# CityJSON: a compact and easy-to-use encoding of the CityGML data model

arXiv: https://arxiv.org/abs/1902.09155 · HTML: https://mlsanity.com/paper/1902.09155/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Feb 2019.

## Built on by (most cited first, 8 of 8)

- [Automated 3D reconstruction of LoD2 and LoD1 models for all 10 million buildings of the Netherlands](https://mlsanity.com/paper/2201.01191/) (2021)
- [TUM2TWIN: Introducing the Large-Scale Multimodal Urban Digital Twin Benchmark Dataset](https://mlsanity.com/paper/2505.07396/) (2025)
- [Analyzing the impact of semantic LoD3 building models on image-based vehicle localization](https://mlsanity.com/paper/2407.21432/) (2024)
- [CM2LoD3: Reconstructing LoD3 Building Models Using Semantic Conflict Maps](https://mlsanity.com/paper/2508.15672/) (2025)
- [Enriching thermal point clouds of buildings using semantic 3D building models](https://mlsanity.com/paper/2407.21436/) (2024)
- [3dSAGER: Geospatial Entity Resolution over 3D Objects (Technical Report)](https://mlsanity.com/paper/2511.06300/) (2025)
- [GS4City: Hierarchical Semantic Gaussian Splatting via City-Model Priors](https://mlsanity.com/paper/2604.11401/) (2026)
- [Remote-Sensing City Layout Extraction with MLLM](https://mlsanity.com/paper/2608.16484/) (2026)

## Abstract (arXiv)

The international standard CityGML is both a data model and an exchange format to store digital 3D models of cities. While the data model is used by several cities, companies, and governments, in this paper we argue that its XML-based exchange format has several drawbacks. These drawbacks mean that it is difficult for developers to implement parsers for CityGML, and that practitioners have, as a consequence, to convert their data to other formats if they want to exchange them with others. We present CityJSON, a new JSON-based exchange format for the CityGML data model (version 2.0.0). CityJSON was designed with programmers in mind, so that software and APIs supporting it can be quickly built. It was also designed to be compact (a compression factor of around six with real-world datasets), and to be friendly for web and mobile development. We argue that it is considerably easier to use than the CityGML format, both for reading and for creating datasets. We discuss in this paper the main features of CityJSON, briefly present the different software packages to parse/view/edit/create files (including one to automatically convert between the JSON and GML encodings), analyse how real-world datasets compare to those of CityGML, and we also introduce Extensions, which allow us to extend the core data model in a documented manner.