Urban Comfort Assessment in the Era of Digital Planning: A Multidimensional, Data-driven, and AI-assisted Framework

TL;DR

This paper proposes a comprehensive, data-driven, and AI-assisted framework for assessing urban comfort, integrating multiple dimensions to improve urban planning and livability evaluations.

Contribution

It introduces a novel multidimensional and data-supported framework that leverages AI to enhance urban comfort assessment in digital planning.

Findings

Highlights the importance of multidimensional analysis for urban comfort

Proposes an integrated framework combining data and AI tools

Provides a theoretical basis for future urban comfort evaluations

Abstract

Ensuring liveability and comfort is one of the fundamental objectives of urban planning. Numerous studies have employed computational methods to assess and quantify factors related to urban comfort such as greenery coverage, thermal comfort, and walkability. However, a clear definition of urban comfort and its comprehensive evaluation framework remain elusive. Our research explores the theoretical interpretations and methodologies for assessing urban comfort within digital planning, emphasising three key dimensions: multidimensional analysis, data support, and AI assistance.