---
license: cc-by-sa-4.0
task_categories:
- image-classification
- image-segmentation
- image-feature-extraction
language:
- en
tags:
- street view imagery
- open data
- data fusion
- urban analytics
- GeoAI
- volunteered geographic information
- machine learning
- spatial data infrastructure
size_categories:
- 1M<n<10M
---

# Global Streetscapes

Repository for the tabular portion of the [Global Streetscapes dataset project](https://ual.sg/project/global-streetscapes/) by the [Urban Analytics Lab (UAL)](https://ual.sg/) at the National University of Singapore (NUS).
Please follow our code to download the raw images (10+ Million images, 346 features, and ~9TB).

Code for reproducibility and documentation: [https://github.com/ualsg/global-streetscapes](https://github.com/ualsg/global-streetscapes).

You can read more about this project on the [project website](https://ual.sg/project/global-streetscapes/).
The project website includes an overview of the project together with the background, [paper](https://www.sciencedirect.com/science/article/pii/S0924271624002612), and FAQ.

Please cite our [paper](https://www.sciencedirect.com/science/article/pii/S0924271624002612):

Hou Y, Quintana M, Khomiakov M, Yap W, Ouyang J, Ito K, Wang Z, Zhao T, Biljecki F (2024): Global Streetscapes — A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics. ISPRS Journal of Photogrammetry and Remote Sensing 215: 216-238.

BibTeX:
```
@article{2024_global_streetscapes,
 author = {Hou, Yujun and Quintana, Matias and Khomiakov, Maxim and Yap, Winston and Ouyang, Jiani and Ito, Koichi and Wang, Zeyu and Zhao, Tianhong and Biljecki, Filip},
 doi = {10.1016/j.isprsjprs.2024.06.023},
 journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
 pages = {216-238},
 title = {Global Streetscapes -- A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics},
 volume = {215},
 year = {2024}
}
```