Northern Netherlands leader in autonomous green space management

What happens when mowing is no longer a periodic action, but a targeted intervention based on real-time data? In the Northern Netherlands, companies, knowledge institutions and site managers are working together on that change.

The Netherlands has 4.2 million hectares of land, about half of which is actively managed. Roadsides along national roads, dikes, ditch banks, water courses, solar parks and sports fields require annual maintenance.

The management of those areas is under pressure. Personnel are scarce and seasonal work is physically demanding and increasingly difficult to fill. Professional knowledge about plant species, ecological value and the right mowing strategy is often in the heads of experienced employees and disappears when they leave. At the same time, demands are increasing. Governments have to comply with biodiversity objectives from European and national legislation, while daily implementation practices are still insufficiently geared to this. Traditional management is crude: periodic mowing, little distinction between species and limited visibility of what is growing underwater or between solar panels.

Autonomous systems enable a different way of working. By first accurately observing what is growing and living and then intervening only where necessary, management becomes more selective, data-driven and more feasible at scale. Biodiversity thus becomes not just a policy goal, but a control variable in implementation.

In the Northern Netherlands, the technology, machinery and knowledge to make this change are already available. Within the cluster Autonomous Green Management these forces are brought together in a focused way.

Autonomous systems are changing the way green space is managed. First, they observe exactly what is growing and living, with sensors, drones and AI. Then they intervene only where necessary. Not everything is lumped together, but selectively, targeted and data-driven.

This shifts the starting point of management. Mowing is no longer just a periodic maintenance task, but a targeted intervention based on current information. Biodiversity thus becomes a control variable. An autonomous mower that recognizes flowers on a roadside does not mow over them. A raking boat that maps submerged aquatic plants removes only the invasive species. A robot that distinguishes crop from weeds leaves valuable plant species in place. The system no longer exclusively follows a schedule, but responds to what actually grows and lives there.

What still sounds experimental to some is already partly operational in practice. In the Northern Netherlands, companies are working together to further connect these applications and make them deployable at scale.

In watercourses, drones that map submerged aquatic plants are already being used. Based on color indices and image analysis, AI models recognize different species and project them as digital layers over the water. This allows the operator on the boat to see not only where plants are growing, but also which species require attention. Manual inventory beforehand is no longer necessary.

The next step is an extension of that: a raking boat that is controlled not only by experience, but by actual data. That technology is currently being developed. As an intermediate step, work is already underway on a remote-controlled boat that responds directly to the analyzed images. The movement from observation to targeted intervention has thus already begun.

At solar parks, other issues come into play. Autonomous mowers move between thousands of posts, in areas where satellite reception is often interfered with by the panels themselves. Combining lidar, cameras and alternative navigation techniques provides accurate positioning without relying on GPS.

These same systems record their activities, detect obstacles and make management more predictable and safer. In parallel, inspection technology is being used to self-monitor panels. Thermal imaging cameras detect glass breakage or closure problems early, before they lead to failure. Where manual inspection relies on snapshots, continuous monitoring makes anomalies visible as soon as they arise.

In organic arable farming, robots are already being used to distinguish crop from weeds, without chemicals and without the heavy seasonal work that traditionally comes with it. AI models recognize plant species in real time and direct the machine to intervene only where necessary. In the process, perception, intelligence and action are directly linked: sensors see what is growing, software interprets that information and the machine responds accordingly.

The same technology is applicable in roadside management. Flowers can be recognized and spared. Nests are detected before they are driven over. Invasive species are targeted for removal instead of broad mowing. What happens in the field today can contribute to biodiversity along roads and dikes tomorrow.

Autonomous systems function not only thanks to mechanics or sensors, but through the translation of images and signals into usable decision information. That software layer forms the link between observation and execution.

Horus develops mobile mapping technology that translates sensor data from cameras, lidar and GPS into geographic information that machines can use to navigate and make decisions. That technology is applied in a variety of markets, from infrastructure to defense, and within the cluster finds direct application in green space management.

Working together on future-proof green management

The applications visible in the region are not isolated. In the Northern Netherlands, companies have been working for years on various components of autonomous green and water management: from machine building and vision software to data analysis, ecological expertise and system integration. Connecting this expertise creates a chain in which observation, analysis and implementation are connected.

This collaboration shortens development time, avoids duplication of effort and allows innovations to be tested and scaled up more quickly. What is valuable individually gets more impact when combined.

EDIH Northern Netherlands facilitates these connections and supports knowledge sharing, matchmaking and access to computing power and research facilities. This creates an ecosystem in which technological development is directly linked to practical application.

The ambition to become a leader in autonomous green space management in Europe is not a loose promise, but a logical extension of what is already happening in the Northern Netherlands. The region has a strong combination of mechanical engineering, robotics, vision technology, geodata and knowledge. Water boards, provinces and land managers offer space to test innovations in practice. Standardization around aquatic plant management and participation in European research projects strengthen that position.

The distinction lies in the way knowledge, technology and implementation are deliberately linked here. This creates scale and cohesion in a field that is traditionally fragmented.

The applications running today are not an end point. They are the foundation for what the Northern Netherlands can do in Europe. The technology is there. The practical experience is growing. The cooperation stands. The next step is scaling up.

Do you have a management challenge, a solution or just a question? Hans Praat and Maarten Groeneveld are happy to think along with you. Details are here at the top right.