# The State of the Art in Visual Analytics for 3D Urban Data

arXiv: https://arxiv.org/abs/2404.15976 · HTML: https://mlsanity.com/paper/2404.15976/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Apr 2024.

## Built on by (most cited first, 4 of 4)

- [SideSeeing: A multimodal dataset and collection of tools for sidewalk assessment](https://mlsanity.com/paper/2407.06464/) (2024)
- [Urbanite: A Dataflow-Based Framework for Human-AI Interactive Alignment in Urban Visual Analytics](https://mlsanity.com/paper/2508.07390/) (2025)
- [VA-Blueprint: Uncovering Building Blocks for Visual Analytics System Design](https://mlsanity.com/paper/2508.07497/) (2025)
- [A Neural Field-Based Approach for View Computation & Data Exploration in 3D Urban Environments](https://mlsanity.com/paper/2511.14742/) (2025)

## Abstract (arXiv)

Urbanization has amplified the importance of three-dimensional structures in urban environments for a wide range of phenomena that are of significant interest to diverse stakeholders. With the growing availability of 3D urban data, numerous studies have focused on developing visual analysis techniques tailored to the unique characteristics of urban environments. However, incorporating the third dimension into visual analytics introduces additional challenges in designing effective visual tools to tackle urban data's diverse complexities. In this paper, we present a survey on visual analytics of 3D urban data. Our work characterizes published works along three main dimensions (why, what, and how), considering use cases, analysis tasks, data, visualizations, and interactions. We provide a fine-grained categorization of published works from visualization journals and conferences, as well as from a myriad of urban domains, including urban planning, architecture, and engineering. By incorporating perspectives from both urban and visualization experts, we identify literature gaps, motivate visualization researchers to understand challenges and opportunities, and indicate future research directions.