Creation OGC standard 3D Tiles automatic and hierarchically from 3D geographical data

3D Tiles is a standard developed for representing and storing 3D data in geographic information systems. In addition to traditional 2D maps and images, the use of 3D data is also rapidly increasing with increasing demands. However, large and complex 3D data can be difficult to effectively store, process and transfer. 3D Tiles was developed to overcome these challenges. This standard hierarchically organizes and segments large amounts of 3D data, making it possible to load and process data faster. Within the scope of the thesis, automatic and hierarchical conversion of 3D geographical data into 3D Tiles format, which is the OGC (Open Geospatial Consortium) standard, was examined. OGC is an organization that develops international standards for geographic information systems and location-based services. Within the scope of the study, an application that is both open source and does not require any intervention until the data conversion stage into 3D Tiles sets has been developed. This application has the ability to perform hierarchical partitioning according to data density. In the thesis study, QuadTree, Octree, Kd-Tree, R-Tree and the proposed Optimized QuadTree algorithms were applied to solve the hierarchical partitioning problem. The results obtained by using these algorithms; The most ideal partitioning method was determined by comparing creation times, tree structure and file sizes. As a result, this study has made a significant contribution to the literature in the automatic and hierarchical conversion of 3D geographical data into 3D Tiles format. The results obtained were successful in the efficient flow and conversion of large-scale 3D geographical data into 3D Tiles sets. This transformation process; It is open source, does not require intervention and has the ability to perform hierarchical partitioning according to data density and offers more efficient results in terms of rendering times and file size. This study serves as an important reference for future urban planning and modeling studies.