Computers Environment and Urban Systems

Papers
(The H4-Index of Computers Environment and Urban Systems is 37. 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 2021-05-01 to 2025-05-01.)
ArticleCitations
Navigating the post-pandemic urban landscape: Disparities in transportation recovery & regional insights from New York City390
How far are we towards sustainable Carfree cities combining shared autonomous vehicles with park-and-ride: An agent-based simulation assessment for Brussels112
A building volume adjusted nighttime light index for characterizing the relationship between urban population and nighttime light intensity106
An ANN-based method for population Dasymetric mapping to avoid the scale heterogeneity: A case study in Hong Kong, 2016–202193
A land-use transport-interaction framework for large scale strategic urban modeling93
Rooftop segmentation and optimization of photovoltaic panel layouts in digital surface models78
An integrated global model of local urban development and population change77
Function and form of U.S. cities76
Streetscapes as part of servicescapes: Can walkable streetscapes make local businesses more attractive?75
Characterizing residential segregation in cities using intensity, separation, and scale indicators73
Large-scale agent-based modelling of street robbery using graphical processing units and reinforcement learning72
A simple agent-based model for planning for bicycling: Simulation of bicyclists' movements in urban environments69
Using a deep learning model to quantify trash accumulation for cleaner urban stormwater63
Augmenting the Social Vulnerability Index using an agent-based simulation of Hurricane Harvey63
Using street-view panoramas to model the decision-making complexity of road intersections based on the passing branches during navigation62
Quality assessment of crowdsourced social media data for urban flood management61
Enhanced solution capabilities for multiple patch land allocation59
Delineating urban functional zones using mobile phone data: A case study of cross-boundary integration in Shenzhen-Dongguan-Huizhou area58
Large scale geospatial data conflation: A feature matching framework based on optimization and divide-and-conquer58
Locating offenders: Introducing the reverse spatial patterning approach56
The language of neighborhoods: A predictive-analytical framework based on property advertisement text and mortgage lending data56
Detecting cities with high intermediacy in the African urban network54
Delineating urban functional use from points of interest data with neural network embedding: A case study in Greater London53
Homogeneity and heterogeneity of diurnal and nocturnal hotspots and the implications for synergetic mitigation in heat-resilient urban planning52
Analyzing usage patterns from video data through deep learning: The case of an urban park50
Capturing the spatial arrangement of POIs in crime modeling48
A framework for modelling spatio-temporal informal settlement growth prediction48
‘Green or short: choose one’ - A comparison of walking accessibility and greenery in 43 European cities46
Understanding the protection of privacy when counting subway travelers through anonymization43
Machine learning to model gentrification: A synthesis of emerging forms43
Interpretable machine learning models for crime prediction41
Delineating functional urban areas in Chinese mega city regions using fine-grained population data and cellphone location data: A case of Pearl River Delta41
Machine learning application to spatio-temporal modeling of urban growth40
A user-friendly assessment of six commonly used urban growth models39
Exploring the viability of walk-sharing in outdoor urban spaces38
Towards a scalable and transferable approach to map deprived areas using Sentinel-2 images and machine learning37
Community time-activity trajectory modeling based on Markov chain simulation and Dirichlet regression37
Strategic allocation of landmarks to reduce uncertainty in indoor navigation37
Corrigendum to “An integrated physical-social analysis of disrupted access to critical facilities and community service-loss tolerance in urban flooding” [Computers, Environment and Urban Systems 80 (37
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