From sub-optimal datasets to a CityGML-compliant 3D city model: experiences from Trento, Italy

Abstract. More and more cities are moving towards the creation and adoption of three-dimensional virtual city models as a means for data integration, harmonisation and storage. To this purpose, CityGML is an international standard conceived specifically as information and data model for semantic city models at urban and territorial scale. The automatic building reconstruction process, up to the Level of Detail 2 (LoD2) can be achieved nowadays nearly completely automatically and with a high degree of accuracy, provided that high quality input data (e.g. a dense DSM obtained from LiDAR or dense stereo-matching with 10÷15 pt/m² or better) are provided. This paper deals indeed with the creation of a CityGML-compliant, LoD2 city model starting from sub-optimal datasets and tries to address some of the issues tied with the use of sub-standard data – which however, represents a quite common case in “real life”. As study area, a part of the city of Trento, in the northern Alpine region of Italy, was chosen and contains about 2300 buildings of different typology, use and construction year. Only existing datasets were gathered and used.