scholarly journals Research on Thermal Discharge Pollution of Xiangshan Power Plant Based on Remote Sensing

2012 ◽  
Vol 6-7 ◽  
pp. 128-134
Author(s):  
Yuan Lin ◽  
Zhong Yang Guo ◽  
Peng Peng Kan ◽  
Shu Feng Ye
Keyword(s):  
Remote Sensing ◽  
Energy Demand ◽  
Power Plants ◽  
Thermal Power ◽  
Thermal Infrared ◽  
Coastal Environment ◽  
Normal Operation ◽  
Thermal Discharge ◽  
Thermal Infrared Remote Sensing ◽  
Sensing Technology

Thermal power technology has brought great convenience for human electricity energy demand, but thermal discharge from thermal power plants has caused great harm to the coastal environment. Therefore, it’s important to strengthen the monitoring of thermal pollution from power plants for guarantee the normal operation of coastal environment and ecological system. Thermal infrared remote sensing technology provides a new measure for monitoring the thermal discharge. In this paper, we use mono-window algorithm and Landsat thermal infrared data to retrieved the sea surface temperature around Xiangshan Power Plants, and achieved the result of 1~5.4°C temperature rise in 106.52km2 in Xiangshan Harbor, revealed the spatial distribution regularities of thermal discharge and discussed the influence of thermal discharge on costal environment.

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.

scholarly journals PCAN—Part-Based Context Attention Network for Thermal Power Plant Detection in Remote Sensing Imagery

2021 ◽  
Vol 13 (7) ◽  
pp. 1243
Author(s):  
Wenxin Yin ◽  
Wenhui Diao ◽  
Peijin Wang ◽  
Xin Gao ◽  
Ya Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Power Plants ◽  
State Of The Art ◽  
Thermal Power ◽  
Image Interpretation ◽  
Remote Sensing Image ◽  
Thermal Power Plants ◽  
Average Precision ◽  
Deep Convolutional Neural Networks ◽  
Multi Scale

The detection of Thermal Power Plants (TPPs) is a meaningful task for remote sensing image interpretation. It is a challenging task, because as facility objects TPPs are composed of various distinctive and irregular components. In this paper, we propose a novel end-to-end detection framework for TPPs based on deep convolutional neural networks. Specifically, based on the RetinaNet one-stage detector, a context attention multi-scale feature extraction network is proposed to fuse global spatial attention to strengthen the ability in representing irregular objects. In addition, we design a part-based attention module to adapt to TPPs containing distinctive components. Experiments show that the proposed method outperforms the state-of-the-art methods and can achieve 68.15% mean average precision.

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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