TESSERA global Earth observation embeddings now available on AWS Open Data

Open data is reshaping how we understand and respond to global challenges. From climate change to food security to forest conservation, the ability to access and analyze large-scale geospatial data is critical for scientific research, policymaking, and real-world decision-making. Yet for most of the people who could benefit from it, satellite data has remained difficult to use because it’s locked in petabytes of irregular, cloud-corrupted imagery that requires specialized expertise and significant computing resources to process.

TESSERA, a global geospatial AI foundation model, is openly available through the Amazon Sustainability Data Initiative (ASDI) and the Amazon Web Services (AWS) Open Data Sponsorship Program. With compute and hosting support from AWS, dClimate is completing TESSERA’s global historical coverage and publishing the resulting analysis-ready data on Amazon Simple Storage Service (Amazon S3) for anyone to use at no additional cost. dClimate delivers climate data solutions that help businesses and governments assess risk, monitor natural capital, and make confident decisions. In this post, we share what TESSERA is, how it works, and how researchers, builders, and institutions can start using it.

Turning raw pixels into usable insight

Two of the most valuable sources of Earth observation data are the European Space Agency’s Sentinel-1 (radar) and Sentinel-2 (optical) missions, which image the planet continuously. But working with this data directly is hard. A single year of Sentinel-2 imagery for one 100-by-100 kilometer tile can exceed 100 gigabytes, and analysts must correct for clouds, align observations over time, and build custom processing pipelines before they can answer basic questions. These costs and complexities have kept advanced Earth observation in the hands of a small number of well-resourced organizations.

TESSERA was created to remove that barrier. The model was developed under Dr. Clement Atzberger, chief scientist at Arbol Inc., an AI-based insurance and climate risk company, in collaboration with researchers at the University of Cambridge. Arbol has served as an open source collaborator throughout TESSERA’s development, contributing applied research, engineering support, and real-world validation drawn from its climate risk underwriting. A peer-reviewed publication entitled TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis describes the work and reflects years of research into how to represent the Earth’s surface in a way that’s both compact and broadly useful.

How TESSERA works

Rather than treating Earth observation as an image-processing problem, TESSERA takes a pixel-based approach focused on what matters most for environmental analysis, which is how the spectral signature of each location evolves over time. The model fuses Sentinel-1 and Sentinel-2 time series and encodes a full year of behavior for every 10-meter pixel on Earth into a compact, 128-dimension embedding, which is a numerical fingerprint that captures the essential characteristics of that location and year.

These embeddings are ready for analysis. Instead of downloading and processing raw scenes, a user can retrieve a lightweight annual data layer and apply it directly to a downstream task with a small model on top, and no fine-tuning of the underlying foundation model is required. Because the embeddings are produced consistently across space and time, they can be compared from one year to the next and from one region to another, which is essential for tracking change.

The practical difference is significant. Downloading an annual embedding tile is far smaller and faster than retrieving the raw multisensor time series for the same area, which collapses the storage, bandwidth, and computing required to work at scale. The public geotessera Python client and an open tile registry make the data straightforward to access and verify.

What the AWS Open Data Sponsorship Program provides

The AWS Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on AWS, working with data providers to democratize access to data, lower the cost of working with it, and encourage communities to build on shared resources. For TESSERA, this support makes two things possible: completing a one-time global processing pass to finalize historical coverage, and hosting the resulting embeddings on Amazon S3 with requestor-friendly access so that anyone, anywhere, can use them without egress costs.

Completing the historical record matters because most environmental questions depend on consistent, multiyear comparison. Whether a forest is shrinking, a region’s soils are gaining or losing carbon, or cropland is under stress can only be answered by looking across years. Making a global, comparable, analysis-ready archive openly available is a meaningful step toward democratizing that capability.

Real-world impact

Organizations are already using TESSERA in the field. Arbol is using TESSERA foundation models to bring new climate insurance products to market in underserved regions where traditional insurers are retreating, and where limited data availability and modeling capability have long made these risks difficult or impossible to underwrite. TESSERA converts years of satellite observation into consistent, analysis-ready signals for every 10-meter patch of land, which gives underwriters the ground-level view needed to structure and price coverage for perils such as drought, flood, wildfire, and crop failure in markets that have historically gone unprotected.

With open access, we expect the range of applications to grow well beyond what any single organization could build. Some of the sectors likely to benefit first include:

• Climate and conservation research – For monitoring deforestation, biodiversity, and ecosystem change, including in regions that have historically lacked consistent observation
• Agriculture and food – For assessing soil health, crop conditions, and yield without relying solely on costly fieldwork
• Carbon and restoration – For verifying project outcomes with independent, high-resolution evidence
• Insurance, lending, and the public sector – For understanding land and natural-risk exposure with greater clarity

These embeddings also power CYCLOPS, Arbol’s land and nature intelligence unit led by Dr. Atzberger, which applies TESSERA to soil health, biomass, yield, and land-use analysis. It’s an example of how an open foundation can support both public research and applied tools.

“The bottleneck in Earth observation has never been satellites—it’s been the cost and complexity of turning raw imagery into something a scientist or developer can actually use. TESSERA clears that bottleneck. By making a decade of analysis-ready, 10-meter embeddings freely available on AWS, we’re collapsing the infrastructure burden that has kept advanced Earth observation out of reach for most organizations. We’re proud to host it.”

– Chris Stoner, open environmental and geospatial data lead, AWS Open Data

Get started

TESSERA’s global embeddings are available through the Registry of Open Data on AWS. You can access the data on Amazon S3 using the open source geotessera Python client, explore the tile registry for reproducibility and integrity verification, and join the growing community of researchers and developers building on open Earth observation data.

To learn more about the Amazon Sustainability Data Initiative, you can visit the Sustainability Exchange page. You can also learn more about Open Data on AWS to find out how you can access and use large datasets to advance your organization’s own initiatives.

We’re excited to see what the community builds. Open, analysis-ready Earth data has the potential to do for environmental science what open data has already done for fields such as genomics and astronomy, which is to turn a specialized, resource-intensive discipline into a shared solution anyone can build on.