Assessment of Display Performance and Comparative Evaluation of Web Map Libraries for Extensive 3D Geospatial Data

TL;DR

This paper evaluates the performance of major WebGL-based web mapping libraries, CesiumJS and MapLibre GL JS, for large-scale 3D geospatial data visualization, providing data-driven guidelines for technology selection.

Contribution

It offers a comprehensive, standardized performance evaluation framework comparing CesiumJS and MapLibre GL JS using large-scale 3D data and Web Vitals metrics.

Findings

MVT-based MapLibre GL JS achieves optimal performance (FCP 0.8s, TBT 0ms).

MapLibre GL JS with deck.gl outperforms CesiumJS in large-scale point cloud processing.

Provides guidelines for selecting web mapping technologies based on use case performance.

Abstract

Large-scale 3D geospatial data visualization has become increasingly critical for the development of the digital society infrastructure in Japan. This study conducted a comprehensive performance evaluation of two major WebGL-based web mapping libraries, CesiumJS and MapLibre GL JS, using large-scale 3D point-cloud data from the VIRTUAL SHIZUOKA and PLATEAU building models. The research employs standardized 3D Tiles 1.1, and Mapbox Vector Tiles (MVT) formats, comparing performance across different data scales (2nd and 3rd grid levels) using Core Web Vitals metrics, including First Contentful Paint (FCP), Largest Contentful Paint (LCP), Speed Index, Total Blocking Time (TBT), and Cumulative Layout Shift (CLS). The results demonstrate that MVT-based building visualization with MapLibre GL JS achieves optimal performance (FCP 0.8s, TBT 0ms), whereas MapLibre GL JS combined with deck.gl shows superior performance for large-scale point cloud processing (TBT: 3ms, CesiumJS: 21,357ms). This study provides data-driven selection guidelines for appropriate technology choices according to use cases, establishing reproducible performance evaluation frameworks for 3D web mapping technologies during the WebGPU and OGC 3D Tiles 1.1 standardization era.