Impacts of Large-Area Impervious Surfaces on Regional Land Surface Temperature in the Great Pearl River Delta, China

2019 ◽  
Vol 47 (11) ◽  
pp. 1831-1845 ◽  
Author(s):  
Yuling Ma ◽  
Kun Yang ◽  
Shaohua Zhang ◽  
Mingchan Li
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Pearl River Delta ◽  
River Delta ◽  
Pearl River ◽  
Impervious Surfaces ◽  
Large Area ◽  
Regional Land

scholarly journals SPATIAL AND TEMPORAL ANALYSIS ON THE EVOLUTION CHARACTERISTICS OF LAND SURFACE TEMPERATURE IN THE PEARL RIVER DELTA REGION

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 713-720
Author(s):  
Q. Y. Huang ◽  
J. L. Jing
Keyword(s):  
High Temperature ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Pearl River Delta ◽  
Pearl River ◽  
Pearl River Delta Region ◽  
Delta Region ◽  
The Pearl River Delta ◽  
The Pearl River

Abstract. With the rapid development of social economy and the continuous progress of urbanization in the Pearl River Delta region, the urban surface temperature had a significant change, which seriously affects people's normal life. The MOD11B3 LST_Day_6km product and other auxiliary data were selected as data sources, and the temperature-standard deviation method, the profile method and the coefficient method were used to analyze the spatial and temporal evolution characteristics of land surface temperature in the Pearl River Delta Region from 2000–2015. The research results showed that: (1) the maximum surface temperature from 2000 to 2015 in June, July and August showed an upward trend, while the minimum temperature showed a fluctuation downward trend, and the average temperature changed gently. (2) the surface temperature had a spatial pattern of low on all sides, and high in the middle. The high temperature zone were mainly distributed in Guangzhou, Dongguan, Foshan and Shenzhen cities and the surrounding areas. And the high temperature areas were more concentrated and showed a spreading direction of East and South. (3) The profile analysis showed that the surface temperature had a double-peak feature along the profile line, and the temperature decreased with the distance farther away from the center of the high temperature zone. (4) The correlation coefficient between land surface temperature and elevation, vegetation index were −0.551 and −0.734 respectively, both passing p < 0.01 significance test, indicating that the surface temperature had a significant negative correlation relationship with elevation and vegetation index. Therefore, strengthen urban greening is of great significance to the healthy development of the city.

scholarly journals On the Scale Effect of Relationship Identification between Land Surface Temperature and 3D Landscape Pattern: The Application of Random Forest

2022 ◽  
Vol 14 (2) ◽  
pp. 279
Author(s):  
Qiong Wu ◽  
Zhaoyi Li ◽  
Changbao Yang ◽  
Hongqing Li ◽  
Liwei Gong ◽  
...  
Keyword(s):  
Random Forest ◽  
Linear Regression ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Landscape Metrics ◽  
Landscape Pattern ◽  
Land Surface ◽  
Landscape Patterns ◽  
Impervious Surfaces ◽  
Multi Scale

Urbanization processes greatly change urban landscape patterns and the urban thermal environment. Significant multi-scale correlation exists between the land surface temperature (LST) and landscape pattern. Compared with traditional linear regression methods, the regression model based on random forest has the advantages of higher accuracy and better learning ability, and can remove the linear correlation between regression features. Taking Beijing’s metropolitan area as an example, this paper conducted multi-scale relationship analysis between 3D landscape patterns and LST using Pearson Correlation Coefficient (PCC), Multiple Linear Regression and Random Forest Regression (RFR). The results indicated that LST was relatively high in the central area of Beijing, and decreased from the center to the surrounding areas. The interpretation effect of 3D landscape metrics on LST was more obvious than that of the 2D landscape metrics, and 3D landscape diversity and evenness played more important roles than the other metrics in the change of LST. The multi-scale relationship between LST and the landscape pattern was discovered in the fourth ring road of Beijing, the effect of the extent of change on the landscape pattern is greater than that of the grain size change, and the interpretation effect and correlation of landscape metrics on LST increase with the increase in the rectangle size. Impervious surfaces significantly increased the LST, while the impervious surfaces located at low building areas were more likely to increase LST than those located at tall building areas. It seems that increasing the distance between buildings to improve the rate of energy exchange between urban and rural areas can effectively decrease LST. Vegetation and water can effectively reduce LST, but large, clustered and irregularly shaped patches have a better effect on land surface cooling than small and discrete patches. The Coefficients of Rectangle Variation (CORV) power function fitting results of landscape metrics showed that the optimal rectangle size for studying the relationship between the 3D landscape pattern and LST is about 700 m. Our study is useful for future urban planning and provides references to mitigate the daytime urban heat island (UHI) effect.

TM/ETM+/LDCM Images for Studying Land Surface Temperature (LST) Interplay with Impervious Surfaces Changes over Time Within the Douala Metropolis, Cameroon

2017 ◽  
Vol 46 (1) ◽  
pp. 131-143 ◽  
Author(s):  
Salomon Cesar Nguemhe Fils ◽  
Mumbfu Ernestine Mimba ◽  
Jean Guy Dzana ◽  
Joachim Etouna ◽  
Patrick Valerie Mounoumeck ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Impervious Surfaces ◽  
Changes Over Time ◽  
Over Time

Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China

2007 ◽  
Vol 19 (2) ◽  
pp. 250-256 ◽  
Author(s):  
Rong-bo XIAO ◽  
Zhi-yun OUYANG ◽  
Hua ZHENG ◽  
Wei-feng LI ◽  
Erich W SCHIENKE ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Spatial Pattern ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Impervious Surfaces ◽  
Beijing China
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