Instead of relying on 2D constructs such as zoom levels, 3D Tiles are based on geometric error for Level-Of-Detail (LOD) selection and a tunable pixel error. This allows performance/visual-quality tuning and is built for multiple “zoom levels” in the same view.
Web Mercator is not ideal for 3D because the poles project to infinity and also because the NGA does not recommend Web Mercator for DoD application. In contrast, in 3D Tiles the tiling scheme is adaptable, in all three dimensions, depending on the models in the dataset and their distribution.
Additive refinement has the additional benefit that child tiles can be rendered as they are downloaded, as opposed to replacement refinement, which requires that all of a parent’s children be downloaded first. 3D Tiles allow both replacement and additive refinement.
In addition to supporting the 3D counterparts of points, polylines, and polygons, vector tiles will support 3D geometries such as boxes and cylinders and a general 3D mesh. The intersection of these 3D volumes with another 3D tileset—such as terrain or a photogrammetry model— defines the surface of the vector tile and allows the vector tile to bring multiple non-uniform layers of shading and semantics to a 3D tileset.
Supporting heterogeneous datasets with both inter-tile (different tile formats in the same tileset) and intra-tile (different tile formats in the same Composite tile) options allows conversion tools to make trade-offs between number of requests, optimal type-specific subdivision, and how visible/hidden layers are streamed.
At runtime, a tile's geometricError is used to compute the screen space error (SSE) to drive refinement.Note that the viewer's height above the ground is rarely a good metric for 3D since 3D supports arbitrary views.