
Proceedings Paper
Design and implementation for satellite remote sensing forest fire-points automatic monitoring systemFormat | Member Price | Non-Member Price |
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Paper Abstract
Satellite remote sensing monitoring of forest fire-points is a routine operation of weather service. By taking advantage of
remote sensing information's characteristics such as relatively fixed resolution, little geometric distortion and quite stable
data quality, the thesis establishes Henan Satellite Remote Sensing Forest Fire-points Automatic Monitoring System in
the way of automatic geography registration based on gray correlation and control point database, which can realize
automation of the whole process including automatic monitoring,automatic geography registration,automatic fire-points
monitoring,automatic production releasing and cell phone short-message notice of fire-points warning information. The
system could greatly improve service efficiency. Automatic registration of remote sensing information based on gray
correlation and control point database features simpleness and quickness. Through automatic geography registration
testing of sunny EOS/MODIS data (at daytime and nightime) during 18 periods from February 2008 to May 2008 in
Henan Province with average error of registration is 0.637 pixels at daytime and 0.319 at nighttime, it can fully meet
ordinary operation requirements. Fire-point identification and fire-point area estimate method in the system can be
applied to monitoring different fires at daytime and at nighttime. Besides, it can automatically screen effective fire-points
according to background geographic information, and thus it can improve monitoring accuracy.
Paper Details
Date Published: 20 August 2009
PDF: 8 pages
Proc. SPIE 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI, 74541L (20 August 2009); doi: 10.1117/12.826823
Published in SPIE Proceedings Vol. 7454:
Remote Sensing and Modeling of Ecosystems for Sustainability VI
Wei Gao; Thomas J. Jackson, Editor(s)
PDF: 8 pages
Proc. SPIE 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI, 74541L (20 August 2009); doi: 10.1117/12.826823
Show Author Affiliations
Chunhui Zou, Henan Institute of Meteorological Science (China)
China Meteorological Administration (China)
Huailiang Chen, Henan Institute of Meteorological Science (China)
China Meteorological Administration (China)
Huailiang Chen, Henan Institute of Meteorological Science (China)
Qing Yin, PLA Information Engineering Univ. (China)
Published in SPIE Proceedings Vol. 7454:
Remote Sensing and Modeling of Ecosystems for Sustainability VI
Wei Gao; Thomas J. Jackson, Editor(s)
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