An adaptive-size vector tile pyramid construction method considering spatial data distribution density characteristics

Abstract

Vector tile pyramid is a technology that provides a compact representation of geospatial data. It enables efficient transmission and rendering by storing geographic information in a tile-based format on the server side. Traditional vector tile construction methods divide vector data into a series of tiles of fixed size, such as 256*256 pixels, which leads to numerous empty tiles, imbalanced data distribution between tiles, and diminished internet transmission efficiency. To address these limitations, we propose a novel three-step method for dynamically adjusting tile sizes based on spatial data distribution density during construction. Firstly, we generalize the raw data into a multi-resolution vector dataset encompassing varying levels of detail (LOD). Subsequently, we employ a quadtree-based approach for each level within the multi-resolution dataset to construct adaptive-size vector tiles that align with the specific spatial distribution density characteristics. Finally, we encode these different-size vector tiles using Geohash technology to facilitate spatial indexing and internet transmission. Experimental results validate the effectiveness of our approach, including a notable reduction in the number of generated tiles, a more balanced distribution of data volume among them, and a marked enhancement in internet transmission efficiency.