Urban form, urban heat island effect and energy demand: Insights from Seoul

Analyzing the Influence of Urban Form Elements on the Urban Heat Island (UHI) Effect and Building Energy Performance in a High-Density Urban Context

Master Thesis (2025)
Author(s)

G. Song (TU Delft - Architecture and the Built Environment)

Contributor(s)

M.A. Mosteiro Romero – Mentor (TU Delft - Environmental & Climate Design)

A. Rafiee – Mentor (TU Delft - Digital Technologies)

M.N. Boeve – Graduation committee member (TU Delft - Urban Development Management)

Faculty
Architecture and the Built Environment
More Info
expand_more
Publication Year
2025
Language
English
Coordinates
37.505500, 126.962300
Graduation Date
29-10-2025
Awarding Institution
Delft University of Technology
Programme
['Architecture, Urbanism and Building Sciences | Building Technology']
Faculty
Architecture and the Built Environment
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

This study investigates the relationships between urban form elements (UFEs), Urban Heat Island (UHI) effects, and building energy consumption in Heukseok-dong, Seoul, South Korea. Using 10 years of satellite imagery, air temperature measurements, and energy consumption data, the research examines how six UFEs (NDVI, building ratio, building height, building volume, FSI, and GSI) influence air temperatures and building energy consumption across multiple spatial scales and seasons. A Multi-Layer Perceptron (MLP) neural network was developed to convert satellite-derived Land Surface Temperature (LST) to air temperature, achieving an R2 of 0.9684, and tested with independent S-DoT sensors. The independent testing was conducted in two phases: for May-August 2020, the mean temperature difference was 1.84°C, remarkably close to the known systematic temperature difference of 1.8°C between S-DoT sensors and AWS. When extended to 2020-2024, the mean
difference was 0.98°C with an R2 of 0.807, confirming the model successfully predicts actual air temperatures rather than sensor-specific values. The Genizi method and partial correlation analysis were combined to address multicollinearity while revealing both relative importance and directional effects of UFEs. This complementary approach provides more comprehensive insights than traditional regression methods alone. Key findings reveal that NDVI dominates temperature variance in spring (79.3%), fall (64.7%), and winter (71.6%), but building characteristics become more important in summer, with building ratio contributing 71.8% at pixel scale. Scale-dependent patterns emerged, with energy consumption best captured at 100m scale (R2 up to 0.378) while temperature variations appeared more clearly at 300m scale (R2 up to 0.328). The cascade relationship from UFE through air temperature to energy consumption showed air temperature driving 54.3% of electricity variance in summer, while building volume consistently influenced both electricity and gas consumption despite EUI normalization. A decade-long analysis of District 3’s transformation from 478 low-rise buildings to 28 high-rise apartments confirmed the statistical findings. Despite a 2,112.6% increase in building volume and 168% improvement in NDVI, temperature trends showed 0.10-0.16°C/year increases, which are approximately half of Heukseok-dong’s 0.17-0.32°C/year rates, demonstrating that urban design can partially mitigate but not eliminate warming effects. The moderate R2 values (0.067-0.378) indicate that urban form elements explain only a portion of variance, partly reflecting the temporal limitation of correlating single hourly satellite observations with monthly energy totals. The research provides evidence-based recommendations for urban planning policies, including maintaining GSI below 0.55, achieving NDVI above 0.15, and implementing seasonal strategies for temperature mitigation and energy management.

Files

Thesis_Report_Final.pdf
(pdf | 138 Mb)
License info not available
P5_Presentation.pdf
(pdf | 27.7 Mb)
License info not available
P2_Graduation_Plan.pdf
(pdf | 0.173 Mb)
License info not available
Final_Reflection.pdf
(pdf | 0.225 Mb)
License info not available