CityGML-based 3D GIS visualization in the cloud environment

CityGML provides an effective approach to the sharing and inoperability of 3D GIS spatial data. However, due to the large amount of data, CityGML’s resolving, transferring, and rendering processes during visualization are inefficient in a standalone system, causing considerable delays in viewing the information of large 3D maps for users. The cloud computing technique is introduced to address these problems in this paper. The Hadoop Distributed File System (HDFS) is employed to store the huge amount of CityGML data. A MapReduce-based parallel CityGML data visualization scheme is proposed. A Hadoop-based public cloud for a 3D city information service is constructed in the cloud, allowing cloud users to interact with the cloud via the service interface and obtain the desired highquality 3D city scenarios. The visualization effectiveness and interoperability efficiency of the large-scale CityGML 3D virtual city data are improved.