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Proceedings Paper

Research about the location technologies of forest fire detecting based on GIS
Author(s): An Zhang; Qingwen Qi; Lili Jiang; Chaohui Guo
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Paper Abstract

Forest fire caused damages of property and loss of human life. Detecting a forest fire and get the location is very significant in the fire early warning. More early and more prompt detecting fire and determining fire position as far as possible could avoid and reduce loss of the disaster. At present there are three ways regarding the forest fire early warning and location determining which included: monitoring form Remote Sense Satellite image, manual observation and patrols, and automatic monitoring through CCD camera long-distance video. Overall evaluation regarding the three location technologies in forest fire early warning, the CCD camera detecting method is suitable in the fire rapid Response. An automatic forest fire surveillance system was running to detect the fire by using visible light images from the remote cameras. If a forest fire was detected, an alarm will be activated. The observation point elevation values, vertical offsets, horizontal and vertical scanning angles, and scanning distances will be also be sent to the central control room. The spatial orientation will be computed and showed on the electronic map. Key location technologies based on CCD camera included the image processing technique for automatically detecting forest fire and the visibility analyzes technique for the digital elevation model. Jing gang Mountain which locates in Jiangxi province of China is taken as an example. With the help of this automatic monitoring through CCD camera long-distance video and visibility analyzes, scientists and government administrators can make decision-supporting easily when they know exactly where a forest fire is. At last the shortage of CCD camera detecting method was discussed. We cannot depend on CCD camera detecting equipment and technologies only. With foundation of the automatic video frequency supervisory system, we should also strengthen manual observation and satellite remote sensing monitor.

Paper Details

Date Published: 7 August 2007
PDF: 9 pages
Proc. SPIE 6754, Geoinformatics 2007: Geospatial Information Technology and Applications, 67541N (7 August 2007); doi: 10.1117/12.764907
Show Author Affiliations
An Zhang, Institute of Geographical Sciences and Natural Resources Research (China)
Qingwen Qi, Institute of Geographical Sciences and Natural Resources Research (China)
Lili Jiang, Institute of Geographical Sciences and Natural Resources Research (China)
Chaohui Guo, Institute of Geographical Sciences and Natural Resources Research (China)


Published in SPIE Proceedings Vol. 6754:
Geoinformatics 2007: Geospatial Information Technology and Applications

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