Mato Grosso do Sul, Brazil. Captured by EDC April 2026.
Last week at Tech Hub Live, I had the opportunity to speak with agronomists, ag retailers, technology leaders, and innovators about a topic that has interested the agriculture industry for years: satellite imagery.
Before getting into the takeaways, I want to thank the Tech Hub Live team and this year’s sponsors for creating a venue where meaningful conversations about the future of agriculture can happen. Events like this bring together many of the people shaping how technology creates value in the field, and I appreciated the opportunity to be part of the discussion.
My talk focused on a simple observation: We have had access to satellite imagery for decades, yet it still has not been fully operationalized at scale.
Why has such a powerful technology struggled to become part of everyday agricultural decision-making?
The agriculture industry has understood the value of satellite imagery for years. It can show how crops are developing, where fields are behaving differently, and where stress may be starting to emerge.
The difficulty has been using that information consistently across a large customer base.
In many organizations, imagery is still used by a specialist team or within a limited pilot. Expanding it across thousands of fields means dealing with processing, storage, system integration, and ongoing support throughout the season.
Some companies try to build those capabilities in-house. Others buy tools that solve part of the problem but still require additional work to fit existing systems. Both approaches can become expensive and difficult to maintain once the program starts to grow.
Many organizations therefore find themselves choosing between something highly capable but complex and something easier to deploy but difficult to scale.
One of the biggest themes I discussed at Tech Hub Live was the gap between successful pilots and successful deployment. Most ag technology professionals have experienced this firsthand.
A new technology generates excitement. A pilot is launched on a limited number of fields with a group of innovative growers. The results look promising, and the value proposition appears clear.
The difficult question comes when the organization tries to scale. What works across 50 fields often becomes significantly more challenging across 150,000. The economics begin to change as well, with costs to get started, expand the program, and keep it running over time.
Eventually, the effort required to use the technology can exceed the value most users consistently extract from it, and adoption stalls. The technology may have worked, but the operational burden became too great to sustain. That is why so many promising agricultural technologies never move beyond the pilot phase.
Analysis Ready Data, or ARD, has helped remove some of the friction involved in working with satellite imagery. Teams no longer have to begin with raw data and carry out every calibration and correction themselves. Much of that work has already been done, making the data quicker to use and easier to compare over time.
That is especially useful for organizations without large geospatial teams. But it addresses only the first part of the workflow. The data may be ready for analysis, while the systems needed to turn it into an alert, recommendation, or business decision still have to be built.
Even when imagery is analysis-ready, organizations still need systems that transform information into action. They need workflows, analytics, automation, and business processes that connect imagery to decisions.
In many cases, the most expensive and complex part of the system still sits between the data and the decision.
I believe the industry is now entering a new phase, with more attention being placed on what it takes to make imagery operational.
At Tech Hub Live, I shared how EarthDaily is approaching this challenge through consistent time-series collections, expanded spectral information, daily global coverage, and fully calibrated and harmonized datasets.
For organizations working across large agricultural networks, this changes where time and resources are spent. Teams can devote less effort to processing and managing imagery and more to agronomy, customer needs, and the applications built on top of the data.
For many organizations, that could make satellite data much easier to use across the business.
For agronomists and ag retailers, operational imagery has the potential to change the economics of decision-making. Many professionals currently spend valuable time reviewing imagery, identifying issues, and determining where attention is needed.
When imagery is consistently available and integrated into existing workflows, agronomists can:
The benefits show up in how quickly issues are identified, how efficiently teams use their time, and how well recommendations are delivered to growers.
One of the most exciting parts of the discussion was what becomes possible as the data layer becomes more reliable. When imagery is consistent, trusted, and continuously available, organizations can begin moving beyond monitoring.
The progression can move from monitoring to intelligence and, eventually, to automation. Reliable time-series datasets support advanced analytics, which can then power predictive models and more informed decision-making at scale.
The question I kept coming back to at Tech Hub Live was which decisions we may be ready to automate as imagery becomes easier to access, integrate, and use.
We are still early in that transition, but it depends on having consistent Earth observation data available throughout the season.
My core message at Tech Hub Live was that the future of satellite imagery will depend on how effectively it supports better decisions.
The agricultural industry has access to more data than ever. The unresolved issue is scale. A pilot may work well, but extending the same service across a retailer’s full territory can quickly become too expensive or difficult to manage. Reducing that burden is what allows imagery to become part of routine agronomic work.
For agronomists and retailers, that could mean seeing changing conditions earlier and directing their time and resources to the fields that need attention.
That is the future I see for Earth observation in agriculture, and it was valuable to explore these ideas with the Tech Hub Live community.
Learn how EarthDaily helps agricultural organizations use Earth observation at scale, from consistent data delivery to operational insights across large farming regions.