Filip Biljecki

Biographic Data

ID	4416598
NAME	Filip Biljecki
GIVEN NAMES	Filip
FAMILY NAME	Biljecki
SIGNATURE	BILJECKI F
AFFILIATIONS	National University of Singapore
ORCID	0000-0002-6229-7749
VERIFIED	Yes
TOTAL WORKS	60
TOTAL CITATIONS	41
AUTHOR COUNT	60
EDITOR COUNT	0
FIRST PUBLICATION YEAR	2015
LATEST PUBLICATION YEAR	2026
H-INDEX	3

Exploring the links amongst place attachment, urban environment qualities, and psychological restoration
Open AccessSifan Cheng, Qiwei Song et al.ARTICLECities2026
A Graph-Based Human-Centered GeoAI for Understanding Street-Level Environment and Traffic Accident Frequency with Street View Imagery
Open AccessPengyuan Liu, Winston Yap et al.ARTICLEJournal of Urban Technology2026
Traffic accidents are a major global concern, highlighting the need for advanced traffic analysis and predictive techniques. The emergence of crowdsourced street view imagery (SVI) platforms has transformed public participation in collecting urban data, initiating the development of human-centered traffic analytics. This article investigates the relationship between visual urban understanding derived from Mapillary SVI and the frequency of urban …
Modeling adolescents’ perception of cycling safety
Open AccessXiaobing Wei, Filip Biljecki et al.ARTICLEComputers Environment and Urban…2026
Inferring urban functions from Google Maps reviews
Open AccessHaixiao Liu, Sijie Yang et al.ARTICLEComputers Environment and Urban…2026
It is not always greener on the other side
Open AccessMatias Quintana, Fangqi Liu et al.ARTICLELandscape and Urban Planning2026
City landscape in sight
Open AccessChucai Peng, Sijie Yang et al.ARTICLELandscape and Urban Planning2026
Perceived traffic safety’s impact on cycling route choice with street-level images
Open AccessKoichi Ito, Roos Terra et al.ARTICLETransportation2026
Perceived traffic safety influences cycling behavior, yet its value relative to travel time and other route attributes remains unquantified. Building on the stated choice experiment and street-level image dataset of Terra et al. (2025), we extract safety perception scores from cycling-perspective images using a computer vision model and estimate mixed logit models to test whether perceived safety affects route choice after controlling for visual …
Living upon networks
Open AccessPengyuan Liu, Yuan Wang et al.ARTICLEEnvironment and Planning B Urban…2026
Cities are supported by multiple, interacting networks, most prominently streets, which channel movement and economic exchange, and, in many contexts, waterways, which regulate flows of goods, people, and environmental amenities. Conventional quantitative studies of urban form have tended to privilege streets alone, limiting their ability to capture the full spatial logic of the urban fabric. This paper introduces a Heterogeneous Graph Autoen-cod…
Urban AI for a sustainable built environment
Open AccessSteffen Knoblauch, Hao Li et al.ARTICLEEnvironment and Planning B Urban…2026
Semantic urban elements
Open AccessMatias Quintana, Chenyi Cai et al.ARTICLEEnvironment and Planning B Urban…2026
Architecture, engineering, and construction have increasingly integrated automated tools and digital approaches for urban analysis and design. Many of these approaches are tailored towards either urban Design or urban Science, despite both being central to our understanding of cities. The separation between these two core aspects of urban development introduces multidisciplinary challenges when addressing the consequences of urban phenomena. We p…
Unveiling the meaning in the image of the city
Open AccessYihan Zhu, Markus Brenken et al.ARTICLEEnvironment and Planning B Urban…2026
Kevin Lynch’s concept of imageability describes how effectively an environment evokes a mental image in an observer’s mind, which consists of three components—“identity, structure, and meaning”—with the first two being the main components to build Lynch’s cognitive map. Although imageability has significantly influenced urban design and planning, and inspired numerous subsequent research, the “meaning” component has not been clearly studied. The …
VoxCity
Open AccessKunihiko Fujiwara, Ryuta Tsurumi et al.ARTICLEComputers Environment and Urban…2026References: 154
Three-dimensional urban environment simulation is a powerful tool for informed urban planning. However, the intensive manual effort required to prepare input 3D city models has hindered its widespread adoption. To address this challenge, we present VoxCity, an open-source Python package that provides a one-stop solution for grid-based 3D city model generation and urban environment simulation for cities worldwide. VoxCity’s ‘generator’ subpackage …
Designing effective image-based surveys for urban visual perception
Open AccessYoulong Gu, Matias Quintana et al.ARTICLELandscape and Urban Planning2025
Sensing climate justice
Open AccessPengyuan Liu, Binyu Lei et al.ARTICLESustainable Cities and Society2025
Bi-directional mapping of morphology metrics and 3D city blocks for enhanced characterisation and generation of urban form
Open AccessChenyi Cai, Biao Li et al.ARTICLESustainable Cities and Society2025
Developing the urban comfort index
Open AccessBinyu Lei, Pengyuan Liu et al.ARTICLESustainable Cities and Society2025
Drivers of day–night intra-surface urban heat island variations under local extreme heat
Open AccessSiyu Li, Filip Biljecki et al.ARTICLESustainable Cities and Society2025
Understanding the user perspective on urban public spaces
Open AccessYihan Zhu, Ye Zhang et al.ARTICLECities2025
Urban Aedes aegypti suitability indicators
Open AccessSteffen Knoblauch, Rutendo T Mukaratirwa et al.ARTICLEThe Lancet Planetary Health2025
Revealing building operating carbon dynamics for multiple cities
Open AccessWinston Yap, Abraham Noah Wu et al.ARTICLENature Sustainability2025Cited by: 1References: 4
Coverage and bias of street view imagery in mapping the urban environment
Open AccessZicheng Fan, Chen-Chieh Feng et al.ARTICLEComputers Environment and Urban…2025Cited by: 2References: 78
Physical urban change and its socio-environmental impact
Open AccessYingjie Liu, Zeyu Wang et al.ARTICLEComputers Environment and Urban…2025Cited by: 1References: 57
Quantifying seasonal bias in street view imagery for urban form assessment
Open AccessTianhong Zhao, Xiucheng Liang et al.ARTICLEComputers Environment and Urban…2025Cited by: 2References: 63
Street view imagery (SVI), with its rich visual information, is increasingly recognized as a valuable data source for urban research. Particularly, by leveraging computer vision techniques, SVI can be used to calculate various urban form indices (e.g., Green View Index, GVI), providing a new approach for large-scale quantitative assessments of urban environments. However, SVI data collected at the same location in different seasons can yield vary…
ZenSVI
Open AccessKoichi Ito, Yihan Zhu et al.ARTICLEComputers Environment and Urban…2025Cited by: 2References: 114
Multidimensional analysis of human outdoor comfort
Open AccessBinyu Lei, Pengyuan Liu et al.ARTICLECities2025Cited by: 1References: 7

Applications of 3D City Models
Open AccessFilip Biljecki, Jantien Stoter et al.ARTICLEISPRS International Journal of…2015
In the last decades, 3D city models appear to have been predominantly used for visualisation; however, today they are being increasingly employed in a number of domains and for a large range of tasks beyond visualisation. In this paper, we seek to understand and document the state of the art regarding the utilisation of 3D city models across multiple domains based on a comprehensive literature study including hundreds of research papers, technica…
An improved LOD specification for 3D building models
Open AccessFilip Biljecki, Hugo Ledoux et al.ARTICLEComputers Environment and Urban…2016
The effect of acquisition error and level of detail on the accuracy of spatial analyses
Open AccessFilip Biljecki, G B M Heuvelink et al.ARTICLECartography and Geographic…2017
There has been a great deal of research about errors in geographic information and how they affect spatial analyses. A typical GIS process introduces various types of errors at different stages, and such errors usually propagate into errors in the result of a spatial analysis. However, most studies consider only a single error type thus preventing the understanding of the interaction and relative contributions of different types of errors. We foc…
Tools for BIM-GIS Integration (IFC Georeferencing and Conversions)
Open AccessFrancesca Noardo, Lars Harrie et al.ARTICLEISPRS International Journal of…2020
The integration of 3D city models with Building Information Models (BIM), coined as GeoBIM, facilitates improved data support to several applications, e.g., 3D map updates, building permits issuing, detailed city analysis, infrastructure design, context-based building design, to name a few. To solve the integration, several issues need to be tackled and solved, i.e., harmonization of features, interoperability, format conversions, integration of …
Assessing bikeability with street view imagery and computer vision
Open AccessKoichi Ito, Filip BiljeckiARTICLETransportation Research Part C:…2021
Classification of urban morphology with deep learning
Open AccessWangyang Chen, Abraham Noah Wu et al.ARTICLEComputers Environment and Urban…2021
D city models for urban farming site identification in buildings
Open AccessAnkit Palliwal, Shuang Song et al.ARTICLEComputers Environment and Urban…2021
Roofpedia
Open AccessAbraham Noah Wu, Filip BiljeckiARTICLELandscape and Urban Planning2021
Sustainable roofs, such as those with greenery and photovoltaic panels, contribute to the roadmap for reducing the carbon footprint of cities. However, research on sustainable urban roofscapes is rather focused on their potential and it is hindered by the scarcity of data, limiting our understanding of their current content, spatial distribution, and temporal evolution. To tackle this issue, we introduce Roofpedia, a set of three contributions: (…
Street view imagery in urban analytics and GIS
Open AccessFilip Biljecki, Koichi ItoARTICLELandscape and Urban Planning2021
Street view imagery has rapidly ascended as an important data source for geospatial data collection and urban analytics, deriving insights and supporting informed decisions. Such surge has been mainly catalysed by the proliferation of large-scale imagery platforms, advances in computer vision and machine learning, and availability of computing resources. We screened more than 600 recent papers to provide a comprehensive systematic review of the s…
Global Building Morphology Indicators
Open AccessFilip Biljecki, Yoong Shin ChowARTICLEComputers Environment and Urban…2022
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, remain scarce and often inadequate. We present Global Building Morphology Indicators (GBM…
Free and open source urbanism
Open AccessWinston Yap, Patrick Janssen et al.ARTICLEComputers Environment and Urban…2022
Free and open source tools present numerous opportunities to support current urban planning practice. However, their overview is fragmented, and the uptake among planning professionals remains lacklustre. Recent discourse in the domain of planning support tools attribute poor take up to the lack of understanding on the landscape and functionality of available tools, and how tools can add value to the planning process. We provide an understanding …
Semantic Riverscapes
Open AccessJunjie Luo, Tianhong Zhao et al.ARTICLELandscape and Urban Planning2022
Unsupervised machine learning in urban studies
Open AccessJing Wang, Filip BiljeckiARTICLECities2022
Sensing urban soundscapes from street view imagery
Open AccessTianhong Zhao, Xiucheng Liang et al.ARTICLEComputers Environment and Urban…2023
Revealing spatio-temporal evolution of urban visual environments with street view imagery
Open AccessXiucheng Liang, Tianhong Zhao et al.ARTICLELandscape and Urban Planning2023
Incorporating networks in semantic understanding of streetscapes
Open AccessWinston Yap, Jiat‐Hwee Chang et al.ARTICLEEnvironment and Planning B Urban…2023
Planning for active mobility satisfies many fundamental tenets of good urban design and planning. However, planning for active mobility is a complex endeavour due to numerous local, place-based factors that influence active mobility decisions. Recent advancements in urban data research have demonstrated the effectiveness of deep learning methods in evaluating active mobility potential for urban environments. At present, the incorporation of seman…
Towards Human-centric Digital Twins
Open AccessPengyuan Liu, Tianhong Zhao et al.ARTICLESustainable Cities and Society2023
Insights in a city through the eyes of Airbnb reviews
Open AccessJiaxuan Wang, Yoong Shin Chow et al.ARTICLECities2023Cited by: 3References: 3
Automatic assessment of public open spaces using street view imagery
Open AccessShuting Chen, Filip BiljeckiARTICLECities2023Cited by: 10References: 84
Continuing from the Sendai Framework midterm
Open AccessEdgardo Macatulad, Filip BiljeckiARTICLEInternational Journal of Disaster…2024
Predicting building characteristics at urban scale using graph neural networks and street-level context
Open AccessBinyu Lei, Pengyuan Liu et al.ARTICLEComputers Environment and Urban…2024
Learning visual features from figure-ground maps for urban morphology discovery
Open AccessJing Wang, Weiming Huang et al.ARTICLEComputers Environment and Urban…2024
Global urban road network patterns
Open AccessWangyang Chen, Huiming Huang et al.ARTICLELandscape and Urban Planning2024
Assessing governance implications of city digital twin technology
Open AccessMasahiko Haraguchi, Tomomi Funahashi et al.ARTICLETechnological Forecasting and…2024
Explainable spatially explicit geospatial artificial intelligence in urban analytics
Open AccessPengyuan Liu, Yan Zhang et al.ARTICLEEnvironment and Planning B Urban…2024
Geospatial artificial intelligence (GeoAI) is proliferating in urban analytics, where graph neural networks (GNNs) have become one of the most popular methods in recent years. However, along with the success of GNNs, the black box nature of AI models has led to various concerns (e.g. algorithmic bias and model misuse) regarding their adoption in urban analytics, particularly when studying socio-economics where high transparency is a crucial compo…