Indexing for Dynamic Abstract Regions

We propose a new main memory index structure for abstract regions (objects) which may heavily overlap, the RCtree. These objects are "dynamic" and may have short life spans. The novelty is that rather than representing an object by its minimum bounding rectangle (MBR), possibly with pre-processed segmentation into many small MBRs, we use the actual shape of the object to maintain the index. This saves significant space for objects with large spatial extents since pre-segmentation is not needed. We show that the query performance of RC-tree is much better than many indexing schemes on synthetic overlapping data sets. The performance is also competitive on real-life GIS nonoverlapping data sets.