Mobile mapping is the research trend in the mapping field due to its superior time efficiency compared to traditional fixed mapping methods. It is an important digital base for numerous applications, such as high-definition (HD) maps, digital twins, smart cities. However, most mobile mapping datasets are based on portable platforms, such as backpacks and robotics, leading to insufficient research on large-scale mobile mapping and autonomous driving. To change the status quo, a multimodal sensor dataset from a vehicle-mounted mobile mapping system for comprehensive urban scenes (MSD-VMMS-HK) is provided. It has rich, high-precision, and large-scale multimodal sensor information, including high-precision (millimeter-level) light detection and ranging (LiDAR), the panoramic camera, and GNSS/INS. The MSD-VMMS-HK dataset features a wide variety of scenarios in Hong Kong, which is a representative urban area with diverse and comprehensive challenging urban scenes like mountain tunnels, cross-harbour tunnels, urban canyons, mountain and seaside roads. It is the first urban-level comprehensive urban scenes dataset that provides high-precision references for the validation of point clouds and image processing. Additionally, examples of various applications of the dataset, such as accurate mapping of urban canyons, urban infrastructure management and maintenance, and change detection, are provided to facilitate reference by the academic community.
Lu et al. (Wed,) studied this question.