Urban Heat Islands: Beating the Heat with Multi-Modal Spatial Analysis

TL;DR

This paper presents a multi-modal spatial analysis framework to understand how urban form influences the Urban Heat Island effect, using Singapore as a case study and combining remote sensing, geospatial, and population data.

Contribution

It introduces a novel multi-modal dataset and statistical modeling framework to analyze UHI in relation to urban form characteristics.

Findings

UHI intensity correlates with specific urban form features.

The framework effectively identifies key factors influencing UHI.

Results inform urban planning to mitigate heat effects.

Abstract

In today's highly urbanized environment, the Urban Heat Island (UHI) phenomenon is increasingly prevalent where surface temperatures in urbanized areas are found to be much higher than surrounding rural areas. Excessive levels of heat stress leads to problems at various levels, ranging from the individual to the world. At the individual level, UHI could lead to the human body being unable to cope and break-down in terms of core functions. At the world level, UHI potentially contributes to global warming and adversely affects the environment. Using a multi-modal dataset comprising remote sensory imagery, geo-spatial data and population data, we proposed a framework for investigating how UHI is affected by a city's urban form characteristics through the use of statistical modelling. Using Singapore as a case study, we demonstrate the usefulness of this framework and discuss our main findings in understanding the effects of UHI and urban form characteristics.