3D city models have become an important piece of geoinformation. They are available in different Levels of Detail (LoD), which determine the amount of complexity provided in the model. LoD1 city models represent simple prismatic building volumes and are typically produced by means of remote sensing. In this article, we investigate the possibility for country-wide reconstruction of LoD1 city models from TanDEM-X intensity images by utilizing deep learning-based single-image height and building footprint reconstruction. As study area, we use the land surface of the country of Denmark. Our results show the general potential of this AI-based approach of country-wide city model reconstruction, which can serve as a data-efficient pipeline that is particularly well-suited in time-critical scenarios or for the exploitation of archive imagery of satellite missions with global data coverage.