Wavelet Tree Approach for Searching and Indexing in Geographical Information Retrieval

Spatial data in Geographical Information Retrieval (GIR) plays an increasingly important role in applications such as spatial planning, crisis management or context-based services. Spatial data makes an already difficult task even more difficult for traditional indexing methods to perform. They are not created with the idea of these complex dimensions built in and need to be more efficient and practical regarding search and retrieval processes. In this paper, we discussa data structure, a wavelet tree-based system named WaveGIR, that supports searching through summarizations by taking advantage of wavelet transform in the multiresolution property. The wavelet tree structure consumes spatial data in a compressed way and permits fast access and retrieval of geographic information. We compare our approach against standard indexing mechanisms on various datasets regarding query response time, memory utilization and retrieval accuracy. The findings showed notable gains in efficiency and scalability, thereby branding the wavelet tree method as an attractive solution for today's GIR scenarios.