Previous week I followed up a workshop that prepared by The Copernicus WEkEO Service. It was relatively short workshop, but I had an incredible and inspiring 2 days. Today I want to share my insights about the workshop and as a user of Copernicus Data, I want to define WEkEO Service and Earthkit.

Welcome to Code Beyond the Earth! I'm Ece, the voice behind the Code Beyond the Earth. After two full days, and after sharing my certificate, I decided that I should talk about WEkEO and Copernicus services.

As a proud user of the Copernicus Data Services, I truly enjoyed exploring the WEkEO Data Platform and all its powerful features. Under the vast roof of the Copernicus Programme lies an incredible wealth of data — especially for those of us working across disciplines like climate science, environmental research, and space systems.

I once tried to invent the term Earth science as a shortcut when I forgot the proper terminology — not just geology, not just climate, but everything about this living, spinning planet. Yes, I know there’s a more precise way to say it. Yes, I could’ve looked it up. But sometimes, making up a word keeps the spark alive. I love language for that reason — it’s like a witch’s spell. With just a limited alphabet, we can conjure whole worlds. But I suppose that’s a topic for another blog post. :)

The Copernicus Program is the European Union’s Earth observation program that watches over our planet in near real-time, it splits two main branches such as; space component and services component.

Space component is a product of European Space Agency. On the other hand, service components have more variety and contribution of more than one important institutes, such as; European Environment Agency, Mercator Ocean International, European Center of Medium-Range Weather Forecasts, Joint Research Center - European Commission, European Maritime Safety Agency, Frontex and European Union Satellite Center.

Let’s dive in to data of the Copernicus Space and Service Component!

Space Component

Sentinel missions

The sentinel mission is created for operational needs of the Copernicus Program. Each mission has coverage requirements and provide robust datasets for the Copernicus Program. There are 7 Sentinel missions and according to official website 6 more missions are planning for the future use.

Sentinel-1:

Sentinel-1 is a satellite mission that uses radar to take pictures of the Earth’s surface, no matter the weather or time of day. Because it orbits from pole to pole, it can scan almost the entire planet regularly. It’s especially useful for monitoring land and ocean changes, and it plays a key role in responding to natural disasters like floods or earthquakes.

1A was launched April 2014 and 1B which was the mission ended in 2022 unexpectedly was launched April 2016. However, in December 2024, 1C was launched and after that Sentinel-1 returned to function fully again!

Sentinel-2:

Sentinel-2 is a polar-orbiting, multispectral high-resolution imaging mission for land monitoring to provide, for example, imagery of vegetation, soil and water cover, inland waterways and coastal areas. Sentinel-2 can also deliver information for emergency services.

2A was launched on June 2015 and 2B followed on March 2017. On September 2024, 2C joined its siblings.

Sentinel-3:

Sentinel-3 is a satellite mission that monitors both the oceans and land with great accuracy. It measures things like sea level, land and sea surface temperatures, and the color of oceans and land. This data helps with weather forecasting for the oceans and tracking environmental and climate changes around the world.

3A was launched on February 2016 and 3B joined on April 2018.

Sentinel-5 Precursor (Aka Sentinel-5P):

Sentinel-5P is a satellite that monitors air pollution and the gases that affect our climate. It was launched to fill the gap between older satellites and the upcoming Sentinel-5 mission. Sentinel-5P tracks harmful gases and tiny particles in the atmosphere, helping scientists understand air quality and climate change in real time.

Sentinel-5P was launched on October 2017.

Sentinel-4:

Sentinel-4 is an advanced air-quality sensor onboard the MTG-S weather satellite. MTG-S, short for Meteosat Third Generation – Sounder, is a new-generation satellite that stays fixed over Europe in geostationary orbit. Every hour, Sentinel-4 measures pollutants and trace gases in the atmosphere—such as nitrogen dioxide and ozone—using ultraviolet, visible, and near-infrared light. This frequent, detailed data helps scientists monitor air quality in real time and improve pollution forecasts to better protect people’s health and the environment.

It was launched on July 2025.

Sentinel-6:

Sentinel-6 is a satellite that measures the height of the world’s oceans with incredible accuracy. Using radar, it monitors sea-level rise and ocean conditions, which are essential for weather forecasting, climate research, and protecting coastal communities. Sentinel-6 continues the legacy of long-term ocean monitoring to better understand global climate change.

It was launched on November 2020.

The Value of Sentinel Data for a Computer Scientist Tackling Climate Change (Hi, That’s Me)

High-quality, Multimodal, and Spatiotemporal

• Rich sensor diversity: Radar (Sentinel-1), multispectral imaging (Sentinel-2), atmospheric chemistry (Sentinel-5P, 5), altimetry (Sentinel-6), and more — offering complementary views of Earth systems.

• Global and frequent: Coverage from daily to weekly with high spatial resolution (as fine as 10m).

• Time series ready: Ideal for modeling temporal patterns, detecting trends, and forecasting.

Open Access, Standardized, and Scalable

• Freely available to all: Sentinel data embodies the principles of open science — removing barriers to participation and enabling innovation from researchers, students, developers, and citizens worldwide.

• Democratizing climate research: You don’t need expensive instruments or proprietary data to study the Earth. With just a laptop and code, anyone can contribute to climate solutions.

• Standard formats & cloud-ready: Delivered in formats like GeoTIFF or NetCDF, Sentinel data integrates smoothly with common tools (e.g., Python, R, QGIS), and platforms like Google Earth Engine or WEkEO enable analysis at scale.

• Supports reproducible science: Open datasets enable transparent, collaborative, and reproducible research — essential for building trustworthy AI and decision-making tools in climate contexts.

• Empowers global South and grassroots innovation: By removing data gatekeeping, Sentinel missions allow under-resourced communities to monitor environmental changes, build early warning systems, and advocate for policy with evidence.

Directly Relevant to Climate Change Challenges

• Land use change & deforestation → Sentinel-2 multispectral imagery helps track vegetation loss, urban sprawl, and agricultural trends.

• Air pollution & atmospheric health → Sentinel-5P & 5 detect NO₂, SO₂, ozone, and methane — critical for understanding emissions and health impacts.

• Sea-level rise & ocean dynamics → Sentinel-6 measures global sea-surface height for monitoring rising oceans.

• Extreme weather and floods → Sentinel-1 radar data can penetrate clouds to detect floods and track soil moisture in disaster-prone areas.

A Playground for AI & ML for Climate

Sentinel data enables:

• Image classification & segmentation (e.g., detecting algae blooms, wildfires, or glacier retreat)

• Time series forecasting (e.g., drought prediction, land degradation)

• Change detection & anomaly detection

• Integration with climate models and socioeconomic data for robust AI systems.

Sentinel data is not just satellite imagery—It’s a structured, scalable, real-world dataset with climate significance, enabling innovation in environmental monitoring, decision support systems, digital twins, and climate resilience tools.

Services Components

Land Monitoring

The Copernicus Land Monitoring Service (CLMS) provides high-quality, regularly updated data on land use, land cover, and land condition across Europe and globally.

This data is essential for understanding how human activity and climate change are transforming landscapes — and it's all open-access and machine-readable, making it perfect for computational analysis and modeling.

Why It’s Valuable for a Computer Scientist

CLMS is a rich, structured dataset offering:

• Land Cover & Land Use Maps
  (e.g. forest, agriculture, urban areas — from local to global scale)

• Vegetation Indicators
  (like Leaf Area Index, NDVI, and Fraction of Green Vegetation)

• Soil and Water Indicators
  (e.g. soil moisture, surface water extent)

• Urban Monitoring
  (e.g. imperviousness, urban sprawl, green urban areas)

• Change Detection
  (e.g. forest disturbance maps, land cover change layers)

As a computer scientist, CLMS data can be used to:

• Train AI models for land cover classification, urban growth prediction, or deforestation alerts

• Build dashboards for local authorities to monitor environmental health or land degradation

• Model interactions between land use and climate variables (e.g. evapotranspiration, urban heat islands)

• Support digital twin models and early warning systems for climate adaptation

• Integrate it with Sentinel satellite imagery and other Copernicus services for multi-source analysis

Marine Environment Monitoring Service

The Copernicus Marine Environment Monitoring Service (CMEMS) provides real-time and historical data on the state of the oceans — from surface currents and sea level to temperature, salinity, biogeochemistry, and sea ice.

It offers scientifically validated, open-access data collected from satellites (like Sentinel-3 and 6), ocean buoys, and advanced ocean models. The goal: to monitor, understand, and predict the health of marine ecosystems and their response to climate change.

Why It Matters for a Computer Scientist

CMEMS is a data-rich, time-aware, and physics-based system, ideal for computational projects. Here’s why it’s gold for you:

• Physical ocean data: Sea surface temperature, currents, salinity, wave height, sea-level rise.

• Biogeochemical data: Chlorophyll, oxygen levels, nutrients — crucial for tracking marine health and detecting threats like algal blooms or mucilage (sea snot).

• Sea ice and polar metrics: Polar region insights to monitor melting trends and Arctic dynamics.

• Model outputs: Forecasts and reanalysis datasets — perfect for AI/ML, climate modeling, and digital twin simulations.

As a computer scientist, CMEMS enables me to:

• Model climate–ocean interactions: Understand how warming seas affect weather, fisheries, and coastal communities.

• Train machine learning models: Detect anomalies (e.g., marine heatwaves, dead zones) or forecast ocean behavior.

• Monitor coastal risks: Support decision tools for flood prediction, storm surge modeling, or coastal erosion.

• Fuse with Sentinel data: Combine satellite imagery (Sentinel-3, Sentinel-2 for coastlines) with in-situ data for robust, real-time environmental monitoring.

• Support SDG goals: Build open tools that help protect marine biodiversity and promote sustainable ocean use.

Atmosphere Monitoring Service

The Copernicus Atmosphere Monitoring Service (CAMS) provides continuous data on the composition of the atmosphere — including air pollution, greenhouse gases, aerosols, ozone, and solar radiation.

It uses a combination of satellite observations (like Sentinel-5P), ground stations, and sophisticated models to deliver real-time monitoring, forecasts, and historical records of air quality and atmospheric dynamics.

Why It’s Valuable for a Computer Scientist

CAMS gives me clean, structured, and interpretable atmospheric datasets — perfect for building intelligent climate-aware applications. Key data includes:

• Air pollutants: Nitrogen dioxide (NO₂), particulate matter (PM2.5, PM10), ozone (O₃), carbon monoxide (CO), sulfur dioxide (SO₂)

• Greenhouse gases: CO₂, CH₄ — tracked globally with spatiotemporal granularity

• Aerosols: Dust, smoke, sea salt — critical for modeling radiation balance and visibility

• Solar radiation: Useful for solar energy planning and weather models

From a computer science + climate innovation perspective, CAMS enables me to:

• Train ML models for air quality prediction, urban pollution mapping, or health impact assessments

• Develop decision-support tools for city planners, health officials, or climate activists

• Integrate with Sentinel data and ERA5 to model complex interactions between climate, land use, and air composition

• Detect pollution hotspots or anomalies using AI-driven pattern recognition

• Contribute to environmental justice: Help visualize pollution exposure in underserved or vulnerable communities

Emergency Services

CEMS provides rapid, reliable information during natural or man-made disasters — such as floods, wildfires, earthquakes, landslides, and humanitarian crises.

It combines real-time satellite data, geographic information systems (GIS), and predictive models to support emergency response, disaster risk reduction, and recovery efforts across Europe and worldwide.

Why It’s Valuable for a Computer Scientist

CEMS offers:

• Rapid Mapping: Near-real-time satellite-based maps to visualize the extent of damage from a disaster (e.g., flooded areas, burned zones, collapsed infrastructure)

• Risk & Recovery Mapping: Pre- and post-event assessments that help planners build safer, more climate-resilient communities

• Global Wildfire Information System (GWIS) and European Flood Awareness System (EFAS): Early warning tools using big data and models to forecast and track hazards

All outputs are open-access and machine-readable, making them a powerful foundation for:

• AI for disaster detection and response

• Risk prediction models

• Fusion with Sentinel-1/2/3 data for enhanced situational awareness

• Tools for humanitarian logistics, climate resilience, and crisis communication

CEMS helps bridge Earth observation and humanitarian action. For developers and researchers, it’s a chance to build solutions that save lives, support emergency workers, and reduce future risks — all powered by open science.

Security Services

The Copernicus Security Services use satellite data and geospatial analysis to support the European Union’s internal and external security policies. These services aren’t as publicly accessible as other Copernicus domains; they’re designed for authorized users such as EU agencies, national authorities, and select international partners.

The service operates across three mission areas:

• Border Surveillance (coordinated by Frontex): Supports the monitoring of EU external borders and feeds into the EUROSUR system to enhance situational awareness, particularly during irregular migration or search-and-rescue operations.

• Maritime Surveillance (led by EMSA): Combines Sentinel-1 radar data with vessel tracking to detect maritime pollution, monitor fishing activity, and support law enforcement at sea.

• Support to EU External Action (provided by SatCen): Delivers geospatial intelligence for crisis management, peacekeeping, humanitarian aid, and monitoring risks linked to instability, environmental degradation, or the protection of cultural heritage.

These services rely on Earth observation satellites, but also integrate non-space data (like ship reports or sensor networks), producing timely, actionable information for decision-makers.

Rethinking Security Through a Feminist Lens

From a feminist computer scientist with sociology background point of view, the concept of security becomes more than border control or state power. It expands into care, access, and protection — not just of territories, but of people, communities, and ecosystems.

So we might ask:

• What does security mean when we consider climate migration, resource scarcity, or environmental injustice?

• How might EO technologies be repurposed or expanded to serve human security, not just geopolitical interests?

• What are the ethical boundaries when satellites monitor vulnerable populations?

• Can we design systems that balance data capability with transparency and accountability?

• What would it mean to design security systems that prioritize well-being over control?

• Can we reimagine satellite technology as a tool for climate care, disaster solidarity, or community resilience?

• How can we ensure that surveillance doesn’t reproduce inequality, especially for displaced people, women, or Indigenous communities?

• Who is empowered — or silenced — by these technologies?

A feminist approach doesn’t reject technology — it asks who it serves, who it overlooks, and how we can reshape it with empathy, justice, and imagination. These aren’t just technical issues — they’re human ones.

These are not just technical questions — they are design questions, ethical questions, and deeply human questions. Each one opens a path I hope to explore in upcoming posts as we rethink Earth observation at the intersection of AI, climate, and care.

Now, with all these services — from land and oceans to atmosphere, climate, emergencies, and security — one question naturally follows:

How do we actually access and work with all this data?

It’s one thing to know that the information exists, but quite another to explore it, code with it, or integrate it into climate-tech tools.

That’s where WEkEO comes in — a platform that brings the entire Copernicus ecosystem to your fingertips, in a way that’s actually developer-friendly.

What Is WEkEO?

WEkEO is the Copernicus Data and Information Access Service (DIAS) platform developed by the European Union. It provides centralized, cloud-based access to all Copernicus data and services, along with data from EUMETSAT, ECMWF, and ESA.

Why It’s Valuable for a Computer Scientist

WEkEO was designed with data scientists, developers, and researchers in mind, offering:

• Access to all Copernicus services (Sentinels, ERA5, CAMS, CLMS, C3S, CMEMS, etc.)

• Cloud processing environment: You can code directly in the platform (Jupyter Notebooks, Python) — no need to download massive datasets to your machine.

• Ready-to-use notebooks and APIs: For exploring use cases in air quality, oceanography, land monitoring, and climate change.

• Interoperability: Seamlessly integrates EO datasets from different sources for multi-layer analysis.

• Scalable infrastructure: Ideal for training machine learning models, running simulations, and building climate-aware apps — without worrying about storage or compute limitations.

In Summary

WEkEO bridges Earth observation and data science by giving you:

• All the Copernicus data you need

• All the compute power you want

• In one single place — free and open

It’s like Google Colab meets Copernicus — for climate tech, environmental modeling, and remote sensing innovation.

During to two days of the workshop, there were valuable workshops about real life usage of WEkEO. Such as:

• Potential of Sentinel-2 for monitoring methane point emissions by Javier Gorroño

• From Copernicus Layers towards Local Climate Zones Classification for Climate Services by Inês Girão and Ana Oliveira

• ClimaMeter: extreme weather events in a changing climate by Davide Faranda

• Analysis of climate projections (temperatures and precipitations) under several carbon emissions scenarios by Alexandre Homerin

• Impacts of climate change on freshwater resources with Sentinel-2 imagery by Daria Andrievskaia

• Studying tundra wildfires in Siberia and the impacts on concentration of greenhouse gases by Simon Millet

Each session showed a different way to listen to the Earth through data, whether it’s wildfire signals in Siberia or urban climate zones shaping our future cities.

I walked away with a clearer sense of what’s possible — and a growing list of ideas I want to explore further after finishing my thesis. Let’s just say my “project ideas” folder has gotten a bit more crowded… and a lot more exciting.

Conclusion

So here I am — a feminist computer scientist with a sociology background, standing at the intersection of climate action, Earth observation, and ethical AI. After exploring the Copernicus ecosystem and diving into WEkEO’s workshops, I’m not just informed — I’m ignited.

Whether it’s building climate risk models, training machine learning on Sentinel-5P data, or rethinking how security tech can serve justice, I see data as a tool for care — not just prediction. And I’m ready to build. 🌍💻✨

To everyone behind the Copernicus program, and to the scientists, engineers, educators, and open data advocates who work to make climate knowledge public and powerful — thank you. These workshops weren’t just technical sessions; they were seeds of action. I left with a notebook full of code, a heart full of ideas, and a mind buzzing with questions that don’t scare me — they fuel me.

This is only the beginning. I’m not just observing change from above —
I’m coding it from within.

And after I wrap up my thesis (almost there!), I’ll share a new blog post focused on my hands-on experience with WEkEO — the code, the tools, the climate justice sparks. Because when data meets care, change becomes possible.
And I’m here for that. All in.

Thanks for reading! If any of this sparked your curiosity, made you think, or reminded you of something you're working on — I’d love to hear from you. Feel free to reach out, share your thoughts, or just say hi. Let's talk climate, code, and everything in between!

From my world to yours, Ece 🌍✨