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Proceedings Paper

Design and implementation for satellite remote sensing forest fire-points automatic monitoring system
Author(s): Chunhui Zou; Huailiang Chen; Qing Yin
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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
Show Author Affiliations
Chunhui Zou, 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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