TY - JOUR
T1 - Urban morphology indicator analyzes for urban energy modeling
AU - Chen, Hung-Chu
AU - Han, Qi
AU - de Vries, Bauke
PY - 2020/1/1
Y1 - 2020/1/1
N2 - The reduction of energy consumption in the urban environment has attracted numerous studies in recent decades. However, limited studies have been conducted to investigate the impact of urban morphology on urban energy demand. Eindhoven serves as a case study in this paper to analyze the spatial relation between energy demand and urban morphology indicators (UMIs). UMIs are calculated by Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), building height, plot area, and building volume. The energy demand is calculated using annual gas and electricity demand. The ordinary least squares regression (OLS) and geographically weighted regression (GWR) models are applied to find the relation between energy demand and the UMIs. For the spatial regression, land-use is clustered into five types: urban areas (U), open space (O), artificial green areas (G), natural green areas (V), and water body (W). The results revealed that the energy demand and UMIs have a significant spatial relation. Urban energy demand as a dependent variable is best described by a combination of NDVI, building height, and plot area as the independent variables. The developed model can support local authorities in developing sustainable strategies and efficient energy planning.
AB - The reduction of energy consumption in the urban environment has attracted numerous studies in recent decades. However, limited studies have been conducted to investigate the impact of urban morphology on urban energy demand. Eindhoven serves as a case study in this paper to analyze the spatial relation between energy demand and urban morphology indicators (UMIs). UMIs are calculated by Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), building height, plot area, and building volume. The energy demand is calculated using annual gas and electricity demand. The ordinary least squares regression (OLS) and geographically weighted regression (GWR) models are applied to find the relation between energy demand and the UMIs. For the spatial regression, land-use is clustered into five types: urban areas (U), open space (O), artificial green areas (G), natural green areas (V), and water body (W). The results revealed that the energy demand and UMIs have a significant spatial relation. Urban energy demand as a dependent variable is best described by a combination of NDVI, building height, and plot area as the independent variables. The developed model can support local authorities in developing sustainable strategies and efficient energy planning.
KW - Energy demand model
KW - Geographically weighted regression (GWR)
KW - Normalized difference built-up index (NDBI)
KW - Normalized difference vegetation index (NDVI)
KW - Urban morphology
UR - http://www.scopus.com/inward/record.url?scp=85072762399&partnerID=8YFLogxK
U2 - 10.1016/j.scs.2019.101863
DO - 10.1016/j.scs.2019.101863
M3 - Article
AN - SCOPUS:85072762399
SN - 2210-6707
VL - 52
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 101863
ER -