Relevant research has investigated how predictive modeling algorithms, deep-learning-
based sensing technologies, and big urban data configure immersive hyperconnected …

With the rise of GeoAI research, streetscape imagery has received extensive attention due to
its comprehensive coverage, abundant information, and accessibility. However, obtaining a …

Today, technological developments are ever-growing yet fragmented. Alongside
inconsistent digital approaches and attitudes across city administrations, such developments …

The present study systematically reviews the existing research on urban digital twins,
machine learning techniques, and 3D city modeling and virtual simulation tools. Our findings …

This paper presents a system of autonomous intelligent software agents, based on a
cognitive architecture, capable of automated instantiation, visualisation and analysis of …

This article develops an ontological description of land use and applies it to incorporate
geospatial information describing land coverage into a knowledge-graph-based Universal …

Urban planning relies on the definition, modelling and evaluation of multidimensional
phenomena for informed decision-making. Urban building energy modelling, for instance …

Abstract Urban Digital Twins (UDTs) have become the new buzzword for researchers,
planners, policymakers, and industry experts when it comes to designing, planning, and …

This article applies a knowledge graph-based approach to unify multiple heterogeneous
domains inherent in climate and energy supply research. Existing approaches that rely on …

Semantic web technologies have the potential to significantly improve urban regulatory data
access, integration and usability, with potentially large implications for planning practice …