Monitoring of Oil Spill Processes in the Area of the Barents Sea Using the Remote Sensing Data

Author(s):  
А Костарев ◽  
A Kostarev
2017 ◽  
Vol 202 ◽  
pp. 28-44 ◽  
Author(s):  
Ujwala Bhangale ◽  
Surya S. Durbha ◽  
Roger L. King ◽  
Nicolas H. Younan ◽  
Rangaraju Vatsavai

2013 ◽  
Vol 823 ◽  
pp. 631-635 ◽  
Author(s):  
Yan Zhou ◽  
Bin Zhou ◽  
Ying Ying Gai

To overcome the drawback that spectral matching is time consuming because of the large volume of remote sensing data, a new parallel algorithm of sea surface oil spill identification based on Graphic Process Unit (GPU) is presented in this paper by taking advantage of HJ-1 CCD remote sensing data. Taking minimum distance classification as an example, we reorganized the pre-processed image data, selected reference spectral data and stored in constant memory, and then the algorithm core code of the host was transplanted to the device so as to realize parallelization on NVIDIA GeForce GTX 550Ti device. Results showed that, the maximum speed-up ratio is up to 102. Finally, the advantage of GPU parallel computing for computationally intensive problems has also been validated through experiments. When the image size is 2048x2048, speed-up ratio is up to 89.


2015 ◽  
Vol 7 (6) ◽  
pp. 7105-7125 ◽  
Author(s):  
Jining Yan ◽  
Lizhe Wang ◽  
Lajiao Chen ◽  
Lingjun Zhao ◽  
Bomin Huang

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