metadata

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 by the Urban Analytics Lab (UAL) 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.

You can read more about this project on the project website. The project website includes an overview of the project together with the background, paper, and FAQ.

Please cite our paper:

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}
}