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 (346 features) of the Global Streetscapes dataset project by the Urban Analytics Lab (UAL) at the National University of Singapore (NUS).

This repository has a total size of about 63G (37G for data/, 23G for manual_labels/, and 2.8G for models/). Please follow our code to download the image files (10+ Million images, ~6TB).

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}
}