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Sensors 2009, 9(2), 961-979; doi:10.3390/s90200961

A Contextual Fire Detection Algorithm for Simulated HJ-1B Imagery

1
State Key Laboratory of Remote Sensing Science, School of Geography, State Key Laboratory of Remote Sensing Science, Beijing Normal University, 100875, Beijing, P.R. China
2
Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences, 518054, Shenzhen, P.R. China
3
The Geography and Planning College of Ludong University, 264025, Yantai, P.R. China
*
Author to whom correspondence should be addressed.
Received: 20 November 2008 / Revised: 29 December 2008 / Accepted: 6 January 2009 / Published: 13 February 2009
(This article belongs to the Section Remote Sensors)
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Abstract

The HJ-1B satellite, which was launched on September 6, 2008, is one of the small ones placed in the constellation for disaster prediction and monitoring. HJ-1B imagery was simulated in this paper, which contains fires of various sizes and temperatures in a wide range of terrestrial biomes and climates, including RED, NIR, MIR and TIR channels. Based on the MODIS version 4 contextual algorithm and the characteristics of HJ-1B sensor, a contextual fire detection algorithm was proposed and tested using simulated HJ-1B data. It was evaluated by the probability of fire detection and false alarm as functions of fire temperature and fire area. Results indicate that when the simulated fire area is larger than 45 m2 and the simulated fire temperature is larger than 800 K, the algorithm has a higher probability of detection. But if the simulated fire area is smaller than 10 m2, only when the simulated fire temperature is larger than 900 K, may the fire be detected. For fire areas about 100 m2, the proposed algorithm has a higher detection probability than that of the MODIS product. Finally, the omission and commission error were evaluated which are important factors to affect the performance of this algorithm. It has been demonstrated that HJ-1B satellite data are much sensitive to smaller and cooler fires than MODIS or AVHRR data and the improved capabilities of HJ-1B data will offer a fine opportunity for the fire detection. View Full-Text
Keywords: Fire detection; simulated HJ-1B imagery; contextual algorithm Fire detection; simulated HJ-1B imagery; contextual algorithm
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Qian, Y.; Yan, G.; Duan, S.; Kong, X. A Contextual Fire Detection Algorithm for Simulated HJ-1B Imagery. Sensors 2009, 9, 961-979.

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