Appendix

Table S1 Pearson correlation coefficients between urban impervious surfaces and land surface temperatures for different ecoregions.

Ecoregion / Summer day / Summer night / Winter day / Winter night
Junggar Basin semi-desert (JBSD) / 0.651** / -0.089* / -0.095* / 0.200**
Manchurian mixed forests (MMF) / 0.456** / 0.170** / -0.130** / 0.114**
Northeast China Plain deciduous forests (NCPDF) / 0.397** / 0.179** / -0.212** / 0.000
Mongolian-Manchurian grassland (MMG) / 0.416** / 0.307** / 0.259** / 0.377**
Huang He Plain mixed forests (HHPMF) / 0.341** / 0.322** / -0.300** / 0.071**
Central China loess plateau mixed forests (CCLPMF) / 0.333** / 0.170** / -0.268** / 0.000
Changjiang Plain evergreen forests (CPEF) / 0.187** / 0.195** / -0.105** / 0.184**
Daba Mountains evergreen forests (DMEF) / 0.032 / 0.417** / 0.126** / 0.550**
Sichuan Basin evergreen broadleaf forests (SBEBF) / 0.338** / 0.469** / 0.032 / 0.270**
Jian Nan subtropical evergreen forests (JNSEF) / 0.138** / 0.295** / 0.324** / 0.387**
Yunnan Plateau subtropical evergreen forests (YPSEF) / 0.378** / 0.110** / 0.077** / 0.000
South China-Vietnam subtropical evergreen forests (SCVSEF) / 0.141** / 0.427** / 0.134** / 0.126**

**Significant at the 0.01 level; *Significant at the 0.05 level.

Table S2 Pearson correlation coefficients between urban impervious surfaces and land surface temperatures for different urban clusters.

Urban cluster / Summer day / Summer night / Winter day / Winter night
North slopes of Tianshan Mountains / 0.559** / 0.145** / 0.219** / 0.000
Harbin-Daqing-Changchun / 0.452** / 0.602** / -0.100** / 0.365**
Liaodong Peninsula / 0.539** / 0.428** / -0.249** / -0.077**
Beijing-Tianjin-Hebei / 0.424** / 0.381** / -0.145** / 0.401**
Hohhot-Baotou-Ordos / 0.473** / 0.600** / -0.179** / 0.606**
Shandong Peninsula / 0.366** / 0.409** / -0.214** / 0.339**
Jinzhong / 0.207** / 0.581** / -0.300** / 0.383**
Central Plains / 0.535** / 0.562** / -0.382** / 0.335**
Yangtze River Delta / 0.141** / 0.277** / -0.077** / 0.217**
Jianghuai / 0.409** / 0.434** / -0.063** / 0.379**
Wuhan / 0.167** / 0.412** / -0.105** / 0.455**
Chengyu / 0.148** / 0.473** / -0.071** / 0.365**
Changsha-Zhuzhou-Xiangtan / 0.055 / 0.640** / -0.100** / 0.537**
Dianzhong / 0.569** / 0.285** / 0.288** / 0.237**
Pearl River Delta / 0.152** / 0.371** / 0.197** / 0.152**

**Significant at the 0.01 level; *Significant at the 0.05 level.

Table S3Pearson correlation coefficients between urban impervious surfaces and land surface temperatures for different urban core areas.

Urban cluster / Urban core / Summer day / Summer night / Winter day / Winter night
Ha-Da-Chang / Daqing / 0.358** / 0.496** / 0.032 / 0.565**
Harbin / 0.492** / 0.738** / 0.055 / 0.767**
Changchun / 0.735* / 0.734** / -0.383** / 0.719**
Liaodong Peninsula / Anshan / 0.722** / 0.657** / 0.214** / 0.444**
Fushun / 0.462** / 0.546** / 0.032 / 0.504**
Shenyang / 0.746** / 0.689** / -0.435** / 0.724**
Jing-Jin-Ji / Beijing / 0.684** / 0.607** / -0.134** / 0.573**
Shijiazhuang / 0.734** / 0.746** / -0.402** / 0.727**
Tianjin / 0.428** / 0.690** / 0.110** / 0.652**
Hu-Bao-E / Baotou / 0.467** / 0.562** / 0.032 / 0.508**
Erdos / 0.268* / 0.680** / 0.077 / 0.579**
Hohhot / 0.662** / 0.709** / -0.537** / 0.660**
Shandong Peninsula / Jinan / 0.609** / 0.586** / 0.045 / 0.421**
Qingdao / 0.313** / 0.492** / -0.100* / 0.437**
Weifang / 0.804** / 0.715** / -0.476** / 0.654**
Jinzhong / Taiyuan / 0.464** / 0.635** / -0.259** / 0.534**
Yangquan / 0.313* / 0.584** / 0.158 / 0.344*
Yuci / 0.553** / 0.727** / 0.084 / 0.612**
Central Plains / Luoyang / 0.500** / 0.676** / -0.511** / 0.498**
Pingdingshan / 0.245* / 0.610** / -0.217* / 0.507**
Zhengzhou / 0.754** / 0.723** / -0.487** / 0.619**
Yangtze River Delta / Hangzhou-Shaoxing / 0.155** / 0.329** / 0.045 / 0.214**
Nanjing / 0.200** / 0.543** / -0.184** / 0.224**
Shanghai-Suzhou-Wuxi / 0.148** / 0.359** / -0.032* / 0.266**
Jianghuai / Anqing / 0.063 / 0.481** / -0.391** / 0.711**
Hefei / 0.578** / 0.560** / -0.184** / 0.534**
Wuhu / 0.084 / 0.625** / 0.055 / 0.796**
Wuhan / Huangzhou / 0.268 / 0.032 / 0.000 / 0.348*
Wuhan / 0.241** / 0.359** / 0.032 / 0.427**
Xianning / 0.000 / 0.251 / 0.170 / 0.045
Chengyu / Chengdu / 0.446** / 0.602** / 0.000 / 0.497**
Mianyang / 0.412** / 0.497** / 0.268** / 0.371**
Chongqing / 0.000 / 0.611** / -0.173** / 0.541**
Chang-Zhu-Tan / Changsha / 0.089* / 0.708** / 0.045 / 0.607**
Xiangtan / -0.319** / 0.564** / -0.276** / 0.504**
Zhuzhou / 0.148* / 0.632** / 0.089 / 0.527**
Dianzhong / Kunming / 0.635** / 0.565** / 0.567** / 0.415**
Qujing / 0.694** / 0.624** / 0.418** / 0.620**
Yuxi / 0.298** / 0.402** / 0.261** / 0.536**
Pearl River Delta / Zhongshan / 0.045 / 0.292** / 0.000 / 0.235**
Guangzhou-Foshan-Shenzhen-Dongguan / 0.155** / 0.365** / 0.192** / 0.152**
Zhaoqing / 0.095 / 0.316 / 0.045 / 0.355*
North slopes of Tianshan Mountains / Changji / 0.625** / 0.243 / 0.000 / 0.195
Karamay / 0.243 / -0.270* / 0.255 / 0.200
Urumqi / 0.290** / 0.268** / 0.100 / 0.170**

**Significant at the 0.01 level; *Significant at the 0.05 level.

Table S4 Significance tests on the regression models developed using the 12 sample points in summer days at the ecoregion scale.

Variables used / Regression model (Y=ax+b) / F test / t test
a / b
R2Mean NDVI / y=-0.557x+0.456 / 17.255** / -4.154** / 5.562**
R2Mean precipitation / y=-0.001x+0.308 / 13.873** / -3.725** / 5.742**
R2Mean temperature / y=-0.029x+0.820 / 5.822* / -2.413* / 2.841*

**Significant at the 0.01 level; *Significant at the 0.05 level.

Mean NDVI, Summer Night
/ Mean NDVI, Winter Day
/ Mean NDVI, Winter Night

Mean precipitation, Summer Night
/ Mean precipitation, Winter Day
/ Mean precipitation, Winter Night

Mean temperature, Summer Night
/ Mean temperature, Winter Day
/ Mean temperature, Winter Night

Fig. S1. Linear regressions ofthe R2 values for the UIS-LST relationship againstmean NDVI (a-c), mean precipitation(mm) (d-f), and mean temperature(℃) (g-i) on the ecoregion scale and at three different times (summer night, winter day, and winter night).

Mean NDVI, Summer Day
/ Mean NDVI, Summer Night
/ Mean NDVI, Winter Day
/ Mean NDVI, Winter Night

Mean precipitation, Summer Day
/ Mean precipitation, Summer Night
/ Mean precipitation, Winter Day
/ Mean precipitation, Winter Night

Mean temperature, Summer Day
/ Mean temperature, Summer Night
/ Mean temperature, Winter Day
/ Mean temperature, Winter Night

Fig. S2. Linear regressions ofthe R2 values for the UIS-LST relationship againstmean NDVI (a-d), mean precipitation (mm) (e-h), and mean temperature (℃) (i-l) on the urban cluster scale and at four different times (summer day, summer night, winter day, and winter night)

Mean NDVI, Summer Day
/ Mean NDVI, Summer Night
/ Mean NDVI, Winter Day
/ Mean NDVI, Winter Night

Mean precipitation, Summer Day
/ Mean precipitation, Summer Night
/ Mean precipitation, Winter Day
/ Mean precipitation, Winter Night

Mean temperature, Summer Day
/ Mean temperature, Summer Night
/ Mean temperature, Winter Day
/ Mean temperature, Winter Night

Fig. S3. Linear regressions between the R2 values for the UIS-LST relationship and mean NDVI (a-d), mean precipitation (mm) (e-h), and mean temperature (℃) (i-l) on the urban core scale and at four different times (summer day, summer night, winter day, and winter night).

Fig. S4. Comparison of the slopesof the UIS-LST relationshiponthree different spatial scales (ecoregions, urban clusters, and urban core areas) and at four different times (summer day, summer night, winter day, and winter night).