Detecting coal fires with a neural network to reduce the effect of solar radiation of Landsat Thematic Mapper thermal infrared images

International Journal of Remote Sensing

Volumn 22, Issue 6, 2001, Pages 933-944

  Deng, W ^a   Wan, Y Q ^b   Zhao, R C ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^b Aerophotogrammetry and Remote Sensing of China Coal   (China)

Author keywords

[No Author keywords available]

Indexed keywords

FIRES; INFRARED IMAGING; MATHEMATICAL MODELS; NEURAL NETWORKS; SOLAR RADIATION;

LANDSAT THEMATIC MAPPER (TM);

COAL COMBUSTION;

ARTIFICIAL NEURAL NETWORK; COAL; FIRE; INFRARED IMAGERY; LANDSAT THEMATIC MAPPER; SOLAR RADIATION; SURFACE TEMPERATURE;

(NORTH); CHINA;

EID: 0035870909     PISSN: 01431161     EISSN: None     Source Type: Journal    
DOI: 10.1080/014311601300074469     Document Type: Article

References (17)

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8. Estimating surface radiation fluxes in the Arctic from TOVS brightness temperatures
9. Accelerating convergence of the back-propagation method
10. Using a DEM to reduce the effect of solar radiance on Landsat TM thermal IR images and detect coal fires
11. Retrieving forest stand parameters from SAR backscatter data using a neural network trained by a canopy backscatter model
12. Surface roughness determination using spectral correlation of scattered intensities and an artificial neural network technique
13. A method to evaluate the capability of Landsat TM band 6 data for sub-pixel coal fire detection