UNIST Heatwave Research for National Heat Wave Policy

Country
South Korea
Sustainable development goals
  • Climate action
  • Partnerships for the goals
  • Sustainable cities and communities
Project link
http://ksrs.or.kr/journal/journal06.asp

About the project

UNIST Heatwave Research is a government-funded project that uses artificial intelligence to analyze heatwave data and predict thermal characteristics of the land.

More project information

UNIST Heatwave Research is a government-funded project that uses artificial intelligence to analyze heatwave data and predict thermal characteristics of the land. Since the spatial distribution of heat in a city varies by region, it is crucial to investigate detailed thermal characteristics of urban areas. 

In the UNIST Heatwave Research, in order to examine the thermal characteristics of Daegu Metropolitan City during the summers between 2012 and 2016, Moderate Resolution Imaging Spectroradiometer (MODIS) was used during the daytime and nighttime to determine the land surface temperature (LST). Data at 1 km spatial resolution was downscaled to a spatial resolution of 250 meter using a machine learning method called random forest. Compared to the original 1 km LST, the downscaled 250 m LST showed a higher correlation between the proportion of impervious areas and mean land surface temperatures in Daegu by the administrative neighborhood unit. Hot spot analysis was then conducted using downscaled daytime and nighttime 250 m LST. The clustered hot spot areas for daytime and nighttime were compared and examined based on the land cover data provided by the Ministry of Environment. The high-value hot spots were relatively more clustered in industrial and commercial areas during the daytime and in residential areas at night. 

The UNIST Heatwave Research will help meet the SDGs of creating Sustainable Cities and Communities and Life on Land by allowing people living in those communities to better plan for heat wave. It will also help meet the goal of Climate Action by helping predict both heat wave and cold wave, which are increasingly prevalent due to climate change. The Research will also help promote Partnerships for the Goals as the thermal characterization of urban areas using the method proposed in this research is expected to contribute to the establishment of the national city and security policies.