The Earth observation industry has experienced an extraordinary period of innovation. Higher resolution imagery, shorter revisit times, radar, LiDAR, aerial photography, drones and an expanding range of sensing technologies have transformed our ability to observe the physical world. The progress has been remarkable, and the industry deserves enormous credit for achieving what only a few years ago seemed impossible.
Success, however, has a habit of changing the problem.
The objective throughout much of the industry's history was clear. We needed to observe more of the world, more frequently and in greater detail. Companies such as Planet, Nearmap and Airbus Defence and Space have played a significant role in transforming what is now possible, delivering higher resolution imagery, more frequent revisits and increasingly sophisticated sensing capabilities. Those advances have fundamentally changed our ability to observe the physical world.
That objective has largely been achieved.
Large infrastructure organizations now have access to an unprecedented volume of observational data. Satellite imagery, aerial photography, radar, LiDAR, drones and operational sensors continuously generate new observations across entire networks. Access to information is no longer the primary constraint. Determining which observations warrant attention, and which can remain observations, has become the more significant challenge. This distinction will define where the next generation of enterprise value is created.
Access to information is no longer the primary constraint. Determining which observations warrant attention, and which can remain observations, has become the more significant challenge.
A simple analogy illustrates the point. Imagine standing on a hill overlooking a valley. You can see everything in front of you, yet very little of it matters at that moment. If someone tells you there is a wildfire beginning on the eastern ridge, your attention immediately shifts. The landscape has not changed. Your understanding of what is important has.
That, in my view, is where Earth observation is heading.
Every image contains thousands of observations. Every survey reveals change. Every new sensing technology increases visibility. None of these developments are negative; they represent the continued success of the industry. The challenge is that every additional observation competes for finite operational resources. Engineers, inspectors, maintenance crews and compliance officers cannot investigate everything they can now see, nor should they.
This is why the next stage in the evolution of Earth observation is not about generating more observations. It is about rationalizing observational intelligence.
The objective should not be to catalog every change across a network or a city. The objective should be to identify the relatively small number of observations that are most likely to influence an operational outcome. That is a fundamentally different problem. It requires understanding consequence rather than simply recognizing change.
The distinction becomes obvious when viewed through the lens of day-to-day operations. A municipality responsible for thousands of properties does not need another satellite image showing every visible alteration. It needs to identify the handful of changes that are most likely to represent unauthorized construction, easement encroachments or other matters that warrant investigation. A utility does not need another dashboard filled with anomalies. It needs confidence that field crews are being directed towards observations that are most likely to affect safety, reliability or network performance.
This is where enterprise value begins to shift.
As observational data becomes increasingly available, the observation itself becomes only part of the value chain. The greater opportunity lies in transforming observations into operational priorities. Organizations will increasingly differentiate themselves not by how much they observe, but by how effectively they convert those observations into better decisions about where to deploy people, capital and operational resources.
At KartaSoft, this thinking has shaped the way we approach the problem. We combine multiple observational datasets across very large geographic areas to identify meaningful ground disturbance and reduce what would otherwise be an overwhelming search task into a focused operational workflow. The purpose is not to replace operational judgment. It is to ensure that judgement is applied where it has the greatest impact.
The implications extend well beyond any single company or technology platform. It suggests that the next phase of Earth observation will be defined by the relationship between observation and decision-making. Imagery will continue to improve. Sensors will continue to improve. Artificial intelligence will continue to improve. Those advances are inevitable and welcome. The organizations that create the greatest long-term value, however, will be those that help operators determine which observations matter, why they matter and what should be done next.
That is the opportunity that now sits before our industry. We have become exceptionally good at observing the world. The next challenge is helping the world decide where to look.
If this perspective resonates with you, I'd welcome the opportunity to continue the conversation. If you're interested in exploring these ideas further, I'm also happy to share a copy of the Category Paper that first articulated this thinking.
The KartaSoft team will be attending the International Pipeline Conference & Expo (IPCE) in Calgary, Canada, 21–25 September 2026. If you'll be there, we'd be pleased to meet and continue the conversation.
Conference details: IPCE 2026.