Improvements in land surface temperature retrieval based on atmospheric water vapour content and atmospheric temperature

2014 ◽  
Vol 35 (13) ◽  
pp. 4881-4904 ◽  
Author(s):  
Lisheng Song ◽  
Zhizhong Zhao ◽  
Jianbo Xu ◽  
Shaomin Liu ◽  
Kejing Peng ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Water Vapour ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Atmospheric Temperature ◽  
Atmospheric Water ◽  
Water Vapour Content ◽  
Atmospheric Water Vapour ◽  
Temperature Retrieval

Evaluation of Land Surface Temperature Retrieved from MODIS Data

2013 ◽  
Vol 785-786 ◽  
pp. 1333-1336
Author(s):  
Xiao Feng Yang ◽  
Xing Ping Wen
Keyword(s):  
Surface Temperature ◽  
Brightness Temperature ◽  
Land Surface Temperature ◽  
Global Climate Change ◽  
Land Surface ◽  
Global Climate ◽  
Average Temperature ◽  
Profile Line ◽  
Weather Stations ◽  
Temperature Retrieval

Land surface temperature (LST) is important factor in global climate change studies, radiation budgets estimating, city heat and others. In this paper, land surface temperature of Guangzhou metropolis was retrieved from two MODIS imageries obtained at night and during the day respectively. Firstly, pixel values were calibrated to spectral radiances according to parameters from header files. Then, the brightness temperature was calculated using Planck function. Finally, The brightness temperature retrieval maps were projected and output. Comparing two brightness temperature retrieval maps, it is concluded that the brightness temperature retrieval are more accurate at night than during the day. Comparing the profile line of brightness temperature from north to south, the brightness temperature increases from north to south. Temperature different from north to south is larger at night than during the day. The average temperature nears 18°C at night and the average temperature nears 26°C during the day, which is consistent with the surface temperature observed by automatic weather stations.

scholarly journals COMPARATIVE ANALYSIS OF SPLIT-WINDOW AND SINGLE-CHANNEL ALGORITHMS FOR LAND SURFACE TEMPERATURE RETRIEVAL OF A PSEUDO-INVARIANT TARGET

2020 ◽  
Vol 26 (2) ◽  
Author(s):  
Pâmela Suélen Käfer ◽  
Silvia Beatriz Alves Rolim ◽  
Lucas Ribeiro Diaz ◽  
Nájila Souza da Rocha ◽  
María Luján Iglesias ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Single Channel ◽  
Temperature Retrieval
Sign in / Sign up

Export Citation Format

Share Document