Application of partial least squares regression in detecting the important landscape indicators determining urban land surface temperature variation

2018 ◽  
Vol 33 (7) ◽  
pp. 1133-1145 ◽  
Author(s):  
Yanxu Liu ◽  
Jian Peng ◽  
Yanglin Wang
Keyword(s):  
Surface Temperature ◽  
Least Squares ◽  
Temperature Variation ◽  
Partial Least Squares ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Partial Least Squares Regression ◽  
Least Squares Regression ◽  
Landscape Indicators ◽  
Surface Temperature Variation

Land Surface Temperature Variation and Major Factors in Beijing, China

2008 ◽  
Vol 74 (4) ◽  
pp. 451-461 ◽  
Author(s):  
Rongbo Xiao ◽  
Qihao Weng ◽  
Zhiyun Ouyang ◽  
Weifeng Li ◽  
Erich W. Schienke ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Temperature Variation ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Major Factors ◽  
Beijing China ◽  
Surface Temperature Variation

Does urbanization increase diurnal land surface temperature variation? Evidence and implications

2017 ◽  
Vol 157 ◽  
pp. 247-258 ◽  
Author(s):  
Yen-Ching Chen ◽  
Hao-Wei Chiu ◽  
Yuan-Fong Su ◽  
Yii-Chen Wu ◽  
Ke-Sheng Cheng
Keyword(s):  
Surface Temperature ◽  
Temperature Variation ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Surface Temperature Variation

scholarly journals Variations of Land Surface Temperature and Its Relationship with Land Cover and Changes in IPB Campus, Dramaga Bogor 2013-2018

2019 ◽  
Vol 125 ◽  
pp. 01004
Author(s):  
Nafiriair Yufan Madakarah ◽  
Supriatna ◽  
Adi Wibowo ◽  
Masita Dwi Mandini Manessa ◽  
Yoanna Ristya
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Spatial Pattern ◽  
Temperature Variation ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Northern Region ◽  
Landsat 8 ◽  
Vegetation Density ◽  
Surface Temperature Variation

At the present time university can be called "small cities" due to their size of area, population and various kinds of activities. Bogor Agricultural University is a campus that can represent a city in smaller scope with a high variety of land cover. Further, the variation of land cover will affect the surface temperature variation. This study aims to determine spatial pattern of land surface temperature variation and relationship with land cover and also the changes. The data used in this study generated from Landsat 8 imagery and field surveys, then analyze using spatial and statistical analysis tools. The results show temperature has a spatial pattern associated with the land cover. Where the highest temperature tends to be located in the central region in the form of a built-up area and the lowest temperature tends to be located in northern region in the form of forest area. The highest increase in temperature tends to appear in the area that shows changes from vegetation to built-up area. Moreover, this study also found that this phenomenon only appears with temperature value were 7ºC greater than the increase in temperature on a similar land cover. Finally, this study proves that the higher vegetation density will create a lower temperature of land surface, while the higher building density creates a higher land surface temperature.

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