Predicting walking-to-work using street-level imagery and deep learning in seven Canadian cities [PDF]
Scientific Reports, 2022 New ‘big data’ streams such as street-level imagery are offering unprecedented possibilities for developing health-relevant data on the urban environment.
Dany Doiron +8 more
doaj +2 more sources
Mapping Tree Canopy in Urban Environments Using Point Clouds from Airborne Laser Scanning and Street Level Imagery [PDF]
Sensors, 2022 Resilient cities incorporate a social, ecological, and technological systems perspective through their trees, both in urban and peri-urban forests and linear street trees, and help promote and understand the concept of ecosystem resilience.
Francisco Rodríguez-Puerta +4 more
doaj +2 more sources
USE-SVI: A reproducible pipeline for sampling, acquiring, and stitching Street View imagery to support urban analyticsI have shared my data/code at [PDF]
MethodsXStreet-level imagery (SLI) is increasingly used in urban analytics for tasks like estimating greenery, conducting transport audits, and assessing facades.
Iuria Betco +2 more
doaj +2 more sources
Street-level imagery dataset for the detection of informal vendors in urban environmentZenodo [PDF]
Data in BriefStreet vending is a prominent component of the informal economy, yet its prevalence remains poorly quantified due to the limitations of traditional survey methods, which are costly, invasive, and labor-intensive.
Keyla Garcia-Jaimes +2 more
doaj +2 more sources
A Hierarchical Urban Forest Index Using Street-Level Imagery and Deep Learning
Remote Sensing, 2019 We develop a method based on computer vision and a hierarchical multilevel model to derive an Urban Street Tree Vegetation Index which aims to quantify the amount of vegetation visible from the point of view of a pedestrian.
Francisco Rowe, Daniel Arribas-Bel
exaly +3 more sources
A comprehensive framework for evaluating the quality of street view imagery
International Journal of Applied Earth Observation and Geoinformation, 2022 Street view imagery (SVI) is increasingly in competition with traditional remote sensing sources and assuming its domination in myriads of studies, mainly thanks to the omnipresence of commercial services such as Google Street View.
Yujun Hou, Filip Biljecki
exaly +3 more sources
Multimodal generative AI for automated pavement condition assessment: Benchmarking model performance. [PDF]
PLoS ONEAccurate and efficient pavement condition assessment is essential for maintaining roadway safety and optimizing maintenance investments. However, conventional assessment methods such as manual visual inspections and specialized sensing equipment are ...
Chang Xu, Lei Shu, Anh Dao, Yue Cui
doaj +2 more sources
Exploring the relationship between urban visual density and responsible tourism behavior: a multimodal study of Macao [PDF]
Frontiers in PsychologyIntroductionUnderstanding responsible tourism behavior in high-density urban destinations is critical for sustainable tourism development. However, limited research has examined how tourists’ psychological evaluations are situated within objectively ...
Youcheng Wang +4 more
doaj +2 more sources
A PILOT STUDY OF URBAN POI MAPPING USING CROWDSOURCED STREET-LEVEL IMAGERY AND DEEP LEARNING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Point-of-interest (POI) data contains rich semantic and spatial information, having a wide range of applications including land use, transport planning and driving navigation.
L. Liu, L. Liu, B. Zhou, B. Zhou, X. Yi
doaj +1 more source
AUTOMATIC IMAGE-BASED 3D RECONSTRUCTION STRATEGIES FOR HIGH-FIDELITY URBAN MODELS – COMPARISON AND FUSION OF UAV AND MOBILE MAPPING IMAGERY FOR URBAN DESIGN STUDIES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Modelling environments for urban projects often involve virtual reconstructions of existing urban areas where generalised city models are not sufficient.
W. Wahbeh +3 more
doaj +1 more source