Computers Environment and Urban Systems

Papers
(The H4-Index of Computers Environment and Urban Systems is 32. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)
ArticleCitations
Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China488
Understanding spatio-temporal heterogeneity of bike-sharing and scooter-sharing mobility114
Extracting spatial effects from machine learning model using local interpretation method: An example of SHAP and XGBoost93
How did micro-mobility change in response to COVID-19 pandemic? A case study based on spatial-temporal-semantic analytics74
Urban function classification at road segment level using taxi trajectory data: A graph convolutional neural network approach69
Uncovering inconspicuous places using social media check-ins and street view images66
Classification of urban morphology with deep learning: Application on urban vitality55
Impacts of tree and building shades on the urban heat island: Combining remote sensing, 3D digital city and spatial regression approaches54
Estimating pedestrian volume using Street View images: A large-scale validation test54
Modeling urban growth using spatially heterogeneous cellular automata models: Comparison of spatial lag, spatial error and GWR53
Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems52
The potential of nighttime light remote sensing data to evaluate the development of digital economy: A case study of China at the city level52
Desirable streets: Using deviations in pedestrian trajectories to measure the value of the built environment43
Scale effects in remotely sensed greenspace metrics and how to mitigate them for environmental health exposure assessment43
Global Building Morphology Indicators42
Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions41
Land suitability and urban growth modeling: Development of SLEUTH-Suitability40
Access to urban parks: Comparing spatial accessibility measures using three GIS-based approaches40
Decoding urban landscapes: Google street view and measurement sensitivity40
Integrating a Forward Feature Selection algorithm, Random Forest, and Cellular Automata to extrapolate urban growth in the Tehran-Karaj Region of Iran38
Delineating urban functional use from points of interest data with neural network embedding: A case study in Greater London37
Using Google Street View imagery to capture micro built environment characteristics in drug places, compared with street robbery37
Spatial biases in crowdsourced data: Social media content attention concentrates on populous areas in disasters37
Delineating urban park catchment areas using mobile phone data: A case study of Tokyo35
Associations between mobility and socio-economic indicators vary across the timeline of the Covid-19 pandemic34
Urban morphology and traffic congestion: Longitudinal evidence from US cities34
Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning34
Estimating congestion zones and travel time indexes based on the floating car data33
Estimating quality of life dimensions from urban spatial pattern metrics32
Assessing multiscale visual appearance characteristics of neighbourhoods using geographically weighted principal component analysis in Shenzhen, China32
Places for play: Understanding human perception of playability in cities using street view images and deep learning32
Flood depth mapping in street photos with image processing and deep neural networks32
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