefore, is twofold: to take advantage of the opportunities offered by the synthesis of visual data to advance science, technology and management, and to minimize the risks associated with the misuse of these capabilities, especially in the form of deepfakes or deliberate falsifications.

In the particular case of satellite imagery, trust takes on a strategic dimension. Critical decisions in national security, disaster response, environmental policy, and international justice depend on them. If the authenticity of these images is called into question, not only the reliability of the data is compromised, but also the legitimacy of decisions based on them.

The future of Earth observation will be shaped by our ability to ensure authenticity, transparency and traceability across the value chain: from data acquisition to dissemination and end use. Technical solutions (robust metadata, digital signatures, blockchain, watermarks, cross-verification, and AI for counterfeit detection), combined with governance frameworks and international cooperation, will be the key to building an ecosystem of trust.

In short, we must assume a simple but forceful guiding principle:

"If we can't trust what we see from space, we put our decisions on Earth at risk."

Content prepared by Mayte Toscano, Senior Consultant in Data Economy Technologies. The contents and points of view reflected in this publication are the sole responsibility of the author.

Sicma, a climate and environmental information system, is a platform that displays climate scenarios and various variables generated from them. This application is developed entirely with free software and allows users to consult current, past, and future climate conditions, with variable spatial resolution according to the needs of each case (100 by 100 meters in the case of the Canary Islands, and 200 by 200 meters in the case of Andalusia). This makes it possible to obtain local information on the point of intervention.

The information is generated for the scenarios, models, horizons and annual periods considered necessary in each case and with the most appropriate resolution and interpolations for each territory.

Sicma provides information on variables calculated from daily series. To quantify uncertainties, it offers projections generated from ten climate models based on the sixth report of the Intergovernmental Panel on Climate Change (IPCC), each under four future emissions scenarios, known as shared socio-economic pathways (SSPs). Therefore, a total of 40 projections are generated. These climate projections, detailed up to the year 2100, are a very useful tool for planning and managing water, agriculture and environmental conservation.

Users can easily access information on climate scenarios, providing representative data in different territorial areas through a viewer. Some of the variables included in this viewer are: maximum temperature, average temperature, minimum temperature, precipitation, potential evapotranspiration, water balance, hot days (>40ºC) or tropical nights (>22ºC).

In addition to viewing, it is also possible to download data in alphanumeric formats in spreadsheets, graphs, or value maps.

There are currently two open sicma environments:

• Sicma Andalucía: https://andalucia.sicma.red/
• Sicma Canarias: https://canarias.sicma.red/

Artificial intelligence (AI) has become a key technology in multiple sectors, from health and education to industry and environmental management, not to mention the number of citizens who create texts, images or videos with this technology for their own personal enjoyment. It is estimated that in Spain more than half of the adult population has ever used an AI tool.

However, this boom poses challenges in terms of sustainability, both in terms of water and energy consumption and in terms of social and ethical impact. It is therefore necessary to seek solutions that help mitigate the negative effects, promoting efficient, responsible and accessible models for all. In this article we will address this challenge, as well as possible efforts to address it.

What is the environmental impact of AI?

In a landscape where artificial intelligence is all the rage, more and more users are wondering what price we should pay for being able to create memes in a matter of seconds.

To properly calculate the total impact of artificial intelligence, it is necessary to consider the cycles of hardware and software as a whole, as the United Nations Environment Programme (UNEP)indicates. That is, it is necessary to consider everything from raw material extraction, production, transport and construction of the data centre, management, maintenance and disposal of e-waste, to data collection and preparation, modelling, training, validation, implementation, inference, maintenance and decommissioning. This generates direct, indirect and higher-order effects:

• The direct impacts include the consumption of energy, water and mineral resources, as well as the production of emissions and e-waste, which generates a considerable carbon footprint.
• The indirect effects derive from the use of AI, for example, those generated by the increased use of autonomous vehicles.
• Moreover, the widespread use of artificial intelligence also carries an ethical dimension, as it may exacerbate existing inequalities, especially affecting minorities and low-income people. Sometimes the training data used are biased or of poor quality (e.g. under-representing certain population groups). This situation can lead to responses and decisions that favour majority groups.

Some of the figures compiled in the UN document that can help us to get an idea of the impact generated by AI include:

• A single request for information to ChatGPT consumes ten times more electricity than a query on a search engine such as Google, according to data from the International Energy Agency (IEA).
• Entering a single Large Language Model ( Large Language Models or LLM) generates approximately 300.000 kg of carbon dioxide emissions, which is equivalent to 125 round-trip flights between New York and Beijing, according to the scientific paper "The carbon impact of artificial intelligence".
• Global demand for AI water will be between 4.2 and 6.6 billion cubic metres by 2,027, a figure that exceeds the total consumption of a country like Denmark, according to the "Making AI Less "Thirsty": Uncovering and Addressing the Secret Water Footprint of AI Models" study.

Solutions for sustainable AI

In view of this situation, the UN itself proposes several aspects to which attention needs to be paid, for example:

• Search for standardised methods and parameters to measure the environmental impact of AI, focusing on direct effects, which are easier to measure thanks to energy, water and resource consumption data. Knowing this information will make it easier to take action that will bring substantial benefit.
• Facilitate the awareness of society, through mechanisms that oblige companies to make this information public in a transparent and accessible manner. This could eventually promote behavioural changes towards a more sustainable use of AI.
• Prioritise research on optimising algorithms, for energy efficiency. For example, the energy required can be minimised by reducing computational complexity and data usage. Decentralised computing can also be boosted, as distributing processes over less demanding networks avoids overloading large servers.
• Encourage the use of renewable energies in data centres, such as solar and wind power. In addition, companies need to be encouraged to undertake carbon offsetting practices.

In addition to its environmental impact, and as seen above, AI must also be sustainable from a social and ethical perspective. This requires:

• Avoid algorithmic bias: ensure that the data used represent the diversity of the population, avoiding unintended discrimination.
• Transparency in models: make algorithms understandable and accessible, promoting trust and human oversight.
• Accessibility and equity: develop AI systems that are inclusive and benefit underprivileged communities.

While artificial intelligence poses challenges in terms of sustainability, it can also be a key partner in building a greener planet. Its ability to analyse large volumes of data allows optimising energy use, improving the management of natural resources and developing more efficient strategies in sectors such as agriculture, mobility and industry. From predicting climate change to designing models to reduce emissions, AI offers innovative solutions that can accelerate the transition to a more sustainable future.

National Green Algorithms Programme

 In response to this reality, Spain has launched the National Programme for Green Algorithms (PNAV). This is an initiative that seeks to integrate sustainability in the design and application of AI, promoting more efficient and environmentally responsible models, while promoting its use to respond to different environmental challenges.

The main goal of the NAPAV is to encourage the development of algorithms that minimise environmental impact from their conception. This approach, known as "Green by Design", implies that sustainability is not an afterthought, but a fundamental criterion in the creation of AI models. In addition, the programme seeks to promote research in sustainable IA, improve the energy efficiency of digital infrastructures and promote the integration of technologies such as the green blockchain into the productive fabric.

This initiative is part of the Recovery, Transformation and Resilience Plan, the Spain Digital Agenda 2026 and the National Artificial Intelligence Strategy.. Objectives include the development of a best practice guide, a catalogue of efficient algorithms and a catalogue of algorithms to address environmental problems, the generation of an impact calculator for self-assessment, as well as measures to support awareness-raising and training of AI developers.

Its website functions as a knowledge space on sustainable artificial intelligence, where you can keep up to date with the main news, events, interviews, etc. related to this field. They also organise competitions, such as hackathons, to promote solutions that help solve environmental challenges.

The Future of Sustainable AI

The path towards more responsible artificial intelligence depends on the joint efforts of governments, business and the scientific community. Investment in research, the development of appropriate regulations and awareness of ethical AI will be key to ensuring that this technology drives progress without compromising the planet or society.

Sustainable AI is not only a technological challenge, but an opportunity to transform innovation into a driver of global welfare. It is up to all of us to progress as a society without destroying the planet.

The value of open satellite data in Europe

Satellites have become essential tools for understanding the planet and managing resources efficiently. The European Union (EU) has developed an advanced space infrastructure with the aim of providing real-time data on the environment, navigation and meteorology.

This satellite network is driven by four key programmes:.

• Copernicus: Earth observation, environmental monitoring and climate change.
• Galileo: high-precision satellite navigation, alternative to GPS.
• EGNOS: improved positioning accuracy, key to aviation and navigation.
• Meteosat: padvanced meteorological prediction and atmospheric monitoring.

Through these programmes, Europe not only ensures its technological independence, but also obtains data that is made available to citizens to drive strategic applications in agriculture, security, disaster management and urban planning.

In this article we will explore each programme, its satellites and their impact on society, including Spain''s role in each of them.

Copernicus: Europe''s Earth observation network

Copernicus is the EU Earth observation programme, managed by the European Commission with the technical support of the European Space Agency (ESA) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT).. It aims to provide free and open data about the planet to monitor climate change, manage natural resources and respond to emergencies.

The programme is structured into three main components:

1. Space component: consists of a series of satellites called Sentinel, developed specifically for the needs of Copernicus. These satellites provide high quality data for various applications, such as land, sea and atmospheric monitoring.
2. Component in situ: includes data collected through ground, air and sea stations. These data are essential to calibrate and validate the information obtained by the satellites, ensuring its accuracy and reliability.
3. Operational Services: offers six thematic services that transform collected data into useful information for users:
   • Atmospheric monitoring
   • Marine monitoring
   • Terrestrial monitoring
   • Climate change
   • Emergency management
   • Safety

These services provide information in areas such as air quality, ocean status, land use, climate trends, disaster response and security, supporting informed decision-making in Europe.

Spain has played a key role in the manufacture of components for the Sentinel satellites. Spanish companies have developed critical structures and sensors, and have contributed to the development of data processing software.  Spain is also leading projects such as the Atlantic Constellation, which will develop small satellites for climate and oceanic monitoring.

Sentinel satellite

Satellite	Technical characteristics	Resolution	Coverage (capture frequency)	Uses
Sentinel-1	C-band SAR radar, resolution up to 5m	Up to 5m	Every 6 days	Land and ocean monitoring, natural disasters
Sentinel-2	Multispectral camera (13 bands), resolution up to 10m	10m, 20m, 60m	Every 5 days	Agricultural management, forestry monitoring, water quality
Sentinel-3	Radiometer SLSTR, Spectrometer OLCI, Altimeter SRAL	300m (OLCI), 500m (SLSTR)	Every 1-2 days	Oceanic, climatic and terrestrial observation
Sentinel-5P	Tropomi spectrometer, resolution 7x3.5 km².	7x3.5 km²	Daily global coverage	Air quality monitoring, trace gases
Sentinel-6	Altimeter Poseidon-4, vertical resolution 1 cm	1cm	Every 10 days	Sea level measurement, climate change

Figure 1. Table satellites Sentinel. Source: own elaboration

Galileo: the european GPS

Galileo is the global navigation satellite system developed by the European Union, managed by the European Space Agency (ESA) and operated by the European Union Space Programme Agency (EUSPA). It aims to provide a reliable and highly accurate global positioning service, independent of other systems such as the US GPS, China''s Beidou or Russia''s GLONASS. Galileo is designed for civilian use and offers free and paid services for various sectors, including transport, telecommunications, energy and finance.

Spain has played a leading role in the Galileo programme. The European GNSS Service Centre (GSC), located in Torrejón de Ardoz, Madrid, acts as the main contact point for users of the Galileo system. In addition, Spanish industry has contributed to the development and manufacture of components for satellites and ground infrastructure, strengthening Spain''s position in the European aerospace sector.

Satellite	Technical characteristics	Resolution	Coverage (capture frequency)	Uses
Galileo FOC	Medium Earth Orbit (MEO), 24 operatives	N/A	Continuous	Precise positioning, land and maritime navigation
Galileo IOV	First test satellites of the Galileo system	N/A	Continuous	Initial testing of Galileo before FOC

Figure 2. Satellite Galileo. Source: own elaboration

EGNOS: improving the accuracy of GPS and Galileo

 The European Geostationary Navigation Overlay Service (EGNOS) is the European satellite-based augmentation system (Satellite Based Augmentation System or SBAS) designed to improve the accuracy and reliability of global navigation satellite systems ( Global Navigation Satellite System, GNSS), such as GPS and, in the future, Galileo. EGNOS provides corrections and integrity data that allow users in Europe to determine their position with an accuracy of up to 1.5 metres, making it suitable for safety-critical applications such as aviation and maritime navigation.

Spain has played a leading role in the development and operation of EGNOS. Through ENAIRE, Spain hosts five RIMS Reference Stations located in Santiago, Palma, Malaga, Gran Canaria and La Palma. In addition, the Madrid Air Traffic Control Centre, located in Torrejón de Ardoz, hosts one of the EGNOS Mission Control Centres (MCC), operated by ENAIRE. The Spanish space industry has contributed significantly to the development of the system, with companies participating in studies for the next generation of EGNOS.

Satellite	Technical characteristics	Resolution	Coverage (capture frequency)	Uses
EGNOS Geo	Geostationary GNSS correction satellites	N/A	Real-time GNSS correction	GNSS signal correction for aviation and transportation

Figure 3. Table satellite EGNOS. Source: own elaboration

Meteosat: high precision weather forecasting

The Meteosat programme consists of a series of geostationary meteorological satellites initially developed by the European Space Agency (ESA) and currently operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). These satellites are positioned in geostationary orbit above the Earth''s equator, allowing continuous monitoring of weather conditions over Europe, Africa and the Atlantic Ocean. Its main function is to provide images and data to facilitate weather prediction and climate monitoring.

Spain has been an active participant in the Meteosat programme since its inception. Through the Agencia Estatal de Meteorología (AEMET), Spain contributes financially to EUMETSAT and participates in the programme''s decision-making and operations. In addition, the Spanish space industry has played a key role in the development of the Meteosat satellites. Spanish companies have been responsible for the design and supply of critical components for third-generation satellites, including scanning and calibration mechanisms.

Satellite	Technical characteristics	Resolution	Cobertura (frecuencia de captura)	Usos
Meteosat Primera Gen.	Initial weather satellites, low resolution	Low resolution	Every 30min	Basic weather forecast, images every 30 min.
Meteosat Segunda Gen.	Higher spectral and temporal resolution, data every 15 min.	High resolution	Every 15min	Improved accuracy, early detection of weather events
Meteosat Tercera Gen.	High-precision weather imaging, lightning detection	High resolution	High frequency	High-precision weather imaging, lightning detection

Figure 4. Metosat satellite. Source: own elaboration

Access to the data of each programme

Each programme has different conditions and distribution platforms in terms of access to data:

• Copernicus: provides free and open data through various platforms.  Users can access satellite imagery and products through the Copernicus Data Space Ecosystem, which offers search, download and processing tools. Data can also be obtained through APIs for integration into automated systems.
• Galileo: its open service (Open Service - OS) allows free use of the navigation signals for any user with a compatible receiver, free of charge. However, direct access to raw satellite data is not provided. For information on services and documentation, access is via the European GNSS Services Centre (GSC):
  • Galileo Portal.
  • Registration for access to the High Accuracy Service (HAS) (registration required).
• EGNOS: This system improves navigation accuracy with GNSS correction signals.  Data on service availability and status can be found on the EGNOS User Support platform..
• Meteosat: Meteosat satellite data are available through the EUMETSAT platform. There are different levels of access, including some free data and some subject to registration or payment.  For imagery and meteorological products you can access the EUMETSAT Data Centre..

In terms of open access, Copernicus is the only programme that offers open and unrestricted data. In contrast, Galileo and EGNOS provide free services, but not access to raw satellite data, while Meteosat requires registration and in some cases payment for access to specific data.

Conclusions

The Copernicus, Galileo, EGNOS and Meteosat programmes not only reinforce Europe''s space sovereignty, but also ensure access to strategic data essential for the management of the planet. Through them, Europe can monitor climate change, optimise global navigation, improve the accuracy of its positioning systems and strengthen its weather predictioncapabilities, ensuring more effective responses to environmental crises and emergencies.

Spain plays a fundamental role in this space infrastructure, not only with its aerospace industry, but also with its control centres and reference stations, consolidating itself as a key player in the development and operation of these systems.

Satellite imagery and data have evolved from scientific tools to become essential resources for security, environmental management and sustainable growth. In a world increasingly dependent on real-time information, access to this data is critical for climate resilience, spatial planning, sustainable agriculture and ecosystem protection.

The future of Earth observation and satellite navigation is constantly evolving, and Europe, with its advanced space programmes, is positioning itself as a leader in the exploration, analysis and management of the planet from space.

Access to this data allows researchers, businesses and governments to make more informed and effective decisions. With these systems, Europe and Spain guarantee their technological independence and strengthen their leadership in the space sector.

Ready to explore more? Access the links for each programme and discover how this data can transform our world.

Copernicus	https://dataspace.copernicus.eu/	Download centre
Meteosat	https://user.eumetsat.int/data-access/data-centre/	Download centre
Galileo	https://www.gsc-europa.eu/galileo/services/galileo-high-accuracy-servic…/	Download centre, after registration
EGNOS	https://egnos-user-support.essp-sas.eu/	Project

Figure 5. Source: own elaboration

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Content prepared by Mayte Toscano, Senior Consultant in Data Economy Technologies. The contents and points of view reflected in this publication are the sole responsibility of the author.

March is approaching and with it a new edition of the Open Data Day. It is an annual worldwide celebration that has been organised for 12 years, promoted by the Open Knowledge Foundation through the Open Knowledge Network. It aims to promote the use of open data in all countries and cultures.

This year's central theme is "Open data to address the polycrisis". The term polycrisis refers to a situation where different risks exist in the same time period. This theme aims to focus on open data as a tool to address, through its reuse, global challenges such as poverty and multiple inequalities, violence and conflict, climate risks and natural disasters.

If several years ago the activities were limited to a single day, from 2023 we have a week to enjoy various conferences, seminars, workshops, etc. centred on this theme. Specifically, in 2025, Open Data Day activities will take place from 1 to 7 March.

Through its website you can see the various activities that will take place throughout the week all over the world. In this article we review some of those that you can follow from Spain, either because they take place in Spain or because they can be followed online.

Open Data Day 2025: Women Leading Open Data for Equality

Iniciativa Barcelona Open Data is organising a session on the afternoon of 6 March focusing on how open data can help address equality challenges. The event will bring together women experts in data technologies and open data, to share knowledge, experiences and best practices in both the publication and reuse of open data in this field.

The event will start at 17:30 with a welcome and introduction. This will be followed by two panel discussions and an interview:

• Round Table 1. Publishing institutions. Gender-sensitive data strategy to address the feminist agenda.
• DIALOGUE Data lab. Building feminist Tech Data practice.
• Round Table 2. Re-users. Projects based on the use of open data to address the feminist agenda.

The day will end at 19:40 with a cocktail and the opportunity for attendees to discuss the topics discussed and expand their network through networking.

How can you follow the event? This is an in-person event, which will be held at Ca l'Alier, Carrer de Pere IV, 362 (Barcelona).

Registration

Open access scientific and scholarly publishing as a tool to face the 21st century polycrisis: the key role of publishers

Organised by a private individual, Professor Damián Molgaray, this conference looks at the key role of editors in open access scientific and scholarly publishing. The idea is for participants to reflect on how open knowledge is positioned as a fundamental tool to face the challenges of the 21st century polycrisis, with a focus on Latin America.

The event will take place on 4 March at 11:00 in Argentina (15:00 in mainland Spain).

How can you follow the event? This is an online event through Google Meet.

Registration

WhoFundsThem

The organisation mySociety will show the results of its latest project. Over the last few months, a team of volunteers has collected data on the financial interests of the 650 MPs in the UK House of Commons, using sources such as the official Register of Interests, Companies House, MPs' attendance at debates etc. This data, checked and verified with MPs themselves through a 'right of reply' system, has been transformed into an easily accessible format, so that anyone can easily understand it, and will be published on the parliamentary tracking website TheyWorkForYou.

At this event, the project will be presented and the conclusions will be discussed. It takes place on Tuesday 4 at 14:00 London time (15:00 in Spain peninsular).

How can you follow the event? The session can be followed online, but registration is required. The event will be in English.

Registration

Science on the 7th: A conversation on Open Data & Air Quality

El viernes 7 a las 9:00 EST – (15:00 en España peninsular) se podrá seguir online una conferencia sobre datos abiertos y calidad del aire. La sesión reunirá a diversos expertos para debatir los temas de actualidad en materia de calidad del aire y salud mundial, y se examinará la contaminación atmosférica procedente de fuentes clave, como las partículas, el ozono y la contaminación relacionada con el tráfico.

Esta iniciativa está organizada por Health Effects Institute, una corporación sin ánimo de lucro que proporciona datos científicos sobre los efectos de la contaminación atmosférica en la salud.

A conference on open data and air quality will be available online on Friday 7 at 9:00 EST (15:00 in mainland Spain). The session will bring together a range of experts to discuss topical issues in air quality and global health, and will examine air pollution from key sources such as particulate matter, ozone and traffic-related pollution.

This initiative is organised by Health Effects Institute, a non-profit corporation that provides scientific data on the health effects of air pollution.

How can you follow the event? The conference, which will be in English, can be viewed on YouTube. No registration is required.

Watch the event online

Deadline open for new event proposals

The above events are just a few examples of the activities that are part of this global celebration, but, as mentioned above, you can see all the actions on the initiative's website.

In addition, the deadline for registering new events is still open. If you have a proposal, you can register it via this link.

From datos.gob.es we invite you to join this week of celebration, which serves to vindicate the power of open data to generate positive changes in our society. Don't miss it!

The European Green Deal (Green Deal) is the European Union's (EU) sustainable growth strategy, designed to drive a green transition that transforms Europe into a just and prosperous society with a modern and competitive economy. Within this strategy, initiatives such as Target 55 (Fit for 55), which aims to reduce EU emissions by at least 55% by 2030, stand out, and the Nature Restoration Regulation(, which sets binding targets to restore ecosystems, habitats and species.

 The European Data Strategy positions the EU as a leader in data-driven economies, promoting fundamental values such as privacy and sustainability.  This strategy envisages the creation of data spaces sectoral spaces to encourage the availability and sharing of data, promoting its re-use for the benefit of society and various sectors, including the environment.

This article looks at how environmental data spaces, driven by the European Data Strategy, play a key role in achieving the goals of the European Green Pact by fostering the innovative and collaborative use of data.

Green Pact data space from the European Data Strategy

In this context, the EU is promoting the Green Deal Data Space, designed to support the objectives of the Green Deal through the use of data. This data space will allow sharing data and using its full potential to address key environmental challenges in several areas: preservation of biodiversity, sustainable water management, the fight against climate change and the efficient use of natural resources, among others.

In this regard, the European Data Strategy highlights two initiatives:

• On the one hand, the GreenData4all initiative which carries out an update of the INSPIRE directive to enable greater exchange of environmental geospatial data between the public and private sectors, and their effective re-use, including open access to the general public.
•  On the other hand, the Destination Earth project proposes the creation of a digital twin of the Earth, using, among others, satellite data, which will allow the simulation of scenarios related to climate change, the management of natural resources and the prevention of natural disasters.

Preparatory actions for the development of the Green Pact data space

As part of its strategy for funding preparatory actions for the development of data spaces, the EU is funding the GREAT project (The Green Deal Data Space Foundation and its Community of Practice). This project focuses on laying the foundations for the development of the Green Deal data space through three strategic use cases: climate change mitigation and adaptation, zero pollution and biodiversity. A key aspect of GREAT is the identification and definition of a prioritised set of high-value environmental data (minimum but scalable set).  This approach directly connects this project to the concept of high-value data defined in the European Open Data Directive (i.e. data whose re-use generates not only a positive economic impact, but also social and environmental benefits)..  The high-value data defined in the Implementing Regulation include data related to Earth observation and the environment, including data obtained from satellites, ground sensors and in situ data.. These packages cover issues such as air quality, climate, emissions, biodiversity, noise, waste and water, all of which are related to the European Green Pact.

Differentiating aspects of the Green Pact data space

At this point, three differentiating aspects of the Green Pact data space can be highlighted.

• Firstly, its clearly multi-sectoral nature requires consideration of data from a wide variety of domains, each with their own specific regulatory frameworks and models.
• Secondly, its development is deeply linked to the territory, which implies the need to adopt a bottom-up approach (bottom-up) starting from concrete and local scenarios.
• Finally, it includes high-value data, which highlights the importance of active involvement of public administrations, as well as the collaboration of the private and third sectors to ensure its success and sustainability.

Therefore, the potential of environmental data will be significantly increased through European data spaces that are multi-sectoral, territorialised and with strong public sector involvement.

Development of environmental data spaces in HORIZON programme

In order to develop environmental data spaces taking into account the above considerations of both the European Data Strategy and the preparatory actions under the Horizon Europe (HORIZON) programme, the EU is funding four projects:

• Urban Data Spaces for Green dEal (USAGE).. This project develops solutions to ensure that environmental data at the local level is useful for mitigating the effects of climate change. This includes the development of mechanisms to enable cities to generate data that meets the FAIR principles (Findable, Accessible, Interoperable, Reusable) enabling its use for environmentally informed decision-making.
• All Data for Green Deal (AD4GD).. This project aims to propose a set of mechanisms to ensure that biodiversity, water quality and air quality data comply with the FAIR principles. They consider data from a variety of sources (satellite remote sensing, observation networks in situ, IoT-connected sensors, citizen science or socio-economic data).
• F.A.I.R. information cube (FAIRiCUBE). The purpose of this project is to create a platform that enables the reuse of biodiversity and climate data through the use of machine learning techniques. The aim is to enable public institutions that currently do not have easy access to these resources to improve their environmental policies and evidence-based decision-making (e.g. for the adaptation of cities to climate change).
• Biodiversity Building Blocks for Policy (B-Cubed).. This project aims to transform biodiversity monitoring into an agile process that generates more interoperable data. Biodiversity data from different sources, such as citizen science, museums, herbaria or research, are considered; as well as their consumption through business intelligence models, such as OLAP cubes, for informed decision-making in the generation of adequate public policies to counteract the global biodiversity crisis.

Environmental data spaces and research data

Finally, one source of data that can play a crucial role in achieving the objectives of the European Green Pact is scientific data emanating from research results.  In this context, the European Union's European Open Science Cloud (EOSC) initiativeis an essential tool. EOSC is an open, federated digital infrastructure designed to provide the European scientific community with access to high quality scientific data and services, i.e. a true research data space. This initiative aims to facilitate interoperability and data exchange in all fields of research by promoting the adoption of FAIR principles, and its federation with the Green Pact data space is therefore essential.

Conclusions

Geospatial data capture is essential for understanding our environment, making informed decisions and designing effective policies in areas such as urban planning, natural resource management or emergency response. In the past, this process was mainly manual and labour-intensive, based on ground measurements made with tools such as total stations and levels. Although these traditional techniques have evolved significantly and are still widely used, they have been complemented by automated and versatile methods that allow more efficient and detailed data collection.

The novelty in the current context lies not only in technological advances, which have improved the accuracy and efficiency of geospatial data collection, but also because it coincides with a widespread shift in mindset towards transparency and accessibility. This approach has encouraged the publication of the data obtained as open resources, facilitating their reuse in applications such as urban planning, energy management and environmental assessment. The combination of advanced technology and an increased awareness of the importance of information sharing marks a significant departure from traditional techniques.

In this article, we will explore some of the new methods of data capture, from photogrammetric flights with helicopters and drones, to ground-based systems such as mobile mapping, which use advanced sensors to generate highly accurate three-dimensional models and maps. In addition, we will learn how these technologies have empowered the generation of open data, democratising access to key geospatial information for innovation, sustainability and public-private collaboration.

Aerial photogrammetry: helicopters with advanced sensors

In the past, capturing geospatial data from the air involved long and complex processes. Analogue cameras mounted on aircraft generated aerial photographs that had to be processed manually to create two-dimensional maps. While this approach was innovative at the time, it also had limitations, such as lower resolution, long processing times and greater dependence on weather and daylight. However, technological advances have reduced these restrictions, even allowing operations at night or in adverse weather conditions.

Today, aerial photogrammetry has taken a qualitative leap forward thanks to the use of helicopters equipped with state-of-the-art sensors. The high-resolution digital cameras allow images to be captured at multiple angles, including oblique views that provide a more complete perspective of the terrain. In addition, the incorporation of thermal sensors and LiDAR (Light Detection and Ranging) technologies adds an unprecedented layer of detail and accuracy. These systems generate point clouds and three-dimensional models that can be integrated directly into geospatial analysis software, eliminating much of the manual processing.

Features	Advantages	Disadvantages
Coverage and flexibility	It allows coverage of large areas and access to complex terrain.	May be limited for use in areas with airspace restrictions. Inaccessible to undergrouns or difficult to access areas such as tunnels.
Data type	Capture visual, thermal and topographic data in a single flight.	-
Precision	Generates point clouds and 3D models with high accuracy.	-
Efficiency in large projects	It allows coverage of large areas where drones do not have sufficient autonomy.	High operational cost compared to other technologies.
Environmental impact and noise	-	Generates noise and greater environmental impact, limiting its use in sensitive areas.
Weather conditions	-	It depends on the weather; adverse conditions such as wind or rain  affect its operation.
Amortised	-	High cost compared to drones or ground-based methods.

Figure 1. Table with advantages and disadvantages of aerial photogrammetry with helicopters.

Mobile mapping: from backpacks to BIM integration

The mobile mapping is a geospatial data capture technique using vehicles equipped with cameras, LiDAR scanners, GPS and other advanced sensors. This technology allows detailed information to be collected as the vehicle moves, making it ideal for mapping urban areas, road networks and dynamic environments.

In the past, topographic surveys required stationary measurements, which meant traffic disruptions and considerable time to cover large areas. In contrast, mobile mapping has revolutionised this process, allowing data to be captured quickly, efficiently and with less impact on the environment. In addition, there are portable versions of this technology, such as backpacks with robotic scanners, which allow access to pedestrian or hard-to-reach areas.

Figure 2. Image captured with mobile mapping techniques.

Features	Advantages	Disadvantages
Speed	Captures data while the vehicle is on the move, reducing operating times.	Lower accuracy in areas with poor visibility for sensors (e.g. tunnels).
Urban coverage	Ideal for urban environments and complex road networks.	It is efficient in areas where vehicles can circulate, but its range is limited such as in rural or inaccessible terrain.
Flexibility of implementation	Available in portable (backpack) versions for pedestrian or hard-to-reach areas.	Portable equipment tends to have a shorter range than vehicular systems.
GIS and BIM implementation	It facilitates the generation of digital models and their use in planning and analysis.	Requires advanced software to process large volumes of data.
Impact on the environment	It does not require traffic interruptions or exclusive access to work areas.	Dependence on optimal environmental conditions, such as adequate light and climate.
Accessibility	Accessible to underground or hard-to-reach areas such as tunnels

Figure 3. Table with advantages and disadvantages of mobile mopping.

The mobile mapping is presented as a versatile and efficient solution for capturing geospatial data on the move, becoming a key tool for the modernisation of urban and territorial management systems.

HAPS and ballons: new heights for information capture

HAPS (High-Altitude Platform Stations) and hot-air balloons represent an innovative and efficient alternative for capturing geospatial data from high altitudes. These platforms, located in the stratosphere or at controlled altitudes, combine features of drones and satellites, offering an intermediate solution that stands out for its versatility and sustainability:

• HAPS, like zeppelins and similar aircraft, operate in the stratosphere, at altitudes between 18 and 20 kilometres, allowing a wide and detailed view of the terrain.
• The aerostatic balloons, on the other hand, are ideal for local or temporary studies, thanks to their easiness of deployment and operation at lower altitudes.

Both technologies can be equipped with high-resolution cameras, LiDAR sensors, thermal instruments and other advanced technologies for data capture.

Features	Advantages	Disadvantages
Useful	Large capture area, especially with HAPS in the stratosphere.	Limited coverage compared to satellites in orbit.
Sustainability	Lower environmental impact and energy footprint compared to helicopters or aeroplanes.	Dependence on weather conditions for deployment and stability.
Amortised	Lower operating costs than traditional satellites.	Higher initial investment than drones or ground equipment.
Versatility	Ideal for temporary or emergency projects.	Limited range in hot air balloons.
Duration of operation	HAPS can operate for long periods (days or weeks).	Hot air balloons have a shorter operating time.

Figure 4. Table with advantages and disadvantages of HAPS and ballons

HAPS and balloons are presented as key tools to complement existing technologies such as drones and satellites, offering new possibilities in geospatial data collection in a sustainable, flexible and efficient way. As these technologies evolve, their adoption will expand access to crucial data for smarter land and resource management.

Satellite technology: PAZ satellite and its future with PAZ-2

Satellite technology is a fundamental tool for capturing geospatial data globally. Spain has taken significant steps in this field with the development and launch of the PAZ satellite. This satellite, initially designed for security and defence purposes, has shown enormous potential for civilian applications such as environmental monitoring, natural resource management and urban planning.

PAZ is an Earth observation satellite equipped with a synthetic aperture radar (SAR), which allows high-resolution imaging, regardless of weather or light conditions.

The upcoming launch of PAZ-2 (planned for 2030) promises to further expand Spain''s observation capabilities. This new satellite, designed with technological improvements, aims to complement the functions of PAZ and increase the availability of data for civil and scientific applications. Planned improvements include:

• Higher image resolution.
• Ability to monitor larger areas in less time.
• Increased frequency of captures for more dynamic analysis.

Feature	Advantages	Disadvantages
Global coverage	Ability to capture data from anywhere on the planet.	Limitations in resolution compared to more detailed terrestrial technologies.
Climate independance	SAR sensors allow captures even in adverse weather conditions.
Data frequency	PAZ-2 will improve the frequency of captures, ideal for continuous monitoring.	Limited time in the lifetime of the satellite.
Access to open data	It encourages re-use in civil and scientific projects.	Requires advanced infrastructure to process large volumes of data.

Figure 5. Table with advantages and disadvantages of PAZ and PAZ-2 satellite technology

With PAZ and the forthcoming PAZ-2, Spain strengthens its position in the field of satellite observation, opening up new opportunities for efficient land management, environmental analysis and the development of innovative solutions based on geospatial datas. These satellites are not only a technological breakthrough, but also a strategic tool to promote sustainability and international cooperation in data access.

Conclusion: challenges and opportunities in data management 

The evolution of geospatial data capture techniques offers a unique opportunity to improve the accuracy, accessibility and quality of data, and in the specific case of open data, it is essential to foster transparency and re-use of public information. However, this progress cannot be understood without analysing the role played by technological tools in this process.

Innovations such as LiDAR in helicopters, Mobile Mapping, SAM, HAPS and satellites such as PAZ and PAZ-2 not only optimise data collection, but also have a direct impact on data quality and availability.

In short, these technological tools generate high quality information that can be made available to citizens as open data, a situation that is being driven by the shift in mindset towards transparency and accessibility. This balance makes open data and technological tools complementary, essential to maximise the social, economic and environmental value of geospatial data.

You can see a summary of these techniques and their applications in the following infographic:

 

Download the infographic here

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Content prepared by Mayte Toscano, Senior Consultant in Data Economy Technologies. The contents and points of view reflected in this publication are the sole responsibility of the author.

Promoting the data culture is a key objective at the national level that is also shared by the regional administrations. One of the ways to achieve this purpose is to award those solutions that have been developed with open datasets, an initiative that enhances their reuse and impact on society.

On this mission, the Junta de Castilla y León and the Basque Government have been organising open data competitions for years, a subject we talked about in our first episode of the datos.gob.es podcast that you can listen to here.

In this post, we take a look at the winning projects in the latest editions of the open data competitions in the Basque Country and Castilla y León.

Winners of the 8th Castile and Leon Open Data Competition

In the eighth edition of this annual competition, which usually opens at the end of summer, 35 entries were submitted, from which 8 winners were chosen in different categories.

Ideas category: participants had to describe an idea to create studies, services, websites or applications for mobile devices. A first prize of 1,500€ and a second prize of 500€ were awarded.

• First prize: Green Guardians of Castilla y León presented by Sergio José Ruiz Sainz. This is a proposal to develop a mobile application to guide visitors to the natural parks of Castilla y León. Users can access information (such as interactive maps with points of interest) as well as contribute useful data from their visit, which enriches the application.
• Second prize: ParkNature: intelligent parking management system in natural spaces presented by Víctor Manuel Gutiérrez Martín. It consists of an idea to create an application that optimises the experience of visitors to the natural areas of Castilla y León, by integrating real-time data on parking and connecting with nearby cultural and tourist events.

Products and Services Category: Awarded studies, services, websites or applications for mobile devices, which must be accessible to all citizens via the web through a URL. In this category, first, second and third prizes of €2,500, €1,500 and €500 respectively were awarded, as well as a specific prize of €1,500 for students.

• First prize: AquaCyL from Pablo Varela Vázquez. It is an application that provides information about the bathing areas in the autonomous community.
• Second prize: ConquistaCyL presented by Markel Juaristi Mendarozketa and Maite del Corte Sanz. It is an interactive game designed for tourism in Castilla y León and learning through a gamified process.
• Third prize: All the sport of Castilla y León presented by Laura Folgado Galache. It is an app that presents all the information of interest associated with a sport according to the province.
• Student prize: Otto Wunderlich en Segovia by Jorge Martín Arévalo. It is a photographic repository sorted according to type of monuments and location of Otto Wunderlich's photographs.

Didactic Resource Category: consisted of the creation of new and innovative open didactic resources to support classroom teaching. These resources were to be published under Creative Commons licences. A single first prize of €1,500 was awarded in this category.

• First prize: StartUp CyL: Business creation through Artificial Intelligence and Open Data presented by José María Pérez Ramos. It is a chatbot that uses the ChatGPT API to assist in setting up a business using open data.

Data Journalism category: awarded for published or updated (in a relevant way) journalistic pieces, both in written and audiovisual media, and offered a prize of €1,500.

• First prize: Codorniz, perdiz y paloma torcaz son las especies más cazadas en Burgos, presented by Sara Sendino Cantera, which analyses data on hunting in Burgos.

Winners of the 5th edition of the Open Data Euskadi Open Data Competition

As in previous editions, the Basque open data portal opened two prize categories: an ideas competition and an applications competition, each of which was divided into several categories. On this occasion, 41 applications were submitted for the ideas competition and 30 for the applications competition.

Idea competition: In this category, two prizes of €3,000 and €1,500 have been awarded in each category.

Health and Social Category

• First prize: Development of a Model for Predicting the Volume of Patients attending the Emergency Department of Osakidetza by Miren Bacete Martínez. It proposes the development of a predictive model using time series capable of anticipating both the volume of people attending the emergency department and the level of severity of cases.
• Second prize: Euskoeduca by Sandra García Arias. It is a proposed digital solution designed to provide personalised academic and career guidance to students, parents and guardians.

Category Environment and Sustainability

• First prize: Baratzapp by Leire Zubizarreta Barrenetxea. The idea consists of the development of a software that facilitates and assists in the planning of a vegetable garden by means of algorithms that seek to enhance the knowledge related to the self-consumption vegetable garden, while integrating, among others, climatological, environmental and plot information in a personalised way for the user.
• Second prize: Euskal Advice by Javier Carpintero Ordoñez. The aim of this proposal is to define a tourism recommender based on artificial intelligence.

General Category

• First prize: Lanbila by Hodei Gonçalves Barkaiztegi. It is a proposed app that uses generative AI and open data to match curriculum vitae with job offers in a semantic way.. It provides personalised recommendations, proactive employment and training alerts, and enables informed decisions through labour and territorial indicators.
• Second prize: Development of an LLM for the interactive consultation of Open Data of the Basque Government by Ibai Alberdi Martín. The proposal consists in the development of a Large Scale Language Model (LLM) similar to ChatGPT, specifically trained with open data, focused on providing a conversational and graphical interface that allows users to get accurate answers and dynamic visualisations.

Applications competition: this modality has selected one project in the web services category, awarded with €8,000, and two more in the General Category, which have received a first prize of €8,000 and a second prize of €5,000.

Category Web Services

• First prize: Bizidata: Plataforma de visualización del uso de bicicletas en Vitoria-Gasteiz by Igor Díaz de Guereñu de los Ríos. It is a platform that visualises, analyses and downloads data on bicycle use in Vitoria-Gasteiz, and explores how external factors, such as the weather and traffic, influence bicycle use.

General Category

• First prize: Garbiñe AI by Beatriz Arenal Redondo. It is an intelligent assistant that combines Artificial Intelligence (AI) with open data from Open Data Euskadi to promote the circular economy and improve recycling rates in the Basque Country.
• Second prize: Vitoria-Gasteiz Businessmap by Zaira Gil Ozaeta. It is an interactive visualisation tool based on open data, designed to improve strategic decisions in the field of entrepreneurship and economic activity in Vitoria-Gasteiz.

All these award-winning solutions reuse open datasets from the regional portal of Castilla y León or Euskadi, as the case may be. We encourage you to take a look at the proposals that may inspire you to participate in the next edition of these competitions. Follow us on social media so you don't miss out on this year's calls!