--- 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} } ```