Geospatial data gathered via satellites, drones, and sensors enables real-time monitoring of our planet, driving improvements in agriculture, energy, insurance, logistics, and climate management.

While a single snapshot of Earth may hold immense sentimental value for astronauts, it offers very little practical utility. Instead, it is multispectral imaging and continuous monitoring that deliver true value—allowing scientists to build historical datasets and track changes across the fifty years we have been focusing our lenses on the world from space.

Capturing 1,400 daily images of Earth at a 30-metre resolution makes it possible to monitor a vast array of phenomena, including wildfires, algal blooms, reservoir levels, and ecosystem health. The data collected by the American Landsat satellites is completely open-access, helping scientists author nearly 20,000 research papers on diverse topics. Dozens of similar models exist across other constellations, such as the Sentinel satellites of the European Copernicus programme, as well as the MODIS and VIIRS satellites, which specialise in tracking wildfires.

Through this technology, we have witnessed the drying up of the Aral Sea, the encroachment of the Sahara Desert, and the loss of the Amazon rainforest. Crucially, space-based observation has also allowed us to monitor the effectiveness of restoration efforts within these very ecosystems—tracking the partial refilling of the sea, conservation progress in the rainforest, and the growth of the Great Green Wall across the Sahel, south of the Sahara.

In fact, over half of all essential climate variables can only be measured at scale from space. This makes Earth observation (EO) technologies a vital tool for multinational organisations looking to meet environmental, social, and governance (ESG) requirements across diverse geographical regions.

Inside this article:

• Environmental shifts
• Geospatial data impact by sector
• Precision agriculture and energy
• Personal wellness and the public sector
• Drones and artificial intelligence in Earth observation

Changes to our planet impact our daily lives far more profoundly than geopolitical uncertainties; indeed, environmental shifts are frequently the root cause of geopolitical instability. The loss of natural ecosystems poses substantial risks, including resource scarcity and the disruption of ecosystem services. This is why having access to accurate data is so critical.

These technologies help organisations design more effective and, above all, sustainable work plans. It is estimated that data from Earth observation can help cut greenhouse gas emissions by more than two gigatonnes of CO₂ equivalent annually—amounting to a significant 3.6% of current global emissions.

In its 2026 Global Risks Report, the World Economic Forum identified extreme weather events as the single greatest global risk for the coming decade. Mitigating climate risks and natural disasters contributes approximately $23 billion to the viability of the sustainable economy, a figure that could triple by the end of the decade.

Understanding how these phenomena develop is a core objective of the European Commission’s Destination Earth (DestinE) initiative. This project aims to create a highly accurate digital twin of the planet to model, monitor, and simulate natural phenomena alongside the human activities that directly impact the environment.

The insurance and financial sectors are among the most avid consumers of Earth observation data, driven by the need to assess how extreme weather events might impact their assets. Unsurprisingly, several banks have partnered with scientific laboratories to pioneer the use of AI in measuring biodiversity—a crucial step for scaling nature-based financial products.

Insurance companies rely on remote sensing data to better evaluate the risks associated with covered assets. This data allows them to offer innovative policy structures, such as parametric insurance, while streamlining claims assessments.

In transport and logistics, corporate information systems harness AI to analyse Earth observation data to optimise delivery times and minimise fuel consumption. This can reduce fuel use by up to 3%, cutting both operational costs and greenhouse gas emissions. As technology advances, new data streams are being integrated, such as particulate matter measurements along flight paths and sea-ice levels for maritime shipping routes.

Earth observation can also be used to drive new revenue streams in certain sectors that produce data but have not previously exploited it. In the airline industry, for instance, this information can be integrated into products and services to create novel and innovative offerings.

Airlines like Lufthansa have equipped a significant portion of their fleet with the AMDAR (Aircraft Meteorological Data Relay) system, which measures variables such as temperature, atmospheric pressure, and wind. For now, the airline chooses not to commercialise this data, opting instead to share it freely with organizations like the German Meteorological Service (DWD).

In precision agriculture, the use of satellite data has been shown to reduce fertiliser application by 4% to 6%. The technology also has a massive impact on crop traceability—an area of intense interest for European authorities.

In the energy sector, Earth observation allows developers to assess the potential of new sites for solar, wind, and hydroelectric plants, while also identifying structural vulnerabilities in large-scale infrastructure such as pipelines and power grids.

Geospatial technologies are even opening up new pathways for personal wellness through consumer-facing applications. Roleplay-based gaming communities like onX, alongside platforms like Strava—which tracks running, hiking, and cycling—promote recreational and sporting activities. These platforms combine location data with Earth observation insights to help users stay safe and get the most out of their leisure time.

Yet, despite this vast landscape of commercial opportunities, public spending still accounts for nearly three-quarters of the geospatial data and services market. A large percentage of commercial demand remains latent.

This distribution makes sense: these are essential technologies for managing urban and environmental shifts in cities, providing multiple layers of temporal and spatial detail. Obsolete information can present severe challenges for public land-use planners during decision-making, especially when core datasets are infrequently updated.

No single technology is perfect for every scenario. The past decade has seen a boom in the availability of both autonomous and remote-controlled drones, whose data complements satellite imagery to build a more realistic picture of our surroundings.

Unmanned aerial vehicles (UAVs) can be equipped with optical and thermal cameras, radar, LiDAR, and other observation devices. While they lack the comprehensive scope and lifespan of satellites, they are far more cost-effective and easier to deploy. As a result, they have become standard tools in civil engineering, agriculture, mining, environmental management, and even archaeology.

Once data is gathered and transmitted, artificial intelligence takes over to perform preliminary processing and full-scale analysis. Automated detection algorithms are now deployed to predict the spread of wildfires and identify changes in land use with speed and precision. We have automated detection algorithms at our disposal to predict the evolution of forest fires or detect land-use changes quickly and accurately.

Collaborative, open-source platforms have also emerged, allowing experts to build and update satellite data processing tools for the wider community. For instance, Google Earth Engine hosts several petabytes of freely accessible data, enabling anyone to analyse trends and risks anywhere on the globe.

By 2032, satellite Earth observation is projected to generate over two exabytes (2,000 million gigabytes) of cumulative data. Its potential cumulative value could reach €700,000 million as early as 2030. The ultimate scale of this market will depend on our ability to resolve the data volume and complexity issues that have historically hindered commercial applications.

If the industry can overcome these bottlenecks, the economic rewards will be substantial: it is estimated that for every 1% increase in the adoption of real-time Earth data by end-users, an additional $9.8 billion of value can be added to the economy. This serves as a major wake-up call for sectors like agriculture, electricity, utilities, emergency services, insurance, financial services, mining, and transport logistics. Together, these industries are positioned to capture 94% of the commercial value generated by satellite data.

Sources: 

• https://www.weforum.org/publications/global-risks-report-2026/