An environmental model is only as good as the spatial data beneath it. TT prepares that data: we survey it, clean it, structure it and make it fast to query. The technical director holds a PhD in Geodetics and Geomatics from the Polytechnic University of Milan, with a focus on advanced GIS, remote sensing, management of large geographic datasets and automated classification of satellite imagery.
Problems we solve
A national noise model has to process the ground cover of a whole country in a reasonable time. An international organisation has to publish large geographic datasets through web services that can take the load. A motorway operator needs a three-dimensional model of its network for design and assessment. A city wants to know which roofs are suitable for solar panels. These are different problems with the same root: large volumes of spatial data that have to become reliable information.
Services
We process Lidar and photogrammetric surveys, extract roads, buildings and other features from point clouds as vector data, design geospatial databases and their management policies, build automated processing pipelines and vector tile services, develop custom QGIS plugins, and produce solar potential maps and population exposure analyses.
We work with open software: QGIS, GRASS, PostgreSQL with PostGIS and R, plus ArcView where the client requires it. We write code in Python, JavaScript, Perl and bash, and deploy services in Docker containers. We have also worked with Azure Blob Storage and with hyperspectral imagery from satellites and drones.
Reference projects
Parked-train noise across Europe (International Union of Railways). AI-assisted satellite validation of train parking locations, combined with population grids. Case study.
DEFRA, United Kingdom. Best practice for processing ground cover over 90,000 km² for noise modelling: the proposed QGIS and PostGIS algorithm made processing about 1,000 times faster.
UNDP SDG GeoHub. PostGIS data architecture and cloud pipelines serving vector tiles on demand. Case study.
Motorway Lidar. Laser scanning and photogrammetric survey of 702 km and 1,377 km of the Autostrade per l'Italia network and processing of 200 km of the Autovie Venete network: 2,279 km in total, with project management, GIS development and data quality control.
Interreg CO ADRIA (Municipality of Udine). Solar potential mapping of Udine and Monfalcone in QGIS, with a plugin developed for the project.
Other work: the GIS system that extracts roads and buildings from Lidar point clouds for three-dimensional noise models, and the final checks and geodata migration for the fourth round of noise mapping of the Environmental Protection Agency of Ireland.
