Analysis on the impact of geothermal exploitation on ground temperature with thermal infrared remote sensing technology

2011 ◽  
Author(s):  
Hong-bin Yang ◽  
Sheng-ke Yang ◽  
Xiu-yan Jing ◽  
Wen Ke Wang
Keyword(s):  
Remote Sensing ◽  
Thermal Infrared ◽  
Ground Temperature ◽  
Thermal Infrared Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Infrared Remote Sensing ◽  
The Impact

scholarly journals Impact of the Revisit of Thermal Infrared Remote Sensing Observations on Evapotranspiration Uncertainty—A Sensitivity Study Using AmeriFlux Data

2019 ◽  
Vol 11 (5) ◽  
pp. 573 ◽  
Author(s):  
Pierre Guillevic ◽  
Albert Olioso ◽  
Simon Hook ◽  
Joshua Fisher ◽  
Jean-Pierre Lagouarde ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Solar Radiation ◽  
Thermal Infrared ◽  
Sensitivity Study ◽  
Time Of Day ◽  
Surface Solar Radiation ◽  
Thermal Infrared Remote Sensing ◽  
Temporal Sampling ◽  
Infrared Remote Sensing ◽  
The Impact

Thermal infrared remote sensing observations have been widely used to provide useful information on surface energy and water stress for estimating evapotranspiration (ET). However, the revisit time of current high spatial resolution (<100 m) thermal infrared remote sensing systems, sixteen days for Landsat for example, can be insufficient to reliably derive ET information for water resources management. We used in situ ET measurements from multiple Ameriflux sites to (1) evaluate different scaling methods that are commonly used to derive daytime ET estimates from time-of-day observations; and (2) quantify the impact of different revisit times on ET estimates at monthly and seasonal time scales. The scaling method based on a constant evaporative ratio between ET and the top-of-atmosphere solar radiation provided slightly better results than methods using the available energy, the surface solar radiation or the potential ET as scaling reference fluxes. On average, revisit time periods of 2, 4, 8 and 16 days resulted in ET uncertainties of 0.37, 0.55, 0.73 and 0.90 mm per day in summer, which represented 13%, 19%, 23% and 31% of the monthly average ET calculated using the one-day revisit dataset. The capability of a system to capture rapid changes in ET was significantly reduced for return periods higher than eight days. The impact of the revisit on ET depended mainly on the land cover type and seasonal climate, and was higher over areas with high ET. We did not observe significant and systematic differences between the impacts of the revisit on monthly ET estimates that are based on morning or afternoon observations. We found that four-day revisit scenarios provided a significant improvement in temporal sampling to monitor surface ET reducing by around 40% the uncertainty of ET products derived from a 16-day revisit system, such as Landsat for instance.

Exploration of Offshore Oil and Gas Resources Using Thermal Infrared Remote Sensing

2012 ◽  
Vol 170-173 ◽  
pp. 1029-1032
Author(s):  
Yu Lin Cai ◽  
Zhao Jun Song ◽  
Chun Zhi Shan
Keyword(s):  
Remote Sensing ◽  
Oil And Gas ◽  
Thermal Infrared ◽  
Thermal Infrared Remote Sensing ◽  
The North ◽  
Sensing Technology ◽  
Infrared Remote Sensing ◽  
Oil And Gas Resources ◽  
Offshore Oil And Gas ◽  
Offshore Oil

abstract:Remote sensing technology is playing anincreasingly important role in the investigation and exploration of oil and gasresources. Using thermal infrared remote sensing technology to detect offshoreoil and gas resources is one of new methods, but there are many uncertainties. Inthis paper, MODIS data are used to explore oil and gas resources availabilityin the North Yellow Sea Basinthrough extracting the temperature anomaly areas. Result shows that this methodcan be effective in assisting in exploring undersea oil and gas resources.

Estimation of crop transpiration and its scale effect based on ground and UAV thermal infrared remote sensing images

2021 ◽  
Vol 131 ◽  
pp. 126389
Author(s):  
Mengjie Hou ◽  
Fei Tian ◽  
S. Ortega-Farias ◽  
C. Riveros-Burgos ◽  
Tong Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Scale Effect ◽  
Thermal Infrared ◽  
Remote Sensing Images ◽  
Thermal Infrared Remote Sensing ◽  
Infrared Remote Sensing
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