Quantifying ocean surface oil thickness using thermal remote sensing

2021 ◽  
Vol 261 ◽  
pp. 112513
Author(s):  
Junnan Jiao ◽  
Yingcheng Lu ◽  
Chuanmin Hu ◽  
Jing Shi ◽  
Shaojie Sun ◽  
...  
Sensors ◽  
2017 ◽  
Vol 17 (7) ◽  
pp. 1542 ◽  
Author(s):  
Thomas Udelhoven ◽  
Martin Schlerf ◽  
Karl Segl ◽  
Kaniska Mallick ◽  
Christian Bossung ◽  
...  

2012 ◽  
Author(s):  
Christopher M. U. Neale ◽  
S. Sivarajan ◽  
A. Masih ◽  
C. Jaworowski ◽  
H. Heasler

2014 ◽  
Vol 7 (1) ◽  
Author(s):  
Morris Scherer Warren ◽  
Antônio Heriberto de Castro Teixeira ◽  
Lineu Neiva Rodrigues ◽  
Fernando Braz Tangerino Hernandez

Author(s):  
S. Schulte ◽  
F. Hillen ◽  
T. Prinz

Collecting vast amount of data does not solely help to fulfil information needs related to crowd monitoring, it is rather important to collect data that is suitable to meet specific information requirements. In order to address this issue, a prototype is developed to facilitate the combination of UAV-based RGB and thermal remote sensing datasets. In an experimental approach, image sensors were mounted on a remotely piloted aircraft and captured two video datasets over a crowd. A group of volunteers performed diverse movements that depict real world scenarios. The prototype is deriving the movement on the ground and is programmed in MATLAB. This novel detection approach using combined data is afterwards evaluated against detection algorithms that only use a single data source. Our tests show that the combination of RGB and thermal remote sensing data is beneficial for the field of crowd monitoring regarding the detection of crowd movement.


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