*2.1. Study Area*

Hangzhou (118◦21–120◦31E, 29◦11–30◦33N) is the capital city of Zhejiang Province, whose GDP ranks among the top 10 in China, with 8.133 million in urban population, 2.227 million in rural population and an urbanization rate of 78.5% in 2019. It is located in the north of Zhejiang Province with a subtropical humid monsoon climate. As for temperature, it is lowest in January (average of 3–5 ◦C) and highest in July (average of 28–29 ◦C) with an annual average of 15.3–17 ◦C. The extreme maximum and minimum temperatures in Hangzhou reached 42.9 ◦C (31 July 1971) and −15 ◦C (5 January 1977). For precipitation, the annual average is 1100–1600 mm with rainy days of 130–160 days/year. There are two rainy seasons throughout the year. The first is the plum flood season from May to June, with an average rainfall of 350–500 mm, accounting for 25–31% of the year. The second rainy season is the typhoon rainy season from August to September, with an average rainfall of 120–220 mm, accounting for 8–13%. The forest coverage rate is over 64.77% (about 10,900 km2), dominated by evergreen broad-leaved forests and deciduous broad-leaved forests. In this study, the land cover map with 10 m-spatial resolution in 2017 from Gong Peng Research Group of Tsinghua University was aggregated to pixels of 500 m × 500 m to extract forest areas for the following analysis. To assure both a certain level of homogeneity in the land cover type and an adequate number of pixels for a meaningful analysis, only the pixels of 500 m where the forest type was over 75% were included in this study. Besides, the multi-temporal dataset of global urban boundaries of 2018 was used to divide the scope of the urban and the rural of Hangzhou Figure 1. This dataset is derived from the Global Artificial Impervious Area-GAIA, released by Gong Peng Research Group of Tsinghua University [37]. Then, 5 test areas of deciduous broad-leaved forest were selected in the urban and the rural (i.e., 10 km away from the urban area) of Hangzhou, respectively. In each test area, 2 sample points, a total of 20 sample points, were extracted (Figure 1). Besides, the Google map, latitude and longitude of the test areas in the urban and rural were showed in Table 1.

**Table 1.** The Google map, latitude and longitude of the test areas in the urban and rural.

**Figure 1.** Spatial distribution of Hangzhou and the location of forest test areas. The small maps in the upper right corner show the location of Hangzhou in Zhejiang Province and the location of Zhejiang Province in China.

#### *2.2. Remote Sensing Data*

#### 2.2.1. Land Surface Temperature

MODIS MYD11A2 LST product was used in this study, including the LST during the daytime and the nighttime, with a spatial resolution of 1000 m and a temporal resolution of 8 days. The LST of Aqua satellite is observed at 1:30 and 13:30 local solar time, the lowest and highest temperature of the day, which is more representative than that of Terra (monitored at 10:30 and 22:30) in the study of urban heat island. Therefore, the LST data of the Aqua satellite were used in this study [38,39]. The MODIS Reprojection Tool (MRT) was used to process the original images of LST, and so did the following data. Then, they were extracted in light of the study area and resampled to 500 m to be consistent with the phenology data. In addition, to explore the quantitative contributions of the ΔLST to the ΔSOS under urbanization, we collected 1000-m spatial resolution LST data of daytime and nighttime from 2006 to 2018 according to the coordinates of forest sample points.
