Urban tree mapping provides cities with a structured and continuously updated dataset, enabling better maintenance planning, risk identification, and long-term urban forest management. Rome has entered the final phase of its urban tree mapping programme, covering approximately 84,000 public street trees across the city.
The scale of the challenge
Rome manages one of the most complex public tree networks in Europe. Its urban forest spans historic districts in the city centre, major arterial corridors, and suburban neighbourhoods that stretch across a vast municipal footprint. The trees are diverse in species, age, and condition and they sit within one of the world’s most demanding urban environments, where infrastructure pressures, heritage constraints, and intense public use all intersect.
At that scale, the core operational challenge is not the trees themselves, it is information. Without consistent, verified records covering every tree, inspection teams work from incomplete data. Maintenance budgets are allocated on intuition as much as evidence. Risk assessments are reactive rather than planned. And when conditions change — after a storm, after a disease outbreak or a construction project — there is no reliable baseline to measure against.
The question Rome faced is one that every large city eventually confronts: how do you manage a living, distributed, constantly changing asset network with the rigour of infrastructure, when the data to do so has never existed in one place?
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84,000 Public street and park trees captured in this phase |
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Unified per-tree record system replacing fragmented data |
Ongoing Structured for repeat capture cycles, not a one-off inventory |
The approach: structured capture at city scale
To address this, Rome initiated a structured capture programme using greehill Trees, with street-level scanning carried out by partner R3GIS across selected districts of the central and suburban street network.
The methodology was precise by design. Rather than relying on manual survey or aerial imagery alone, R3GIS deployed street-level LiDAR scanning to capture each tree with positional accuracy and enough structural detail to support condition assessment. That raw capture was then processed into the greehill Trees platform, where each tree becomes a digital twin: a structured record connecting imagery, precise geolocation, structural attributes, and condition indicators in a format built for operational use.
The scope of this phase — 84,000 public street and park trees — makes it one of the largest city-scale urban forest capture programmes in Europe. But the size is less significant than the approach. This was not designed as a one-off census. It was built as the foundation layer of a repeatable, updatable system.
“The objective was not to count trees. It was to establish a per-tree record that could support inspection planning, prioritisation, documentation, and repeat updates — all within one system.” Sven König, Vice President Europe greehill
What each digital twin contains
Every tree captured in the greehill Trees platform holds a structured record designed for operational use across city departments. The record is not a photograph or a map marker. It is a linked dataset connecting multiple layers of information about a single tree.
PER-TREE DIGITAL TWIN — DATA LAYERS
| Street-level imagery | Precise geolocation |
| Structural attributes | Condition indicators |
| Inspection history | Maintenance records |
| Risk assessment flags | Reporting outputs |
That combination — precise location, structural data, and condition status in one accessible record — is what makes the system operationally useful rather than merely informational. City teams working on inspection planning do not have to cross-reference multiple systems or interpret incomplete historical records. The data they need is in one place, structured for the decision at hand.
Why Urban Tree Mapping Matters for Cities
The greehill Trees platform is designed to support the full operational cycle of urban tree management, not just the initial data capture. In Rome, the system now underpins four core workflows.
01 Inspection planning. Teams can identify which trees require inspection based on condition data, structural risk indicators, or time since last assessment, rather than relying on scheduled routes or reactive callouts. This makes inspection resource allocation significantly more efficient at city scale.
02 Maintenance prioritisation. With verified condition data for 84,000 trees, Rome can make evidence-based decisions about where to direct maintenance budgets. Trees that require urgent intervention can be identified and prioritised against those where work can be deferred, reducing both risk and unnecessary expenditure.
03 Documentation of completed work. As maintenance is carried out, records are updated within the same system. This creates an auditable history for each tree, important both for liability management and for understanding how the urban forest evolves over time.
04 Reporting outputs. City administrations increasingly need to report on green infrastructure to funders, regulators, and citizens. A verified, structured dataset makes that reporting faster, more accurate, and more credible, whether for climate resilience programmes, EU funding requirements, or public transparency obligations.
Built for continuity, not just completion
One of the most important design principles behind the Rome project is that the record is structured for repeat capture cycles. This is what distinguishes an urban forest digital twin from a conventional tree inventory.
A traditional inventory produces a snapshot. It reflects the state of the urban forest at a point in time and then it ages. Within a few years, conditions have changed, trees have been removed or added, and the data no longer reflects reality. Cities that rely on such inventories find themselves commissioning new surveys every few years, effectively starting from scratch each time.
The greehill model works differently, because each record is structured around a persistent per-tree identity, subsequent capture cycles do not replace the dataset, they update it. The same tree record carries forward its full history, with new condition data, inspection notes, and structural assessments added over time. This creates longitudinal data: the ability to track how individual trees, districts, and the whole urban forest change across years and decades.
For Rome, this means that the investment made in this phase is not a one-time cost. It is the foundation of an evolving system that becomes more valuable with each subsequent update cycle.
| Traditional inventory | greehill digital twin |
| Snapshot in time | Living, updatable record |
| Degrades as conditions change | Updates on each capture cycle |
| Requires full re-survey every few years | Carries full history forward |
| No longitudinal data | Builds longitudinal insight over time |
| High recurring cost with no continuity | Foundation investment that compounds in value |
What this means for city leaders
The implications of a complete urban forest digital twin extend well beyond the parks and green spaces department. For city administrations, this kind of verified, city-scale dataset directly supports several strategic priorities.
Climate resilience planning increasingly requires cities to demonstrate what their green infrastructure actually delivers in terms of carbon sequestration, urban heat island mitigation, stormwater management, and biodiversity support. Without a reliable baseline, those claims are difficult to substantiate and impossible to track over time. A digital twin provides that baseline.
Budget accountability is another driver. As cities face pressure to demonstrate the value of public expenditure, the ability to show that maintenance resources are allocated based on verified condition data becomes a significant governance advantage.
And risk management becomes fundamentally different when you have a complete, current picture of your urban forest. The difference between knowing which trees are at structural risk and not knowing is not just operational, it is a liability question.
Rome as a model for city-scale urban forestry
Rome is not the first city to invest in urban forest data, but the scale, structure, and operational focus of this programme make it a significant reference point for how cities can approach urban forest management as infrastructure.
The combination of partner-supported street-level scanning (R3GIS), a data-driven operational platform (greehill Trees), and a record architecture designed for long-term continuity gives other municipalities a clear model to consider. The technology is proven, the operational workflows are defined and the data is actionable from day one.
As the programme extends into additional districts and subsequent capture cycles, Rome’s urban forest digital twin will become an increasingly complete picture of one of Europe’s most complex and historically significant urban tree networks and a demonstration that large-scale urban forestry can be managed with the same precision as any other city infrastructure.
Project scope
| City | Rome, Italy |
| Trees captured | 84,000 public street and park trees |
| Coverage | Selected districts across central and suburban street networks |
| Delivery model | Partner-supported implementation (R3GIS, Italy) |
| System | greehill Trees |
| Record type | Per-tree digital twin with imagery, location, structural attributes, condition indicators |
| Update model | Structured for repeat capture cycles |
| GET IN TOUCH
What could a complete urban forest digital twin look like for your city? We work with municipalities across Europe to build verified, city-scale tree datasets that support long-term operational use — from initial capture through to ongoing update cycles. Visit greehill.com to request a demo or speak with our team. |
greehill · Urban Forest Intelligence · greehill.com · Implementation partner: R3GIS, Italy
