In recent years, semantic 3D city models have been increasingly used for large scale urban analysis in urban digital twins and smart cities. As a crucial component, semantic 3D streetspace models have gained attention due to the growing availability of road and transportation infrastructure data. However, these models exist in various data formats, such as point cloud data and BIM models, each designed for different use cases, making integration and management challenging when diverse models need to be utilized together for further applications. To address this, we develop a workflow to transform heterogeneous streetspace component representations into an integrated semantic 3D model based on the international standard CityGML 3.0, which serves as a hub for integrating different geometric and semantic features. A case study in City X, Country Y was conducted by integrating BIM, GIS, and point cloud data. The case study area features complex streetspace components, including roads, bridges, and tunnels. This study demonstrates the feasibility of harmonizing complex urban environments with multiple types of models for streetspace components. Challenges encountered in the transformation process are discussed, along with future research directions further to enhance the integration of semantic 3D streetspace models.