Integration of Multi-scale Spatial Digital Twins in Metaverse Based on Multi-dimensional Hash Geocoding

With the popularization of the metaverse, virtual reality mapping technology based on digital twins has generated a large amount of spatial data. These data are multidimensional, multi-scale, mobile, and distributed. In order to fully utilize these data, we propose a non mutation multidimensional hash geocoding that can organize and store data with geographic features, and achieve data mapping at different scales from macro to micro. The mapping between them can achieve joint utilization of data of various scales. On this basis, we propose a block network secure storage mapping model for spatial digital twins, which can securely and reliably organize and map spatial data. This article also looks forward to the possible emergence of digital twins of different dimensions and scales in the future metaverse, and proposes an adaptive 3D reconstruction method based on this to adapt to digital twins models of different scales in the metaverse. On the basis of our work, we will further promote the development of the spatial digital twin metaverse.