scholarly journals Computational modeling of land surface temperature using remote sensing data to investigate the spatial arrangement of buildings and energy consumption relationship

2020 ◽  
Vol 14 (1) ◽  
pp. 254-270 ◽  
Author(s):  
Maryam Faroughi ◽  
Mehrdad Karimimoshaver ◽  
Farshid Aram ◽  
Ebrahim Solgi ◽  
Amir Mosavi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Energy Consumption ◽  
Computational Modeling ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Spatial Arrangement ◽  
Sensing Data

Study on the Application and Comparative Analysis of Land Surface Temperature Retrieval Method Based on Multi-Sensor Remote Sensing Data

2014 ◽  
Vol 1010-1012 ◽  
pp. 1276-1279 ◽  
Author(s):  
Yin Tai Na
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Advantages And Disadvantages ◽  
Urban Heat ◽  
Split Window Algorithm ◽  
Temperature Retrieval

The three commonly used remote sensing land surface temperature retrieval methods are described, namely single-window algorithm, split window algorithm and multi-channel algorithm, which have their advantages and disadvantages. The land surface temperature (LST) of study area was retrieved with multi-source remote sensing data. LST of study area was retrieved with the split window algorithm on January 10, 2003 and November 19, 2003 which is comparatively analyzed with the LST result of ETM+data with the single-window algorithm and the LST result of ASTER data with multi channel algorithm in the same period. The results show that land surface temperature of different land features are significantly different, where the surface temperature of urban land is the highest, and that of rivers and lakes is the lowest, followed by woodland. It is concluded that the expansion of urban green space and protection of urban water can prevent or diminish the urban heat island.

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