Everything About ___
Live briefing

Everything about R-tree

Data structures used in spatial indexing

R-trees are tree data structures used for spatial access methods, i.e., for indexing multi-dimensional information such as geographical coordinates, rectangles or polygons. The R-tree was proposed by Antonin Guttman in 1984 and has found significant use in both theoretical and applied contexts. A common real-world usage for an R-tree might be to store spatial objects such as restaurant locations or the polygons that typical maps are made of: streets, buildings, outlines of lakes, coastlines, etc. and then find answers quickly to queries such as "Find all museums within 2 km of my current location", "retrieve all road segments within 2 km of my location" or "find the nearest gas station". The R-tree can also accelerate nearest neighbor search for various distance metrics, including great-circle distance. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: R-treeA 5-minute orientation
  2. Skim a recent paper: Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation toolInfluential work since 2022
  3. Pick up a classic book: Farquhar's garden annualThe most-reprinted book on the subject
  4. Read the landmark paper: IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood PhylogeniesCited 25,767 times
  5. Go sideways: R*-treeA closely related topic
  6. Go sideways: Hilbert R-treeA closely related topic

📖 Definitions

No dictionary entry for this exact phrase.

🗂️ The subject at a glance

  1. R-tree idea
  2. Variants
  3. Algorithm

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics