In this paper we present a new technique to improve the performance of spatial access methods by minimizing redundancy: the oversize shelf. Oversize shelves are additional disk pages that are attached to the interior nodes of a treebased spatial access method (such as the R-tree or the cell tree). These pages are used to accommodate very large data objects in order to avoid their excessive fragmentation. Whenever inserting a new object into the tree, one now has to decide whether to store it on an oversize shelf or insert it into the corresponding subtrees. For this purpose, we developed an analytic model for the behaviour of dynamic spatial access methods under insertion and deletions. The model yields a threshold value for the size of an object, such that it is more favourable to put it on the oversize shelf if and only if its size is greater than the threshold value. Otherwise the insertion into the corresponding subtrees is preferable. Practical experiments indicate that this policy results in a faster computation of search queries, and that the cell tree with oversize shelves is one of the most efficient spatial access methods currently available.