Regenerating Large Volume Vector Layers with a Denormalization-Based Method

Abstract

A geographic information system (GIS) is a computer system for capturing, storing, controlling and displaying data about locations of objects on the Earth’s surface. The GIS systems are widely used nowadays to help individuals and organizations better understand spatial patterns and relationships. The GIS systems consist of large volumes of spatial data. Data in the GIS systems is made into a vector layer for users to access quickly. However, these layers, which consist of many different types of data, are frequently updated. It is a complicated process to keep the frequently updated large volume vector layer up to date. A new denormalization-based system is proposed in this study to keep up to date with frequently updated large volume vector layers. Denormalization is defined as accelerating a database’s response time by adding or combining features that are not needed after a normalization process in a database design. The results of the proposed denormalization-based system in this study were compared with the normalization-based method results using large volumes of spatial data belonging to Kayseri Metropolitan Municipality. Experimental results showed that the proposed denormalization-based system creates large volume vector layers faster than the normalization-based system and ensures that the layer is up-to-date.