Data structures and operations for geographical information

• Main Author: Toussaint, Richard
• Other Authors: Merrett, T. H. (advisor)
• Format: Others
• Language: en
• Published: McGill University 1995
• Subjects: Information Science.; Computer Science.
• Online Access: http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=23945

The topic of this thesis revolves around the organization of geographical information in permanent memory. Our premise is that a recognized and fully documented direct access storage technique called Multidimensional Paging or Multipaging would provide a well balanced storing structure for this category of data. Since multipaging uses a multidimensional perspective on the information to allocate it to pages in secondary storage then spatial data, which is fundamentally multidimensional by nature, would surely offer a suitable profile. === First, we attempt to evaluate the efficiency of multipaging on static files and to suggest possible modifications to the standard algorithm to better serve spatial data. === Our solution to this problem consists in compressing the pages that overflow. Because geographical information is often a representation of occurences of Nature, we hypothesize that Fractal Geometry, which serves to formalize a mathematical description of such elements, could provide the theoretical background to derive an efficient fractal-based compression algorithm. An appreciable improvement is obtained by compressing the pages of the multipaged administrative regions data that exceed their capacity: $ alpha=0.7272$ and $ pi=1.0$. === The outcome of these experiments led us to elaborate a mixed system based on two relatively different approaches: multipaging and fractal-based data compression. The first part consisted in the implementation of the standard static multipaging algorithm using a relational database management system named Relix. The other approach was developed using the C programming language to accommodate some particularities of the multipaged spatial data. The preliminary results were encouraging and allowed us to establish the parameters for a more formal implementation. Also, it brought out the limits of the compression method in view of the intended usage of the data. (Abstract shortened by UMI.)