TY - JOUR
T1 - A study on identification of the heat vulnerability area considering spatial autocorrelation - Case study in Daegu
AU - Seong, Ji Hoon
AU - Lee, Ki Rim
AU - Kwon, Yong Seok
AU - Han, You Kyung
AU - Lee, Won Hee
N1 - Publisher Copyright:
© 2020 Korean Society of Surveying. All rights reserved.
PY - 2020
Y1 - 2020
N2 - The IPCC (Intergovernmental Panel on Climate Change) recommended the importance of preventive measures against extreme weather, and heat waves are one of the main themes for establishing preventive measures. In this study, we tried to analyze the heat vulnerable areas by considering not only spatial characteristics but also social characteristics. Energy consumption, popu lation density, normalized difference vegetation index, waterfront distance, solar radiation, and road distribution were examined as variables. Then, by selecting a suitable model, SLM (Spatial Lag Model), available variables were extracted. Then, based on the Fuzzy theory, the degree of vulnerability to heat waves was analyzed for each variable, and six variables were superimposed to finally derive the heat vulnerable area. The study site was selected as the Daegu area where the effects of the heat wave were high. In the case of vulnerable areas, it was confirmed that the existing urban areas are mainly distributed in Seogu, Namgu, and Dalseogu of Daegu, which are less affected by waterside and vegetation. It was confirmed that both spatial and social characteristics should be considered in policy support for reducing heat waves in Daegu.
AB - The IPCC (Intergovernmental Panel on Climate Change) recommended the importance of preventive measures against extreme weather, and heat waves are one of the main themes for establishing preventive measures. In this study, we tried to analyze the heat vulnerable areas by considering not only spatial characteristics but also social characteristics. Energy consumption, popu lation density, normalized difference vegetation index, waterfront distance, solar radiation, and road distribution were examined as variables. Then, by selecting a suitable model, SLM (Spatial Lag Model), available variables were extracted. Then, based on the Fuzzy theory, the degree of vulnerability to heat waves was analyzed for each variable, and six variables were superimposed to finally derive the heat vulnerable area. The study site was selected as the Daegu area where the effects of the heat wave were high. In the case of vulnerable areas, it was confirmed that the existing urban areas are mainly distributed in Seogu, Namgu, and Dalseogu of Daegu, which are less affected by waterside and vegetation. It was confirmed that both spatial and social characteristics should be considered in policy support for reducing heat waves in Daegu.
KW - Climate Change
KW - Heat Vulnerability Area
KW - Moran's I
KW - Spatial Regression
KW - Vulnerability Assessment
UR - http://www.scopus.com/inward/record.url?scp=85093667463&partnerID=8YFLogxK
U2 - 10.7848/ksgpc.2020.38.4.295
DO - 10.7848/ksgpc.2020.38.4.295
M3 - Article
AN - SCOPUS:85093667463
SN - 1598-4850
VL - 38
SP - 295
EP - 304
JO - Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
JF - Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
IS - 4
ER -