Computers Environment and Urban Systems

Papers
(The TQCC of Computers Environment and Urban Systems is 16. 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 2020-07-01 to 2024-07-01.)
ArticleCitations
Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China581
Extracting spatial effects from machine learning model using local interpretation method: An example of SHAP and XGBoost129
Urban function classification at road segment level using taxi trajectory data: A graph convolutional neural network approach81
How did micro-mobility change in response to COVID-19 pandemic? A case study based on spatial-temporal-semantic analytics78
Classification of urban morphology with deep learning: Application on urban vitality64
Impacts of tree and building shades on the urban heat island: Combining remote sensing, 3D digital city and spatial regression approaches63
Using graph structural information about flows to enhance short-term demand prediction in bike-sharing systems58
The potential of nighttime light remote sensing data to evaluate the development of digital economy: A case study of China at the city level56
Desirable streets: Using deviations in pedestrian trajectories to measure the value of the built environment49
Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions49
Global Building Morphology Indicators47
Scale effects in remotely sensed greenspace metrics and how to mitigate them for environmental health exposure assessment46
Decoding urban landscapes: Google street view and measurement sensitivity46
Integrating a Forward Feature Selection algorithm, Random Forest, and Cellular Automata to extrapolate urban growth in the Tehran-Karaj Region of Iran45
Access to urban parks: Comparing spatial accessibility measures using three GIS-based approaches45
Delineating urban functional use from points of interest data with neural network embedding: A case study in Greater London44
Urban morphology and traffic congestion: Longitudinal evidence from US cities40
Using Google Street View imagery to capture micro built environment characteristics in drug places, compared with street robbery40
Spatial biases in crowdsourced data: Social media content attention concentrates on populous areas in disasters40
VictimFinder: Harvesting rescue requests in disaster response from social media with BERT39
Flood depth mapping in street photos with image processing and deep neural networks38
Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning37
Places for play: Understanding human perception of playability in cities using street view images and deep learning37
Associations between mobility and socio-economic indicators vary across the timeline of the Covid-19 pandemic37
Estimating congestion zones and travel time indexes based on the floating car data37
Estimating quality of life dimensions from urban spatial pattern metrics36
Interpretable machine learning models for crime prediction36
Domain-specific sentiment analysis for tweets during hurricanes (DSSA-H): A domain-adversarial neural-network-based approach35
Assessing multiscale visual appearance characteristics of neighbourhoods using geographically weighted principal component analysis in Shenzhen, China34
Mobile phone location data for disasters: A review from natural hazards and epidemics34
A systematic review of agent-based models for autonomous vehicles in urban mobility and logistics: Possibilities for integrated simulation models33
A framework for urban land use classification by integrating the spatial context of points of interest and graph convolutional neural network method33
Investigating the spatiotemporal pattern between the built environment and urban vibrancy using big data in Shenzhen, China33
3D city models for urban farming site identification in buildings32
Inferencing hourly traffic volume using data-driven machine learning and graph theory32
Towards a multidimensional view of tourist mobility patterns in cities: A mobile phone data perspective32
Simulating the urban spatial structure with spatial interaction: A case study of urban polycentricity under different scenarios32
Modeling urban growth sustainability in the cloud by augmenting Google Earth Engine (GEE)31
Establishing a citywide street tree inventory with street view images and computer vision techniques31
Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data30
Quality of location-based crowdsourced speed data on surface streets: A case study of Waze and Bluetooth speed data in Sevierville, TN30
Assessing the influence of point-of-interest features on the classification of place categories29
Impact of extreme weather events on urban human flow: A perspective from location-based service data29
“Domains of deprivation framework” for mapping slums, informal settlements, and other deprived areas in LMICs to improve urban planning and policy: A scoping review29
Scaling of urban economic outputs: insights both from urban population size and population mobility28
Peeking inside the black-box: Explainable machine learning applied to household transportation energy consumption28
Advancing scenario planning through integrating urban growth prediction with future flood risk models28
A geographic data science framework for the functional and contextual analysis of human dynamics within global cities28
Numerical modelling for analysis of the effect of different urban green spaces on urban heat load patterns in the present and in the future28
Towards user-driven earth observation-based slum mapping26
Modeling urban development and its exposure to river flood risk in Southeast Asia26
Free and open source urbanism: Software for urban planning practice26
Towards generating network of bikeways from Mapillary data26
Spatio-temporal graph convolutional networks for road network inundation status prediction during urban flooding25
Quantify city-level dynamic functions across China using social media and POIs data25
Quality assessment of crowdsourced social media data for urban flood management25
Coupling graph deep learning and spatial-temporal influence of built environment for short-term bus travel demand prediction25
Mapping the geodemographics of digital inequality in Great Britain: An integration of machine learning into small area estimation25
BiFlowLISA: Measuring spatial association for bivariate flow data25
Sensing urban soundscapes from street view imagery25
Calibrating SLEUTH with big data: Projecting California's land use to 210024
An extended patch-based cellular automaton to simulate horizontal and vertical urban growth under the shared socioeconomic pathways24
Geographic micro-process model: Understanding global urban expansion from a process-oriented view24
A building volume adjusted nighttime light index for characterizing the relationship between urban population and nighttime light intensity24
Impact of 3-D urban landscape patterns on the outdoor thermal environment: A modelling study with SOLWEIG24
Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City24
Advances in portable sensing for urban environments: Understanding cities from a mobility perspective23
The importance of spatio-temporal infrastructure assessment: Evidence for 5G from the Oxford–Cambridge Arc23
Sensing urban poverty: From the perspective of human perception-based greenery and open-space landscapes23
Measuring inequalities in urban systems: An approach for evaluating the distribution of amenities and burdens22
Multiscale analysis of the influence of street built environment on crime occurrence using street-view images22
You are how you travel: A multi-task learning framework for Geodemographic inference using transit smart card data22
An efficient dynamic route optimization for urban flooding evacuation based on Cellular Automata21
Integrating spatial nonstationarity into SLEUTH for urban growth modeling: A case study in the Wuhan metropolitan area21
Life is a scene and we are the actors: Assessing the usefulness of planning support theatres for smart city planning21
A spatiotemporal dynamic analyses approach for dockless bike-share system20
Modelling the effect of landmarks on pedestrian dynamics in urban environments20
A multi-objective Markov Chain Monte Carlo cellular automata model: Simulating multi-density urban expansion in NYC20
Equalizing the spatial accessibility of emergency medical services in Shanghai: A trade-off perspective20
Automatic detection of potential mosquito breeding sites from aerial images acquired by unmanned aerial vehicles20
Identifying degrees of deprivation from space using deep learning and morphological spatial analysis of deprived urban areas19
SALT: A multifeature ensemble learning framework for mapping urban functional zones from VGI data and VHR images19
An iterative tessellation-based analytical approach to the design and planning of waste management regions19
Urban expansion simulation from the perspective of land acquisition-based on bargaining model and ant colony optimization19
Which city is the greenest? A multi-dimensional deconstruction of city rankings19
Using smartphone-GPS data to understand pedestrian-scale behavior in urban settings: A review of themes and approaches19
Road network evolution in the urban and rural United States since 190019
Vital triangle: A new concept to evaluate urban vitality19
GeoAI in terrain analysis: Enabling multi-source deep learning and data fusion for natural feature detection18
A data-driven agent-based simulation to predict crime patterns in an urban environment18
Incorporating space and time into random forest models for analyzing geospatial patterns of drug-related crime incidents in a major U.S. metropolitan area18
Exploring the effect of urban spatial development pattern on carbon dioxide emissions in China: A socioeconomic density distribution approach based on remotely sensed nighttime light data18
Towards the automated large-scale reconstruction of past road networks from historical maps18
Comprehensive decision-strategy space exploration for efficient territorial planning strategies18
Structural changes in intercity mobility networks of China during the COVID-19 outbreak: A weighted stochastic block modeling analysis18
A new approach to detecting and designing living structure of urban environments18
Multi-objective optimization of urban environmental system design using machine learning17
Optimization of carsharing fleet size to maximize the number of clients served17
Understanding the movement predictability of international travelers using a nationwide mobile phone dataset collected in South Korea17
Shared automated vehicle fleet operations for first-mile last-mile transit connections with dynamic pooling17
Space-time analytics of human physiology for urban planning17
Mapping dynamic peri-urban land use transitions across Canada using Landsat time series: Spatial and temporal trends and associations with socio-demographic factors16
Ridesharing accessibility from the human eye: Spatial modeling of built environment with street-level images16
Determination of building flood risk maps from LiDAR mobile mapping data16
Urban morphological regionalization based on 3D building blocks—A case in the central area of Chengdu, China16
Combining a land parcel cellular automata (LP-CA) model with participatory approaches in the simulation of disruptive future scenarios of urban land use change16
Converting street view images to land cover maps for metric mapping: A case study on sidewalk network extraction for the wheelchair users16
Using a deep learning model to quantify trash accumulation for cleaner urban stormwater16
Mapping the walk: A scalable computer vision approach for generating sidewalk network datasets from aerial imagery16
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