Author: S. Hsu, A. Mavrogianni, I. Hamilton

Year: 2017

Published in: Procedia Engineering Volume 198

The threat of elevated temperatures and more intense and prolonged heat waves coupled with urban heat islands presents a significant risk to human health. City planners and policymakers need tools that predict how overheating risk varies within a city under different climate change and mitigation scenarios. A key driver of determining overheating risk is exposure to local urban temperatures and the extent to which such exposure may be modified by built environments where the majority of people spend their time. Due to the dispersion of monitoring stations, techniques are needed to extrapolate from single point measurements and their modifying determinants. This research aims to compare nine GIS spatial interpolation techniques of estimating street-level temperature in a subtropical city.


Methods:  Taipei city, Taiwan, is located in a subtropical zone with one of the highest population densities in the world. Taipei experienced warmer winters and hotter summers in recent 10 years with average temperature from 16.4 to 30.1 °C, and expected to rise from 0.8(RCP2.6) to 3.2(RCP8.5)°C in 2081-2100. In this study, data from the Taiwan Central Weather Bureau weather stations and the Taiwan Environmental Protection Administration air monitoring sites were used. Nine interpolation techniques were applied. These were validated by using records from two sources to cross-validate by comparing Standardised mean error and Standardised Root-Mean-Square error.


Results:  Kriging techniques have better prediction performance than four non-geostatistical interpolation techniques. The performance of OCK techniques indicated the built environment, such as the nearby village park area or home density, can be important modifiers of external temperature in cities.  Discussion:  Local urban climates are complex systems; selecting a robust interpolation technique that accounts for underlying drivers is essential for policymakers. This research provides the basis to further estimate overheating risk by estimating local outdoor street-level temperature and the modifying effects of the built environment.

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