Vol. 6 pp.27 - 38.

AbstractAs the climate problem becomes more serious, mitigating the heat island effect is becoming an important issue. To solve the problem, it is necessary to identify the areas where the heat island effect is more severe and present appropriate measures to those areas. In this paper, we divided Seoul into 573 grids and divided into four clusters by hierarchical clustering techniques to identify the current status of the city's heat island effect. Of these cluster, we chose the one with the most urban features. We extracted the variable importance with random forest models and developed the heat island index from 1) multiplication of the variable importance and 2) the sign of the correlation coefficient between temperature and 3) the corresponding variable. Furthermore we analyzed areas where the heat island effect is severe with the index. According to the analysis, the heat island effect was particularly severe in five grids, and we suggested ways to mitigate the heat island effect for the areas concerned.