Spatial Data Structures are specialized formats used to organize and manage spatial data, which refers to information about the position, shape, and size of objects in space. These structures help in efficiently storing, querying, and analyzing data related to geographic locations, such as maps or 3D models. Common examples include Quadtrees, Octrees, and R-trees, each designed to optimize specific types of spatial queries. These structures enable faster access to spatial information by dividing space into manageable sections. For instance, Quadtrees divide a two-dimensional space into four quadrants, while Octrees do the same in three dimensions. By using these methods, applications like geographic information systems (GIS) and computer graphics can perform complex calculations more efficiently.