Spatio-temporal Data Analysis for Development of Microclimate Prediction Models

Tageui Hong, Yeonsook Heo

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Microclimate prediction models have been developed to consider the effects of urban variables on urban microclimate. However, existing studies have not fully exploited the spatio-temporal microclimate data and focused on either spatial or temporal aspects of microclimate conditions. In this study, we analyze the characteristics of full spatio-temporal data of 246 weather stations in Seoul, Korea through the widely used multiple linear regression and Gaussian process regression. We created a set of datasets with different levels of spatial-temporal variability and evaluated the suitability of the two methods and the characteristics of the microclimate data. The statistical analysis results indicate that the accuracy of predicting the urban heat island (UHI) intensity depends on a level of variability contained in the spatio-temporal data and the two methods cannot fully explain the effect of meteorological and urban variables on the UHI phenomena. The results suggest the need to develop an appropriate modelling methodology that can accurately capture full variability in the spatial-temporal data of microclimate conditions.

Original languageEnglish
Title of host publicationBS 2021 - Proceedings of Building Simulation 2021
Subtitle of host publication17th Conference of IBPSA
EditorsDirk Saelens, Jelle Laverge, Wim Boydens, Lieve Helsen
PublisherInternational Building Performance Simulation Association
Number of pages8
ISBN (Electronic)9781775052029
Publication statusPublished - 2022
Event17th IBPSA Conference on Building Simulation, BS 2021 - Bruges, Belgium
Duration: 2021 Sept 12021 Sept 3

Publication series

NameBuilding Simulation Conference Proceedings
ISSN (Print)2522-2708


Conference17th IBPSA Conference on Building Simulation, BS 2021

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A2C1003751).

Publisher Copyright:
© International Building Performance Simulation Association, 2022

ASJC Scopus subject areas

  • Building and Construction
  • Architecture
  • Modelling and Simulation
  • Computer Science Applications


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