Fig 1.
Continuous urban area and 277 census tracts used in the analysis.
Background image: NASA Landsat Program, 2010, Landsat 5TM+ scene 20100319.141244/233_083_0/2, Bands 472, USGS, Sioux Falls, 03/19/2010.
Table 1.
Summary of data sources for the variables used in the analysis.
Fig 2.
a) Land surface temperature (LST) and b) Normalized diference vegetation index (NDVI) for Santiago.
LST and NDVI indexes were calculated based on satellite image taken from NASA Landsat Program, 2009, Landsat TM, scene LT52330832009075COA02, L17, USGS, Sioux Falls, 03/16/2009.
Fig 3.
Scatter plots for z-values of sensitivity and adaptive capacity.
PC loadings are shown in red.
Table 2.
PC loadings for sensitivity (above) and adaptive capacity variables following varimax rotation.
Table 3.
Pearson correlation matrix (r-values) between main indexes used in the analysis.
The built-up density is used as a spatial parameter for comparisons. P-values are significant at 0.01.
Table 4.
List of 41 census tracts with higher HVI values.
Fig 4.
Normalized values for HVI, exposure, sensitivity and adaptive capacity for the 41 census tracts with higher values HVI.
HVI increases towards the northern end of the city.
Fig 5.
Results for a) exposure, b) sensitivity, c) adaptive capacity and d) the heat vulnerability index at the census tract level for Santiago.
Table 5.
List of 52 census tracts contained in the four indicated clusters.
Fig 6.
Anselin I Moran for exposure a), sensitivity b), adaptive capacity c) and HVI d). The four clusters of high HVI values are indicated in caption d) with the number 1, 2, 3 and 4. High High for a statistically significant (0.05 level) cluster of positive high values (z-scores) and Low Low for a statistically significant (0.05 level) cluster of positive low values. Statistically significant spatial outliers (0.05 level) are indicated by negative z-scores: High Low if the feature has a high value and is surrounded by features with low values and Low High if the feature has a low value and is surrounded by features with high values.
Table 6.
Correlation matrix (r-values) between HVI and the original variables used in the PCA.
Fig 7.
Spider plot for the sensitivity analysis for adaptive capacity (left) and HVI (right) for the 52 census tracts existing in the four heat vulnerability clusters.
Table 7.
Main statistics for partial indexes and HVI calculated for four clusters.