Singapore skyline by Mike Enerio on Unsplash. We continuously accept new PhD students through the regular route by applying to one of the scholarships available by our university.| Urban Analytics Lab | Singapore
NUS Urban Analytics Lab| Urban Analytics Lab | Singapore
3D City Index – Assessing and benchmarking 3D City Models About the project 3D city models are omnipresent in urban management and simulations. We establish a holistic and comprehensive 4-category framework – ‘3D City Index’, encompassing 47 criteria to identify key properties of 3D city models, enabling their assessment and benchmarking, and suggesting usability. The framework implementation enables a comprehensive and structured understanding of the landscape of semantic 3D geospati...| Projects | Urban Analytics Lab | Singapore
GBMI — Understanding the building form around the world in detail Our triplex project: metrics, open-source software, and open dataset Characterising and analysing urban morphology is a continuous task in urban data science, environmental analyses, and many other domains. As the availability and quality of data on them have been increasing, buildings have gained more attention. However, tools and data facilitating large-scale studies, together with an interdisciplinary consensus on metrics,...| Projects | Urban Analytics Lab | Singapore
This is an ongoing project: the inventory is currently in beta, as we are working on cleaning it and adding new datasets. A preliminary snapshot is provided here to raise awareness of the project, solicit more datasets, and help us detect errors. A preprint is available. Mapping and analysing the availability of authoritative datasets on buildings worldwide About the project Open government data on buildings is becoming increasingly available and accessible globally, being useful for a variet...| Projects | Urban Analytics Lab | Singapore
A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics| Urban Analytics Lab | Singapore
We are a multidisciplinary research group focusing on urban data management and analysis, geographic data science, and digital twins at the National University of Singapore (NUS), a leading global university centred in Asia. Our mission is to leverage and make sense of big geospatial data at different scales for urban applications and catalyse the development of spatial data infrastructures and digital twins in the realm of smart cities and the built environment. We are particularly intereste...| Urban Analytics Lab | Singapore
Slides can be added in a few ways: Create slides using Wowchemy’s Slides feature and link using slides parameter in the front matter of the talk file Upload an existing slide deck to static/ and link using url_slides parameter in the front matter of the talk file Embed your slides (e.g. Google Slides) or presentation video on this page using shortcodes. Further event details, including page elements such as image galleries, can be added to the body of this page.| Urban Analytics Lab | Singapore
We are glad to share a new collaborative paper: Wang S, Huang X, Liu P, Zhang M, Biljecki F, Hu T, Fu X, Liu L, Liu X, Wang R, Huang Y, Yan J, Jiang J, Chukwu M, Reza Naghedi S, Hemmati M, Shao Y, Jia N, Xiao Z, Tian T, Hu Y, Yu L, Yap W, Macatulad E, Chen Z, Cui Y, Ito K, Ye M, Fan Z, Lei B, Bao S (2024): Mapping the landscape and roadmap of geospatial artificial intelligence (GeoAI) in quantitative human geography: An extensive systematic review. International Journal of Applied Earth Obser...| Urban Analytics Lab | Singapore
We are glad to share our new paper: Macatulad E, Biljecki F (2024): Continuing from the Sendai Framework midterm: Opportunities for urban digital twins in disaster risk management. International Journal of Disaster Risk Reduction, 102: 104310. 10.1016/j.ijdrr.2024.104310 PDF This research was led by Edgardo G. Macatulad. Congratulations on this journal publication that is part of his PhD research! 🙌 👏 The paper is available freely until 2024-03-27. Highlights A review of urban disaster ...| Urban Analytics Lab | Singapore
We are glad to share our new paper: Wang Z, Ito K, Biljecki F (2024): Assessing the equity and evolution of urban visual perceptual quality with time series street view imagery. Cities, 145: 104704. 10.1016/j.cities.2023.104704 PDF This research was led by Wang Zeyu, our Master of Urban Planning graduate. Congratulations on the first journal publication! 🙌 👏 The paper is available freely until 2024-01-26. Abstract The abstract follows. The well-being of residents is considerably influen...| Urban Analytics Lab | Singapore
We are glad to share a new collaborative paper: Lin S, Ramani V, Martin M, Arjunan P, Chong A, Biljecki F, Ignatius M, Poolla K, Miller C (2023): District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images. Scientific Data 10: 859. 10.1038/s41597-023-02749-0 PDF This paper presents an openly released dataset collected from thermal observatories deployed in the campus of our National University of Singapore. Infrared thermography provides a non-conta...| Urban Analytics Lab | Singapore
We are glad to share a new collaborative paper: Jin X, Fu C, Kazmi H, Balint A, Canaydin A, Quintana M, Biljecki F, Xiao F, Miller C (2023): The Building Data Genome Directory – An open, comprehensive data sharing platform for building performance research. Journal of Physics: Conference Series 2600: 032003. 10.1088/1742-6596/2600/3/032003 PDF This paper presents the Building Data Genome Directory, an open data-sharing platform serving as a one-stop shop for the data necessary for vital cat...| Urban Analytics Lab | Singapore
We are glad to share our new paper: Yap W, Biljecki F (2023): A Global Feature-Rich Network Dataset of Cities and Dashboard for Comprehensive Urban Analyses. Scientific Data 10: 667. 10.1038/s41597-023-02578-1 PDF This research was led by Winston Yap. Congratulations on the great work! 🙌 👏 Urbanity is a network-based Python package developed by Winston Yap at our NUS Urban Analytics Lab to automate the construction of feature rich (contextual and semantic) urban networks at any geograph...| Urban Analytics Lab | Singapore
We are glad to share our new paper: Yap W, Stouffs R, Biljecki F (2023): Urbanity: automated modelling and analysis of multidimensional networks in cities. npj Urban Sustainability 3: 45. 10.1038/s42949-023-00125-w PDF This research was led by Winston Yap. Congratulations on the great work on both the software and publication! 🙌 👏 Urbanity is a network-based Python package developed by Winston Yap at our NUS Urban Analytics Lab to automate the construction of feature rich (contextual an...| Urban Analytics Lab | Singapore
We are glad to share our new paper: Wang J, Chow YS, Biljecki F (2023): Insights in a city through the eyes of Airbnb reviews: Sensing urban characteristics from homestay guest experiences. Cities 140: 104399. 10.1016/j.cities.2023.104399 PDF This research was led by Wang Jiaxuan. Congratulations on the great work and publication! 🙌 👏 Jiaxuan has graduated from our NUS Master of Urban Planning programme. Until 2023-07-26, the article is available for free via this link. Abstract The abs...| Urban Analytics Lab | Singapore
We are glad to share our new paper: Zhao T, Huang Z, Tu W, Biljecki F, Chen L (2023): Developing a multiview spatiotemporal model based on deep graph neural networks to predict the travel demand by bus. International Journal of Geographical Information Science, 37(7): 1555-1581. 10.1080/13658816.2023.2203218 PDF This research was led by Tianhong Zhao. Congratulations on his great work! 🙌 👏 Tianhong had been with us for a year as a visiting scholar from Shenzhen University, and he was aw...| Urban Analytics Lab | Singapore
We are glad to share our new paper: Chen S, Biljecki F (2023): Automatic assessment of public open spaces using street view imagery. Cities 137: 104329. 10.1016/j.cities.2023.104329 PDF This research was led by Chen Shuting. Congratulations on the great work and publication! 🙌 👏 Shuting is now at the University of Hong Kong, where she started her PhD after graduating from our NUS Master of Urban Planning programme. Studies using street-level imagery have been confined to driveable roads...| Urban Analytics Lab | Singapore