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.
Highlights
Biomass burning has tremendous impact on the Earth’s ecosystems and climate, as it drastically alters the landscape and biological structure, and emits large amounts of greenhouse gases and aerosol particles [1]
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
If the fire area is smaller than 10 m2, only when the fire temperature is larger than 900 K may the fire be detected
Summary
Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced The Geography and Planning College of Ludong University, 264025, Yantai, P.R. China Received: 20 November 2008; in revised form: 29 December 2008 / Accepted: 6 January 2009 /
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