@article{(Open Science Index):https://publications.waset.org/pdf/15851,
	  title     = {Evaluation of Graph-based Analysis for Forest Fire Detections},
	  author    = {Young Gi Byun and  Yong Huh and  Kiyun Yu and  Yong Il Kim},
	  country	= {},
	  institution	= {},
	  abstract     = {Spatial outliers in remotely sensed imageries represent
observed quantities showing unusual values compared to their
neighbor pixel values. There have been various methods to detect the
spatial outliers based on spatial autocorrelations in statistics and data
mining. These methods may be applied in detecting forest fire pixels
in the MODIS imageries from NASA-s AQUA satellite. This is
because the forest fire detection can be referred to as finding spatial
outliers using spatial variation of brightness temperature. This point is
what distinguishes our approach from the traditional fire detection
methods. In this paper, we propose a graph-based forest fire detection
algorithm which is based on spatial outlier detection methods, and test
the proposed algorithm to evaluate its applicability. For this the
ordinary scatter plot and Moran-s scatter plot were used. In order to
evaluate the proposed algorithm, the results were compared with the
MODIS fire product provided by the NASA MODIS Science Team,
which showed the possibility of the proposed algorithm in detecting
the fire pixels.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {10},
	  year      = {2007},
	  pages     = {3179 - 3184},
	  ee        = {https://publications.waset.org/pdf/15851},
	  url   	= {https://publications.waset.org/vol/10},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 10, 2007},
	}