4.2. Land-Use Distribution and Verification of Land-Use Classification
Unlike in Shenzhen, forest dominates in Hong Kong. Although Shenzhen has attempted to increase its proportion of forest cover, it remains less than Hong Kong’s, which has a vegetation cover rate exceeding 60%. By contrast, the high-albedo area in Shenzhen is greater than in Hong Kong (
Figure 4 and
Figure 5). In addition, Shenzhen’s high-albedo coverage has increased, indicating that the use of high-albedo materials has increased, while Hong Kong has remained almost unchanged.
The accuracy of the land-use classification was compared for the randomly selected ground true regions of interest (ROIs) and the classification results. From the classification results (
Table 2), it is clear that the MLP algorithm classification, based on supervised classification, was highly accurate. Moreover, small specific objects were outlined after the extraction of the multiple band characteristics and the MLP were developed by training on ROI samples. Furthermore, the classification accuracy was verified against the urban morphology, with the shapes of the cool roofs essentially outlined using the MLP algorithm. Thus, the MLP algorithm is suitable for classifying specific objects, such as cool roofs, consistent with the findings of previous studies [
21]. For example, on the basis of Google Earth Map data, as shown in
Table 4, the high-albedo features outlined in the classification correspond to large complex public buildings, such as the Shenzhen Bay Sports Center, Shenzhen Bao’an International Airport, Hong Kong International Airport, and Hong Kong Stadium.
4.3. Multiple Regression Analysis
Detailed multiple regression model results are provided in
Table 5 and
Table 6. Low-albedo features are excluded by the multiple-stepwise linear regression because of collinearity. In summary, most of the factors included in the multiple regression method are significant. The determined LSTs of the urban areas in Shenzhen are similar to those in Hong Kong, with a summer temperature of approximately 25 °C in both areas, versus a winter temperature of 16 °C. The vegetation and water have negative effects on the LSTs, but the soil and the high albedo have positive effects. The LSTs were stable, with no clear annual deviations. Importantly, the high-albedo coefficient in Hong Kong was higher than in Shenzhen, indicating that artificial heat is one of the most important sources of the temperature differences between these two areas. In addition, although time-series data were not used in this model, the multiple line regression was input with a temperature-independent variable. Because it may exist in the spatial autocorrelation among the temperature of the surrounding pixels, autocorrelation must be considered in the model and the DW test (a tool designed for testing autocorrelation). The regression model applied in Shenzhen is significant but it is not in the case of Hong Kong. The
p values in the t-statistics of Shenzhen and Hong Kong were less than 0.05, with Shenzhen’s DW values almost equal to 2, but Hong Kong’s less than 2, indicating autocorrelation in Hong Kong, perhaps as a result of the differences in the topographies between Shenzhen and Hong Kong. The relatively high-temperature area is wider in Shenzhen, but more centralized in Hong Kong, and because of the spatial autocorrelation, the multiple linear regression model is valid in Shenzhen, but is not statistically significant for Hong Kong and, thus, should be modified further using Moran’s I in ArcGIS.
The model result of November of 1998, Hong Kong, shows that if soil is increased in the urban area, the retrieval LST of the urban area will increase 2.29 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will increase 0.74 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 5.77 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 4.82 °C on average.
The model result of Shenzhen in the November of 1998 shows that if soil is increased in the urban area, the retrieval LST of the urban area will increase 1.21 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will decrease 0.20 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 8.86 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 4.34 °C on average.
The model result of Hong Kong in the November of 2004 shows that if soil is increased in the urban area, the retrieval LST of the urban area will increase 1.25 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will decrease 3.98 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 6.66 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 4.72 °C on average.
The model result of Shenzhen in the November of 2004 shows that if soil is increased in the urban area, the retrieval LST of the urban area will decrease 0.73 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will decrease 0.72 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 6.58 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 4.91 °C on average.
The model result of Hong Kong in the October of 2009 shows that if soil is increased in the urban area, the retrieval LST of the urban area will decrease 1.14 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will decrease 9.94 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 6.88 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 5.78 °C on average.
The model result of Shenzhen in the October of 2009 shows that if soil is increased in the urban area, the retrieval LST of the urban area will decrease 1.31 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will decrease −0.13 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 8.33 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 6.19 °C on average.
The model result of Hong Kong in the October of 2013 shows that if soil is increased in the urban area, the retrieval LST of the urban area will decrease 2.42 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will increase 5.95 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 4.31 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 4.42 °C on average.
The model result of Shenzhen in the October of 2013 shows that if soil is increased in the urban area, the retrieval LST of the urban area will increase 0.89 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will increase 2.93 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 2.08 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 3.85 °C on average.
The model result of Hong Kong in the February of 2018 shows that if soil is increased in the urban area, the retrieval LST of the urban area will increase 1.94 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will increase 6.89 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 6.72 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 3.73 °C on average.
The model result of Shenzhen in the February of 2018 shows that if soil is increased in the urban area, the retrieval LST of the urban area will increase 0.24 °C on average. If high albedo is increased in the urban area, the retrieval LST of the urban area will increase 6.40 °C on average. If water is increased in the urban area, the retrieval LST of the urban area will decrease 6.07 °C on average. If vegetation is increased in the urban area, the retrieval LST of the urban area will decrease 3.35 °C on average.