Preliminary Result of 3D City Modelling For Hanoi, Vietnam

Abstract

Hanoi is the one of the fastest-growing cities in Vietnam, which sets the target to turn into a smart city in 2030. Nowadays, 3D city models are being increasingly employed for many domains and tasks beyond visualization, then it will take an important role in smart city. In order to develop 3D city models, 2D geographic data such as building footprint and building height attribute are required. However, the lack of the height attribute for various types of building and low performance of rendering and visualizing 3D city models are two big remaining problems. In this paper, available data from open sources is used to predict the building height. The prediction has carried out with machine learning techniques using the combination of different attributes. After that, the models will be created using 3D tiles specification to improve the visualization performance. The preliminary results of the proposed method highlight the potential of generation of massive 3D city models from the available data in Vietnam.