Datasets:
Modalities:
Geospatial
Languages:
English
Size:
1M<n<10M
Tags:
street view imagery
open data
data fusion
urban analytics
GeoAI
volunteered geographic information
License:
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 NUS Global Streetscapes dataset project by the [Urban Analytics Lab (UAL)](https://ual.sg/). | |
Please follow our code to download the raw images (10+ Million images, 346 featuers, 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, FAQ | |
Cite our paper: | |
``` | |
@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 = {}, | |
title = {Global Streetscapes -- A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics}, | |
volume = {}, | |
year = {2024} | |
} | |
``` |