Written by: EAASI (European Association of Aerial Surveying Industries)
From Fragmented Data to an Integrated Urban Platform
Piacenza is a city of roughly 100,000 residents in Italy’s Emilia-Romagna region, about an hour southeast of Milan by train. Historically an agricultural and industrial hub along the Po River, it’s now the site of one of Italy’s more ambitious municipal digital twin projects — giving city officials a centimeter-accurate, georeferenced 3D model designed to unify municipal databases that were previously siloed and disconnected.
The project was delivered by EAASI Member CGR SpA in partnership with AeroDron, combining crewed aerial, UAV, and mobile mapping system (MMS) surveys into a single, interoperable dataset. Survey data was collected between September 2025 and May 2026, with the completed platform publicly presented in Piacenza this past May. The goal: a virtual model precise enough to support predictive maintenance, resource management, and simulation of complex urban scenarios — moving the city from fragmented recordkeeping toward an integrated digital infrastructure.
Fusing Aerial, UAV, and Ground-Based Survey Data
To capture Piacenza’s territory from every angle, the project team combined two complementary acquisition methods:
· Crewed aircraft and UAV flights, collecting zenithal and oblique-zenithal imagery for top-down mapping of rooftops, streets, and open spaces.
· Mobile Mapping System (MMS) surveys, conducted at street level to capture detail inaccessible from the air, including building façades and features obscured by tree canopy.
All flight and ground operations were carried out under controlled conditions — clear skies, no fog, and no low-angle sunlight — to avoid shadows and glare that could compromise the accuracy or visual clarity of the resulting data.
The fusion of these datasets produced photorealistic LiDAR point clouds paired with 360-degree spherical imagery, eliminating the blind spots that typically result from relying on a single survey method.
Classification: From Raw Data to Structured Assets
Once collected, the raw point clouds and imagery were processed through a pipeline combining machine learning classification with human quality review. The result is a set of independent vector layers cataloging individual urban assets, including:
· Mobility and safety infrastructure: traffic lights, signal heads, gantries, and both vertical and horizontal road signage
· Urban furniture and services: streetlights, benches, waste bins, and public transit shelters
· Utilities: service boxes, technical cabinets, and roadside equipment
· Pavement condition: potholes and surface deterioration
· Green space and addressing: trees, trunks, green areas, and house numbers
In total, the classification effort catalogued more than 12,500 trees, 19,000 manholes, and 23,000 road signs — figures that illustrate the granularity of the resulting asset inventory.
GIS Integration and a Single Point of Data Access
Rather than existing as a standalone visualization, the digital twin is built into a single, interactive map in which all municipal data carries a precise geographic location, allowing for immediate consultation and automatic updates. The model is fully interoperable within AeroDron/CGR’s web-GIS platforms — viewable and accessible from any device — and exportable in standard formats to other GIS systems.
That interoperability is designed to support three things: day-to-day consultation by technicians and decision-makers, cross-departmental sharing between offices such as urban planning, public works, and security, and integration into open data portals and municipal geoportals.
Data acquisition and platform development were paired with staff training for municipal employees, on the premise that a digital twin only delivers value once it becomes a daily operational tool rather than a one-time deliverable. Project leads describe the effort as having built cross-functional synergy among municipal offices that previously worked with separate, disconnected datasets.
From Asset Mapping to Administrative Management
Beyond the asset inventory itself, the platform is being used to support a range of administrative and operational workflows, allowing staff to complete tasks that once required fieldwork remotely:
· Driveway verifications: rapid dimensional checks that speed up processing of building permits and local tax assessments
· Urban and altimetric controls: measurement of façade heights and building volumes, reducing fieldwork evaluation errors and helping ensure compliance of new developments
· Automated road bill of quantities: calculation of asphalt volumes for milling or paving, with altimetric cross-sections generated directly from the 3D model
· New project simulation: 3D rendering of proposed public works and temporary installations within the model, used both for public communication and technical documentation in tender processes
· Building inspections: condition assessment of historical roofs and façades using 5K aerial imagery, removing the need for scaffolding or aerial platforms and reducing high-altitude work risk for inspection staff
· Green space management: 3D monitoring of the urban tree inventory to inform pruning schedules, assess plant stability, and manage city parkland
Looking Ahead
Piacenza’s digital twin adds to a growing list of Italian cities — including Milan — investing in centimeter-accurate urban 3D models built from combined aerial, UAV, and mobile mapping data. What distinguishes Piacenza’s approach is the emphasis on turning the model into daily administrative infrastructure, not just a planning reference: municipal staff are already using it for permitting, inspections, and asset management. As municipalities face increasing pressure to modernize infrastructure management and plan for climate resilience, projects like Piacenza’s offer a template for how mid-sized cities can build practical, staff-facing tools on top of high-precision geospatial data.
