*3.2. Land Surface Temperature Maps*

Figure 6 shows LST maps of the inner Hanoi City for (a) 1 June 2016 and (b) 4 June 2017, and their corresponding histogram distributions in (c) and (d), respectively. Three areas with substantial changes in LST are randomly chosen and labeled as B, E, and F in both (a) and (b) for a further interpretation of SUHI intensity's variation. It is found that the average LSTs are 40.9 ◦C and 40.1 ◦C for 1 June 2016 and 4 June 2017, respectively. That is, the average LST was slightly higher for the hottest days in 2016 than 2017 by 0.8 ◦C. Note that even with an overall warmer thermal environment for the whole of inner Hanoi City in 2016 than 2017, LSTs were lower in the areas with significant transformation of land-use from vegetation cover to built-up, labeled as B, E, and F, in 2016 than 2017 by 0.9, 0.8, and 2.5 ◦C, respectively. The number of pixels and mean LST for the three chosen areas B, E, and F on the two hottest days in 2016 and 2017 and the difference in LST between the two hottest days are shown in Table 7. Results indicate that the transformation of land-use from vegetation to built-up has enhanced the contrast in thermal signatures, i.e., LSTs, by 1.7, 1.6, and 3.3 ◦C in the three fast-changing land-use regions B, E, and F, respectively, in one year between years 2016 and 2017. The contrast confirms the cooling effect of vegetation cover on the SUHI intensity that cannot be overstressed in the hot urban cites.

**Figure 6.** Land surface temperature (LST) maps of inner Hanoi City for (**a**) 1 June 2016 and (**b**) 4 June 2017; and their corresponding histogram distributions in (**c**,**d**), respectively. Three areas with substantial changes in LST between two hottest days are randomly chosen and labeled as B, E, and F in both (**a**,**b**). The pixel size is 30 × 30 m.

**Table 7.** Number of pixels (1 pixel = 30 × 30 m) and mean LST for the three randomly chosen areas B, E, and F on the two hottest days in 2016 and 2017, and the difference in LST between the two hottest days.


As for the signature of the traditionally defined SUHI, it is analyzed here by assuming the boundary of Hanoi's downtown, that consists of seven districts, including Tay Ho, Hoan Kiem, Ba Dinh, Dong Da, Hai Ba Trung, Cau Giay, and Thanh Xuan Districts, as a mask to divide the urban (pink color) and suburban areas (green color), as shown in Figure 7. The statistics of urban and suburban LSTs are given in Table 8. The STDs in Table 8 represent the standard deviations of the LSTs retrieved from Landsat 8 images with a spatial resolution of 30 m.

**Figure 7.** The map shows downtown of inner Hanoi (pink color) and suburban (green color).



Table 8 indicates the mean LST of the urban area was higher by 0.53 ◦C than that in the suburban area in 2016. In contrast, in 2017, the LST of the urban area was lower than that in the suburban area, by 0.21 ◦C. This was due to the massive land use change in the suburban area, possibly resulting from the implementation of Hanoi Master Plan 2030, where many buildings are being constructed. That is, areas with vegetation and water surfaces in the suburban area are significantly reduced. Table 9 shows that the built-up area is increased by 4.28 km2 and vegetation decreased by 4.01 km<sup>2</sup> in the suburban belt in only a one year interval from 2016 to 2017. Consequently, fast urbanization in suburban area results in slightly higher LSTs in the suburban area than in urban area in 2017. This finding is also in line with the comparative results of the LST in the chosen areas B, E, and F, which are located in the suburban belt to demonstrate a negative SUHI in response to urban expansion in inner Hanoi City.


**Table 9.** Land use/land cover (LULC) change in urban and suburban areas of Hanoi in 2016–2017.
