density tends to moderate. Therefore, the nuclear build-
ing density in the space search radius of 600 m has the best
reflection impact of heat island strength. That is, the building
density of the observation point has the maximum impact of
heat island strength within a radius of 600 m.
Influence of Nuclear Building Density on Heat Island Strength
The intensity of
UHI
is mainly reflected in the temperature,
humidity, and other changes. Many factors affect intensity
change. Therefore, building density is compared with the
temperature and humidity in 2000 and 2009 at various scales.
Table 2 shows that at the 0.01 significance level, a significant
correlation exists between building density and temperature
and humidity at various scales. Moreover, the humidity is
more apparent than the temperature and the change in Janu-
ary is more intense than in July. Meanwhile, the analysis
results show that a slight decrease and gradual increase in the
correlation between building density and temperature and
humidity after 600 m are observed.
These results are closely related to
the change of building density in the
change of scale. Building density in
the space search radius of 600 m has
the best reflection impact on the heat
island strength.
The correlation coefficient of
temperature and building density in
Table 2 is 0.54, thereby indicating the
existence of a close, positive correla-
tion. Thus, a high density of urban
buildings will result in a high tem-
perature. Numerous urban buildings
results in a reduction in wind speed
in the area, thereby reducing the air
ventilation efficiency in the region.
This outcome may be observed with-
out wind in the local area, thereby
resulting in a further increase in the
regional air temperature. Further-
more, free space is nearly absent in
the urban high-density building area
as a place of public activity, such as
greening and square, and man-made
heat is likely to be produced. Hence,
the regional heat island effect dete-
riorates. However, when only a few
buildings are present and the distri-
bution is sparse, the exchange of hot
and cold air is favorable, air ventila-
tion efficiency is high, and the heat
island effect is relatively weak. How-
ever, the large distance among build-
ings in a high-rise building area is
favorable for air ventilation efficiency.
A high-rise building can appropri-
ately increase the ground shadow
area, thereby reducing the cumulative
sunshine time in the area. This result
reduces the non-building surface ac-
ceptance of the solar direct radiation,
thereby decreasing the solar radiation
generated by the warming.
Discussion
To verify the effects of various build-
ing densities on the heat island effect,
this study used the buildings (con-
struction area: see Figure 8b) within
Guangzhou City as the land use type
for the heat island effect simulation analysis. The ideal sen-
sitivity tests are performed using the
WRF
mode coupled with
the multi-layer urban canopy model (
BEP
). A total of 30 eta
levels with the pressure of 50 hPa at top level are used. The
domain uses a grid of 100 × 110, 94 × 100, 161 × 136, and 160
× 178 with horizontal spatial resolutions of 45, 15, 3, and 1
km, respectively. The most inner domain (D04) covers the en-
tirety of Guangzhou. The simulation area is shown in Figure
8a. The meteorological initial and boundary conditions were
derived from the National Centers for Environmental Predic-
tion global reanalysis data of 1°×1°.
Considering the spin-up time, the simulation time is
from 00:00 (world time) on 31 October, 2016 to 00:00 on 04
November, while the analysis period is from 00:00 (local
time) on 02 November to 23:00 on 03 November. Guangzhou
has fine weather during this time period, thereby making
Table 2. Correlation coefficient between building density and temperature/humidity in scale.
Scale (meters)
Humidity
between 2000
and 2009 years
in January(Rh2)
Temperature
between 2000
and 2009 years
in January(°C)
Humidity
between 2000
and 2009 years
in July(Rh2)
Temperature
between 2000
and 2009 years
in July(°C)
100
0.30
0.22
0.25
0.26
150
0.34
0.27
0.28
0.29
200
0.38
0.32
0.32
0.33
250
0.41
0.36
0.35
0.36
300
0.42
0.38
0.36
0.37
350
0.44
0.39
0.38
0.39
400
0.45
0.40
0.39
0.39
450
0.46
0.41
0.39
0.40
500
0.46
0.41
0.40
0.41
550
0.47
0.42
0.41
0.42
600
0.49
0.43
0.44
0.45
650
0.48
0.42
0.43
0.44
700
0.48
0.41
0.43
0.44
750
0.49
0.41
0.44
0.45
800
0.50
0.42
0.45
0.46
850
0.51
0.42
0.46
0.47
900
0.51
0.43
0.47
0.48
950
0.53
0.43
0.48
0.49
1000
0.54
0.44
0.50
0.50
Figure 8. Schematic diagram of the simulation area (a) and urban land use type
distribution of Guangzhou (b)
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
September 2018
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