AI & foundation models for cities

From Frankenstein to Gulliver urbanism: Reframing AI and scale in urban theory

A geospatial decision support system for infrastructure planning: a GIS-machine learning-MCDM framework with an application to EV charging station planning

Monitoring and forecasting of urban air pollution and exceedance events: implications for environmental risk assessment and early warning communication using machine learning in sustainable cities

Forecasting Urban Heat Island hotspots using spatially aware machine learning: Explainable multi-model prediction with spatial validation and uncertainty analysis

A comparative machine learning assessment for urban flood susceptibility modeling and future flood susceptibility projections in Dhaka Metropolitan Area (DMA), Bangladesh

Space, sentiment, and social comparison: Decoding urban park satisfaction with Large Language Models

Modeling urban perception with large language models: A systematic review

Mapping vitality in Xi'an: Integrating Jacobs' criteria with machine learning for urban regeneration

The Prediction Optimization Bridge (POB): A Surrogate Assisted Random Forest–NSGA-II Framework for Energy Efficient Vehicle Routing

Exploring the interplay of sustainability and cultural values in urban design: Analyzing contemporary landscapes through machine learning (ML) insights modeling

Toward evidence-based zoning: A machine learning framework for land use compatibility assessment

Exploring the nonlinear impacts of the intra-urban built environment on carbon emissions using an interpretable ensemble machine learning framework

Urban Road Crash Severity Prediction Using Explainable Machine Learning and Spatial Hotspot Analysis: Evidence from Loja, Ecuador

Regional Innovation Disparities in Kazakhstan: Input–Output Misalignment in an Official Panel, 2014–2025

Adapting large language models for urban trip purpose inference: A domain-informed textual representation and fine-tuning framework

Nonlinear and heterogeneous effects of 2D/3D factors on global urban heat island using explainable spatial machine learning

Urban Flood Risk Prediction Based on the Hybrid Sampling of Imbalanced Data and Deep Learning Model

Global patterns of urban heat shaped by climate and morphology

Separates the heat-island contribution of background climate from that of surrounding urban form across 2,213 cities and projects how each will change.

Street View Imagery Analysis in a Computational Notebook

A hands-on methods chapter showing how to download street view images and apply deep convolutional networks to detect and measure features of the built environment, in a reproducible notebook.

Learning street view representations based on a spatiotemporal contrastive learning framework

Benchmarks representation-learning strategies for street view imagery and introduces a spatiotemporal contrastive framework to learn features useful for perception and socioeconomic prediction tasks.