An interactive intro to quadtrees
3 days ago
- #algorithms
- #spatial-data
- #quadtrees
- Quadtrees are used to efficiently organize and query spatial data, such as points on a map.
- They divide a rectangular region into four quadrants, subdividing further if a quadrant contains too many points.
- This adaptive subdivision creates fine-grained cells in dense areas and coarse cells in sparse areas.
- Quadtrees optimize search operations by allowing entire regions to be skipped if they don't overlap with the query area.
- Common applications include map applications, collision detection in games, and image compression.
- The efficiency of quadtrees depends on node capacity, query size, and data distribution.
- Quadtrees can be extended to higher dimensions (e.g., octrees for 3D space) and are part of a broader family of spatial indexing structures.