It uses a tuple to represent a spatial data in the database. In order to retrieve the data, each tuple has a unique identifier, tuple-identifier. At the leaf node of a R-Tree, it has index record that can reference the spatial data. I is an n-dimensional rectangle and it is the bounding rectangle of the spatial data indexed. A R-Tree is a height balance tree and all leaves are on the same level.
Root node has at least two children unless it is the leaf node.
Every non-leaf node contains between m and M entries unless it is the root. Every leaf node contains between m and M index records unless it is the root. The R-tree is based on a heuristic optimization. The optimization criterion is to minimize the area of each enclosing rectangle in the inner nodes. For slightly higher implementation cost, it outperforms the existing R-Tree variants.